a literature review of lean manufacturing

• DOI: 10.1080/17509653.2013.825074
• Corpus ID: 110768642

A literature review of lean manufacturing

• Shaman Gupta , S. Jain
• Published 26 September 2013
• Business, Engineering
• International Journal of Management Science and Engineering Management

176 Citations

An empirical review of lean manufacturing and their strategies, a review on lean manufacturing implementation tools, human-related lean practices for manufacturing smes’ lean transformation: a systematic literature review, industry 4.0 impact on lean manufacturing: literature review, application of lean manufacturing using kaizen analysis: a case study, a mini review: lean management tools in assembly line at automotive industry, the hybrid lean system to improve manufacturing environment, product quality improvement policies in industry 4.0: characteristics, enabling factors, barriers, and evolution toward zero defect manufacturing, soft lean practices for successful lean production system implementation in malaysia automotive smes: a proposed framework, lean practices and their effect on performance: a literature review, 70 references, a lean route to manufacturing survival.

• Highly Influential

Key Practice Areas of Lean Manufacturing

Lean manufacturing in continuous process industry : an empirical study, a survey on lean manufacturing implementation in malaysian automotive industry, supplier issues for lean implementation, critical success factors for lean implementation within smes, an investigation of manufacturing performance improvement through lean production: a study on bangladeshi garment firms, lean manufacturing in the screw cutting sector: assessment of maturity level, lean manufacturing best practices in smes, the roles of communication process for an effective lean manufacturing implementation, related papers.

Showing 1 through 3 of 0 Related Papers

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Recommended Articles
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

A perception survey of lean management practices for safer off-site construction.

1. Introduction

2. materials and methods, 2.1. prior literature review, 2.2. survey design and administration, 2.3. sampling, 2.4. data analysis procedures, 3.1. survey response, 3.2. respondents profile, 3.3. pre-testing survey response, 3.4. mean score analysis and ranking of lmps, 3.5. average mean score analysis and ranking of lmts, 4. discussion, 4.1. lmps for safer osc, 4.1.1. mistake-proofing, 4.1.2. first run studies, 4.1.3. daily huddle meetings, 4.1.4. improved visualisation, 4.1.5. 5s housekeeping, 4.1.6. last planner system, 5. theoretical and practical implications of the study, 6. conclusions, contributions, and limitation of the study, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

• Wuni, I.B.; Shen, G.Q. Barriers to the adoption of modular integrated construction: Systematic review and meta-analysis, integrated conceptual framework, and strategies. J. Clean. Prod. 2020 , 249 , 119347. [ Google Scholar ] [ CrossRef ]
• Ayinla, K.O.; Cheung, F.; Tawil, A. Demystifying the concept of offsite manufacturing method: Towards a robust definition and classification system. Constr. Innov. 2019 , 20 , 223–246. [ Google Scholar ] [ CrossRef ]
• Chatzimichailidou, M. and Ma, Yue. Using BIM in the safety risk management of modular construction. Saf. Sci. 2022 , 154 , 105852. [ Google Scholar ] [ CrossRef ]
• Wuni, I.B.; Shen, G.P.Q.; Mahmud, A.T. Critical risk success factors in the application of modular integrated construction: A systematic review. Int. J. Constr. Manag. 2022 , 22 , 133–147. [ Google Scholar ] [ CrossRef ]
• Lu, N.; Korman, T. Implementation of building information modeling (BIM) in modular construction: Benefits and challenges. In Proceedings of the Construction Research Congress 2010: Innovation for Reshaping Construction Practice, Banff, AB, Canada, 8–10 May 2010; pp. 1136–1145. [ Google Scholar ]
• Lessing, J. Industrialised House Building—Conceptual Orientation and Strategic Perspectives- Lund University (Media—Tryck). 2015. Available online: https://www.semanticscholar.org/paper/Industrialised-House-Building-Conceptual-and-Lessing/0c9a3e51bee96389ea85efc2de7bf71a4e2385cb (accessed on 9 June 2021).
• HM Government. The Construction Playbook. Cabinet Office. 2020. Available online: https://www.gov.uk/government/publications/the-construction-playbook (accessed on 19 July 2024).
• Gibb, A. Standardization and pre-assembly-distinguishing myth from reality using case study research. J. Constr. Manag. Econ. 2001 , 19 , 307–315. [ Google Scholar ] [ CrossRef ]
• Smith, R.E. Off-Site Construction Implementation Resources: Off-Site and Modular Construction Explained ; National Institute of Building Services: Washington, DC, USA; University of Utah: Salt Lake City, UT, USA, 2016. [ Google Scholar ]
• Jonsson, H.; Rudberg, M. Production System Classification Matrix: Matching Product Standardization and Production-System Design. J. Constr. Eng. Manag. 2015 , 141 , 05015004. [ Google Scholar ] [ CrossRef ]
• Chatzimichailidou, M.M.; Whyte, J. Dealing with complexity in modular construction. In Proceedings of the 8th International Conference on Mass Customisation and Personalization—Community of Europe (MCP-CE 2018), Novi Sad, Serbia, 19–21 September 2018; pp. 47–52. [ Google Scholar ]
• El-Abidi, K.M.A.; Ghazali, F.E.M. Motivations and limitations of prefabricated building: An overview. Applied Mech. Mat. 2015 , 802 , 668–675. [ Google Scholar ] [ CrossRef ]
• Jeong, G.; Kim, H.; Lee, H.; Park, M.; Hyun, H. Analysis of safety risk factors of modular construction to identify accident trends. J. Asian Archit. Build. Eng. 2021 , 21 , 1040–1052. [ Google Scholar ] [ CrossRef ]
• Ahn, S.; Crouch, L.; Kim, T.W.; Rameezdeen, R. Comparison of worker Safety risks between onsite and offsite construction methods: A site management perspective. J. Constr. Eng. Manag. 2020 , 146 , 1–11. [ Google Scholar ] [ CrossRef ]
• Bajjou, M.S.; Chafi, A.; En-Nadi, A. The potential effectiveness of lean construction tools in promoting safety on construction sites. Int. J. Eng. Res. Afr. 2017 , 33 , 179–193. [ Google Scholar ] [ CrossRef ]
• Ghosh, S. Does Formal Daily Huddle Meetings Improve Safety Awareness. Int. J. Constr. Educ. Res. 2014 , 10 , 285–299. [ Google Scholar ] [ CrossRef ]
• Carvajal-Arango, D.; Bahamon-Jaramillo, S.; Aristizabal-Monsalve, P.; Vasquez-Hernandez, A.; Botero, L.F.B. Relationships between lean and sustainable construction: Positive impacts of lean practices over sustainability during construction phase. J. Clean. Prod. 2019 , 234 , 1322–1337. [ Google Scholar ] [ CrossRef ]
• Kalyuni, M.; Wodajo, T. Application of a Design Method for Manufacture and Assembly. MSc Thesis, Chalmers University of Technology, Gothenburg, Sweden, 2012. Available online: https://publications.lib.chalmers.se/records/fulltext/164233.pdf (accessed on 14 January 2024).
• Han, S.; Bouferguene, A.; Al-Hussein, M.; Hermann, U. 3D-based crane evaluation system for mobile crane operation selection on modular-based heavy construction sites. J. Constr. Engin. Manag. 2017 , 143 , 12. [ Google Scholar ] [ CrossRef ]
• Li, X.; Han, S.; Gül, M.; Al-Hussein, M. Automated post-3D visualization ergonomic analysis system for rapid workplace design in modular construction. Autom. Constr. 2019 , 98 , 160–174. [ Google Scholar ] [ CrossRef ]
• Franks, E. Safety and Health in Prefabricated Construction: A New Framework for Analysis ; University of Washington: Washington, DC, USA, 2018. [ Google Scholar ]
• Liu, Q.; Ye, G.; Feng, Y. Workers’ safety behaviors in the off-site manufacturing plan. Eng. Constr. Arch. Mang. 2019 , 27 , 765–784. [ Google Scholar ] [ CrossRef ]
• Goh, J.T.; Hu, S.; Fang, Y. Human-in-the-loop simulation for crane lift planning in modular construction on-site assembly. In Proceedings of the ASCE International Conference on Computing in Civil Engineering, Atlanta, GA, USA, 17–19 June 2019; pp. 71–78. [ Google Scholar ]
• Vithanage, S.C.; Sing, M.; Davis, P. Systematic review on the identification of safety risks in off-site manufacturing (OSM). J. Eng. Des Technol. 2021 , 20 , 935–964. [ Google Scholar ] [ CrossRef ]
• Fardi, M.M.; Terouhid, S.A.; Kibert, C.J.; Hakim, H. Safety concerns related to modular/prefabricated building construction. Int. J. Inj. Control. Saf. Promot. 2017 , 24 , 10–23. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• James, J.; Ikuma, L.H.; Nahmens, I.; Aghazadeh, F. The impact of kaizen on safety in modular home manufacturing. Int. J. Adv. Manuf. Technol. 2014 , 70 , 725–734. [ Google Scholar ] [ CrossRef ]
• Ikuma, L.H.; Nahmens, I.; James, J. Use of safety and lean integrated kaizen to improve performance in modular homebuilding. J. Constr. Eng. Manag. 2011 , 137 , 551–560. [ Google Scholar ] [ CrossRef ]
• Kim, S.; Nussbaum, M.A.; Jia, B.C. Low back injury risks during construction with prefabricated (panelised) walls: Effects of task and design factors. Ergon 2011 , 54 , 60–71. [ Google Scholar ] [ CrossRef ]
• Soto, S.; Hubbard, B.; Hubbard, S. Exploring prefabrication facility safety in the U.S. Construction industry. In Proceedings of the Achieving Sustainable Construction Health and Safety, Lund, Sweden, 2–3 June 2014. [ Google Scholar ]
• Abas, N.H.; Blismas, N.; Lingard, H. Knowledge-based energy damage model for evaluating industrialised building systems (IBS) occupational health and safety (OHS) risk. In Proceedings of the 3rd International Conference on Civil and Environmental Engineering for Sustainability, IConCEES 2015, Melaka, Malaysia, 1–2 December 2015. [ Google Scholar ]
• Mao, C.; Shen, L.; Tang, L. Comparative study of greenhouse gas emissions between off-site prefabrication and conventional construction methods: Two case studies of residential projects. Energy Build. 2013 , 66 , 165–176. [ Google Scholar ] [ CrossRef ]
• Banks, C.; Kotecha, R.; Curtis, J. Enhancing high-rise residential construction through design for manufacture and assembly—A UK case study. Proc. Inst. Civ. Eng. Manag. Proc. Law 2018 , 171 , 164–175. [ Google Scholar ] [ CrossRef ]
• Chen, K.; Lu, W. Design for Manufacture and Assembly Oriented Design Approach to a Curtain Wall System: A Case Study of a Commercial Building in Wuhan, China. Sustainability 2018 , 10 , 221. [ Google Scholar ] [ CrossRef ]
• Soltaninejad, M.; Fardhosseini, N.S.; Kim, Y.W. Safety climate and productivity improvement of construction workplaces through the 6S system: Mixed-method analysis of 5S and safety integration. Int. J. Occup. Saf. Ergon. 2021 , 28 , 1811–1821. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Bashir, A.M.; Suresh, S.; Proverbs, D.; Gameson, R. A critical, theoretical, review of the impacts of lean construction tools in reducing accidents on construction sites. In Proceedings of the 27th Annual ARCOM Conference, Bristol, UK, 5–7 September 2011 ; Egbu, C., Lou, E.C.W., Eds.; Association of Researchers in Construction Management: Bristol, UK, 2011; pp. 249–258. [ Google Scholar ]
• Chileshe, N.; Njau, C.W.; Kiptoo, B.; Macharia, L.N.; Kavishe, N. Critical success factors for Public-Private Partnership (PPP) infrastructure and housing projects in Kenya. Int. J. Constr. Manag. 2020 , 22 , 1606–1617. [ Google Scholar ] [ CrossRef ]
• Osei-Kyei, R.; Chan, A.P.C.; Ameyaw, E.E. A fuzzy synthetic evaluation analysis of operational management critical success factors for public-private partnership infrastructure projects. Benchmark Int. J. 2017 , 24 , 2092–2112. [ Google Scholar ] [ CrossRef ]
• Babaunde, S.O.; Perera, S.; Adeniyi, O. Identification of critical risk factors in public-private partnership project phases in developing countries: A case of Nigeria. Benchmark Int. J. 2019 , 26 , 334–335. [ Google Scholar ] [ CrossRef ]
• Prajogo, D.I.; Sohal, A.S. The multidimensionality of TQM practices in determining quality and innovation performance: An empirical examination. Technovation 2004 , 23 , 443–453. [ Google Scholar ] [ CrossRef ]
• Tata, J.; Prasad, S.; Thorn, R. The influence of organisational structure on the effectiveness of TQM programs. J. Manag. Iss. 1999 , 11 , 440–453. [ Google Scholar ] [ CrossRef ]
• Bayhan, H.G.; Dermikesen, S.; Zhang, C.; Tezel, A. A lean construction and BIM interaction model for the construction industry. Prod. Plan. Control. 2021 , 34 , 1447–1474. [ Google Scholar ] [ CrossRef ]
• Hwang, B.G.; Shan, M.; Looi, K.Y. Key constraints and mitigation strategies for prefabricated prefinished volumetric construction. J. Clean. Prod. 2018 , 183 , 183–193. [ Google Scholar ] [ CrossRef ]
• Ameyaw, E.E.; Chan, A.P.C. Evaluation and ranking of risk factors in public-private partnership water supply projects in developing countries using fuzzy synthetic evaluation approach. Expert Syst. Appl. 2015 , 42 , 5102–5116. [ Google Scholar ] [ CrossRef ]
• Enshassi, A.; Saleh, N.; Mohamed, S. Application level of lean construction techniques in reducing accidents in construction projects. J. Financ. Manag. Prop. Constr. 2019 , 24 , 274–293. [ Google Scholar ] [ CrossRef ]
• Babalola, O.; Ibem, E.O.; Ezema, I.C. Implementation of lean practices in the construction industry: A systematic review. Built Environ. 2019 , 148 , 34–43. [ Google Scholar ] [ CrossRef ]
• Wu, X.; Yuan, H.; Wang, G.; Li, S.; Wu, G. Impacts of Lean Construction on Safety Systems: A System Dynamics Approach. Int. J. Environ. Res. Public Health 2019 , 16 , 221. [ Google Scholar ] [ CrossRef ]
• Sarhan, J.G.; Xia, B.; Fawzia, S.; Karim, A. Lean Construction Implementation in the Saudi Arabian Construction Industry. Constr. Econ. Build. 2017 , 17 , 46–69. [ Google Scholar ] [ CrossRef ]
• Ahmed, S.; Hossain, M.; Haq, I. Implementation of lean construction in the construction industry in Bangladesh: Awareness, benefits and challenges. Int. J. Build. Pathol. Adapt. 2020 , 39 , 2396–4708. [ Google Scholar ] [ CrossRef ]
• Ansah, R.H.; Sorooshian, S. Effect of lean tools to control external environment risks of construction projects. Sustain. Cities Soc. 2017 , 32 , 348–356. [ Google Scholar ] [ CrossRef ]
• Bashir, A.M. A Framework for Utilising Lean Construction Strategies to Promote Safety on Construction Sites. Ph.D. Thesis, University of Wolverhampton, Wolverhampton, WV, USA, 2013. Available online: https://wlv.openrepository.com/handle/2436/297665 (accessed on 3 September 2022).
• Aziz, R.F.; Hafez, S.M. Applying lean thinking in construction and performance improvement. Alex. Eng. J. 2013 , 52 , 679–695. [ Google Scholar ] [ CrossRef ]
• Taherdoost, H. Designing a Questionnaire for a Research Paper: A Comprehensive Guide to Design and Develop an Effective Questionnaire. Asian J. Manag. Sci. 2022 , 11 , 8–16. [ Google Scholar ] [ CrossRef ]
• Rowley, J. Designing and using research questionnaires. Manag. Res. Rev. 2014 , 37 , 308–330. [ Google Scholar ] [ CrossRef ]
• Chyung, S.Y.; Roberts, K.; Swanson, L.; Hankinson, A. Evidence-based Survey Design: The Use of a Midpoint on the Likert Scale. Int. Sci. Perf. 2017 , 56 , 15–23. [ Google Scholar ] [ CrossRef ]
• Battaglia, P. Nonprobability Sampling ; SAGE Publications: Thousand Oaks, CA, USA, 2011. [ Google Scholar ]
• Cronbach, L.J. Coefficient alpha and the internal structure of tests. Psychometrika 1951 , 16 , 297–334. [ Google Scholar ] [ CrossRef ]
• Surucu, L.; Maslakci, A. Validity and reliability in quantitative research. Business and management studies. Buss. Manag. Stud. Int. J. 2020 , 8 , 2694–2726. [ Google Scholar ] [ CrossRef ]
• Gel, Y.R.; Miao, W.; Gastwirth, J.L. Robust directed tests of normality against heavy-tailed alternatives. Comput. Stat. Data Anal. 2007 , 51 , 2734–2746. [ Google Scholar ] [ CrossRef ]
• Field, A. Discovering Statistics Using IBM SPSS Statistics: And Sex and Drugs and Rock “N” Roll , 4th ed.; Sage: Los Angeles, CA, USA, 2013. [ Google Scholar ]
• Agumba, J.N.; Haupt, T.C. The influence of health and safety practices on health and safety performance outcomes in small and medium enterprise projects in the South African construction industry. J. S. Afr. Inst. Civ. Eng. 2018 , 60 , 61–72. [ Google Scholar ] [ CrossRef ]
• Abray, W.; Smallwood, J.J. The effects of unsatisfactory working conditions on productivity in the construction industry. Procedia Eng. 2014 , 85 , 3–9. [ Google Scholar ] [ CrossRef ]
• Nunnaly, J.C. An overview of psychological measurement. In Clinical Diagnosis of Mental Disorders ; Plenum Press: New York, NY, USA, 1978; pp. 97–146. [ Google Scholar ]
• Noorzai, E. Evaluating lean techniques to improve success factors in the construction phase. Constr. Innov. 2023 , 23 , 622–639. [ Google Scholar ] [ CrossRef ]
• Aslam, M.; Gao, Z.; Smith, G. Exploring factors for implementing lean construction for rapid initial successes in construction. J. Clean. Energy 2020 , 277 , 123295. [ Google Scholar ] [ CrossRef ]
• Zhang, X.; Mohandes, S.R. Occupational health and safety in green building construction projects: A holistic Z-numbers-based risk management framework. J. Clean. Energy 2020 , 275 , 122788. [ Google Scholar ] [ CrossRef ]
• Zhu, Z.; Park, M.-W.; Koch, C.; Soltani, M.; Hammad, A.; Davari, K. Predicting movements of onsite workers and mobile equipment for enhancing construction site safety. Autom. Constr. 2016 , 68 , 95–101. [ Google Scholar ] [ CrossRef ]
• Soltanmohammadlou, N.; Sadeghi, S.; Hon, C.K.H.; Mokhtarpour-Khanghah, F. Real-time locating systems and safety in construction sites: A literature review. Saf. Sci. 2019 , 117 , 229–242. [ Google Scholar ] [ CrossRef ]
• Aisheh, Y.I.A.; Tayeh, B.A.; Alaloul, W.S.; Almalki, A. Health and safety improvement in construction projects: A lean construction approach. JOSE 2021 , 8 , 1981–1993. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Pee, L.G. Affordances for sharing domain-specific and complex knowledge on enterprise social media. Int. J. Infor. Manag. 2017 , 43 , 25–37. [ Google Scholar ] [ CrossRef ]
• Wandahl, S.; Pérez, C.T.; Salling, S.; Hansen, C.H.; Nielsen, M.K.; Nissen, T. Daily huddles’ effect on crew productivity. In Proceedings of the 31st Annual Conference of the International Group for Lean Construction (IGLC31), Lille, France, 26 June–2 July 2023; pp. 1255–1266. [ Google Scholar ]
• Anerao, S.D.; Deshmukh, S.S. Waste minimization by lean construction technology. IRJET 2016 , 3 , 1703–1707. [ Google Scholar ]
• Pestana, C.; Gambatese, J.A. Lean practices and safety performance. In Proceedings of the Construction Research Congress 2016, San Juan, PUR, USA, 31 May–2 June 2016. [ Google Scholar ] [ CrossRef ]
• Sarhan, S.; Fox, A. Barriers to Implementing Lean Construction in the UK Construction Industry. Built Hum. Environ. Rev. 2013 , 6 , 1–17. Available online: https://www.researchgate.net/publication/263658667_Barriers_to_Implementing_Lean_Construction_in_the_UK_Construction_Industry (accessed on 27 March 2023).
• Oladiran, O.J. An investigation into the usage of lean construction techniques in Nigeria. J. Constr. Proj. Manag. Innov. 2017 , 17 , 1712–1725. [ Google Scholar ]
• Camuffo, A.; Stefano, F.D.; Paolino, C. Safety reloaded: Lean operations and high involvement work practices for sustainable workplace. J. Bus. Ethics 2017 , 143 , 245–259. [ Google Scholar ] [ CrossRef ]
• Awada, M.A.; Lakkis, B.S.; Doughan, A.R.; Hamzeh, F.R. Influence of Lean Concepts on Safety in the Lebanese Construction Industry. In Proceedings of the 24th Annual Conference of the International Group for Lean Construction, Boston, MA, USA, 18–24 July 2016; pp. 63–72. [ Google Scholar ]
• Cohen, W.M.; Nelson, R.R.; Walsh, J.P. Links and Impacts: The Influence of Public Research on Industrial R and D. Manag. Sci. 2002 , 48 , 1–23. [ Google Scholar ] [ CrossRef ]

Click here to enlarge figure

Share and Cite

Simukonda, W.; Emuze, F. A Perception Survey of Lean Management Practices for Safer Off-Site Construction. Buildings 2024 , 14 , 2860. https://doi.org/10.3390/buildings14092860

Simukonda W, Emuze F. A Perception Survey of Lean Management Practices for Safer Off-Site Construction. Buildings . 2024; 14(9):2860. https://doi.org/10.3390/buildings14092860

Simukonda, Wakisa, and Fidelis Emuze. 2024. "A Perception Survey of Lean Management Practices for Safer Off-Site Construction" Buildings 14, no. 9: 2860. https://doi.org/10.3390/buildings14092860

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

A systematic literature review regarding the influence of lean manufacturing on firms' financial performance

Journal of Manufacturing Technology Management

ISSN : 1741-038X

Article publication date: 7 April 2021

Issue publication date: 17 December 2021

The lean philosophy has demonstrated its effectiveness to improve firms' operational performance. However, the impact of lean practices on financial performance is still unclear due to the poor understanding of the link between operational and financial measures and the conflictive results obtained by previous research. The purpose of this paper is to conduct a systematic literature review to understand whether lean companies have improved their financial performance. Moreover, this article aims to uncover research gaps in the literature and examine which time spans of research have been considered to analyse both the degree of lean implementation and the measurement of financial outcomes.

Design/methodology/approach

A systematic literature review has been conducted to identify peer-reviewed articles that analyse the effect of the lean production paradigm on the financial performance measures of manufacturing companies. Then, the identified articles were processed using a combination of descriptive and content analyses methods to draw new conclusions, uncover gaps and find novel paths for research.

Various authors indicate that lean initiatives lead to an enhancement of financial performance measures. JIT and TQM lean practice bundles are suggested as the best enablers of financial performance in terms of sales and profit. In contrast, according to some scholars, lean does not necessarily improve companies' financial results if it is not properly implemented.

Originality/value

Several studies have focused on analysing the effects of lean on performance. However, only a small part of the literature has addressed the study of the effects of lean practices on financial performance metrics. The originality of this study lies in the investigation of the connections between lean practices and financial performance measures found in the literature. The outcome is the identification of various possible positive impacts of some lean practices on financial metrics.

• Lean manufacturing
• Financial performance
• Business performance
• Competitiveness

Dieste, M. , Panizzolo, R. and Garza-Reyes, J.A. (2021), "A systematic literature review regarding the influence of lean manufacturing on firms' financial performance", Journal of Manufacturing Technology Management , Vol. 32 No. 9, pp. 101-121. https://doi.org/10.1108/JMTM-08-2020-0304

Emerald Publishing Limited

Copyright © 2021, Marcos Dieste, Roberto Panizzolo and Jose Arturo Garza-Reyes

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

Under the leadership of Taiichi Ohno, Toyota defined a new industrial production model focused on the reduction of waste, continuous improvement and the importance of involving all company employees ( Ohno, 1988 ). In their book, Womack et al. (1990) define lean in terms of its outcomes: “compared to mass production it uses less of everything – half the human effort in the factory, half the manufacturing space, half the investment in tools, half the engineering hours to develop a new product in half the time”.

During the last decades, the lean thinking theory has been evolving. Both researchers and practitioners have stressed the importance of extending the principles of lean production to other company areas ( Womack and Jones, 1996 ). Several industrial firms worldwide have put into practice both lean principles and practices and have achieved important transformations towards continuous improvement, value creation and waste elimination, accomplishing outstanding operational efficiency levels.

In the academic field, numerous authors have studied the aforementioned empirical evidence and have suggested that lean manufacturing initiatives improve companies' operational performance ( Demeter and Matyusz, 2011 ; Shah and Ward, 2003 ). The links between lean and operational measures have been deeply studied since it is obvious that the direct impact of lean practices is reflected in production processes' performance metrics or operational performance metrics ( Negrão et al. , 2017 ).

Nevertheless, financial performance measures are those that reflect the performance of the whole company in terms of economic indicators and portray the ability of firms to create value ( Galeazzo and Furlan, 2018 ). These performance measures are directly related with operational performance ( Fullerton et al. , 2014 ), but according to some authors, the link between both dimensions may be fragile ( Bhasin, 2012 ; Losonci and Demeter, 2013 ) as non-financial measures are not part of traditional accounting systems ( Abdel-Maksoud et al. , 2005 ). This suggests that financial performance measures could be more consequential than operational performance measures given the levels of lean maturity in current production environments.

The first studies on this topic have investigated the effect of different dimensions of the lean production system such as just in time (JIT) or total quality management (TQM) on financial performance ( Callen et al. , 2000 ; Eriksson and Hansson, 2003 ). These practices are part but not synonymous of lean production ( Hofer et al. , 2012 ). According to some authors, lean production is more than a technique; it is a holistic system approach that creates a culture in which everyone in the organization continuously improves operations ( Liker, 2004 ; Sahoo and Yadav, 2018 ). In order to study in a more holistic approach the effects of lean practices on financial performance, authors have included the other two dimensions of the lean paradigm, namely total preventive maintenance (TPM) and human resource management (HRM), applying the important work developed by Shah and Ward (2003) . According to these authors, lean practices with similar characteristics can be classified into four groups or “lean bundles” (i.e. JIT, TQM, TPM and HRM). The bundle model has been widely used by academics for the study of the impact of lean on financial performance.

Prior research suggests that lean practices have a positive effect on financial performance metrics ( Sahoo, 2019 ; Yang et al. , 2011 ), and, moreover, various studies remark the importance of implementing lean practices as a whole ( Fullerton et al. , 2014 ) and in a structured manner ( Nawanir et al. , 2013 ) to achieve better financial performance results. In contrast, some scholars do not fully agree with this evidence and suggest that the positive links between lean and financial performance are not so obvious and may depend, among others, on external ( Losonci and Demeter, 2013 ) and internal factors to the company ( Bevilacqua et al. , 2017a ).

What are the results obtained by previous research regarding the effects of lean on financial performance?

What is the connection between lean and financial performance measures?

What are the main paths for further research when concurrently investigating lean and financial performance?

The originality of this study lies in the investigation of the connections between lean practices and financial performance measures found in literature, resulting in the identification of various possible positive impacts of each practice on each indicator. In contrast, various relevant inconsistencies exposed in the literature are provided. Furthermore, understanding which time intervals have been considered for the analysis of the implementation of lean practices is strongly significant. It is also important to recognize how many years have been considered in previous research for measuring financial performance. This will allow researchers to identify which of the prior studies could be anecdotal and which are based on sustained data over time. In this regard, this paper provides relevant insights for both practitioners and scholars, remarking the importance of a long-term implementation and analysis of lean practices. These contributions facilitate the general understanding of the specific effects of lean practices on each financial performance measure so far investigated in the literature, regrouping them and giving them a numerical value to emphasize their importance. Finally, research gaps and future research recommendations are stressed in the form of research questions to enrich the study of the effects of lean practices on financial performance measures.

2. Research method

A systematic literature review has been conducted to identify peer-reviewed articles that aimed to analyse the effect of the lean production paradigm and its practices on the financial performance measures of manufacturing companies. The systematic literature review (SLR) method approaches in a precise, transparent and explicit manner the analysis of scientific research documents. This method, which includes various phases, guarantees rigour and comprehensibility to the literature review process ( Tranfield et al. , 2003 ) due to the systematic, explicit and reproducible approach adopted ( Fink, 2005 ). Several academics consider that systematic literature reviews should include the following five sequential stages ( Buchanan and Bryman, 2009 ): scope formulation, study location, study evaluation, analysis and synthesis, and reporting and using the results (see Figure 1 ). For reasons of transparency, these sequential phases and the methods used to support every stage will be explained in detail throughout the paper ( Saunders et al. , 2009 ).

Following this paragraph, in Section 2.1 , together with the premises introduced in Section 1 , the scope of the research is formulated corresponding to the first phase of the systematic literature review. Then the following stages of the literature review are successively presented in the next sections of this paper.

2.1 Scope formulation

The recent attention paid in previous research to the relationship between lean and both operational and financial performances has encouraged authors to explore its implications in different dimensions ( Dieste et al. , 2019 ). An increased emphasis has been put in previous studies regarding the analysis of the implications of lean production on operational performance ( Negrão et al. , 2017 ), and, moreover, several authors suggest that there is a direct positive effect of lean on operational performance measures ( Chavez et al. , 2013 ; Cua et al. , 2001 ; Shah and Ward, 2003 ; Shrafat and Ismail, 2019 ).

Lean manufacturing, which is frequently implemented at a shop-floor level, is naturally associated with production processes and therefore involves the use of non-financial measures which are not part of traditional accounting systems ( Abdel-Maksoud et al. , 2005 ). This suggests that lean companies may be more likely to use non-financial measures for measuring performance rather than financial performance metrics ( Nawanir et al. , 2013 ). The link between lean practices and non-financial metrics is easier to identify than the effects of lean on financial performance measures. Nevertheless, operational performance subsequently influences the entire business performance. In order to observe the ability of a lean organization to create value, it is more appropriate to understand the effects of lean production on financial performance ( Galeazzo and Furlan, 2018 ).

Previous studies have already approached the topic and demonstrated that lean implementation may have a positive impact on financial measures of manufacturing organizations ( Fullerton and Wempe, 2009 ; Hofer et al. , 2012 ; Negrão et al. , 2019 ), and, moreover, researchers suggest that to reach its potential, lean must be adopted as a holistic business strategy, instead of single isolated activities in operations ( Fullerton et al. , 2014 ). However, as suggested by Bhasin (2012) , the lean benefits on financial performance are not always obvious since the connection between financial and non-financial measures is fragile. Some other authors have already explored this issue and have confirmed that the financial benefits derived from the lean implementation are not always tangible ( Ghobakhloo and Azar, 2018 ; Losonci and Demeter, 2013 ). Moreover, some scholars suggest that lean may produce a negative impact on financial metrics due to inadequate implementation of the lean bundles (JIT, TQM, TPM and HRM) ( Galeazzo and Furlan, 2018 ), to the lack of a systematic and sustainable approach ( Bevilacqua et al. , 2017a ) or to the use of ineffective financial reporting methods ( Meade et al. , 2010 ).

In summary, various authors have already approached the impact of lean production on the financial performance of manufacturing companies. However, the academic literature exploring this research topic still needs further investigation, since the impact of lean on financial measures is still unclear due to the conflictive results already obtained by previous research. Therefore, this article provides a comprehensive literature review on the current state of the research on this relevant subject, aiming to give light on the effects of the lean philosophy on financial results, uncover gaps and inconsistencies in the literature and find new research directions.

2.2 Paper selection method

To identify the most relevant research papers for this literature review, the Scopus search database was selected since it provides extensive coverage of peer-reviewed journal articles in the scientific, technical and social sciences research fields. This SLR considered peer-reviewed articles published in the English language without limiting the search to a specific period. All fields of knowledge, as well as all subject areas available in the Scopus database, were selected.

The selected keywords were used in the title, abstract and keyword search fields using the following Boolean operators: lean AND manufacturing AND (financial OR performance). More specifically, the keyword “lean” was selected to include concepts such as “lean thinking” or “lean production”; subsequently, the keyword “manufacturing” was chosen to incorporate as far as possible studies developed within the manufacturing sector. Finally, both keywords “financial” and “performance” were selected. The first aims to address all papers investigating specifically financial measures. The keyword “performance”, which has a broader meaning, was included to identify all the articles that study the relationship between lean and performance (operational, financial and environmental), enabling this way later filtering of the articles and not losing information.

As seen in Table 1 , a total of 2,303 papers were initially found using the keywords search in the Scopus database. Thirty-one papers were not written in the English language, and thus the total number of articles listed was 2,272. By excluding reviews, conference papers, book chapters and other document types, 1,221 papers were identified. Considering only papers that fit with fields of knowledge such as engineering, management, social sciences or similar, 1,119 papers remained in the selection protocol. Then, only papers addressing issues of lean and performance measurement, evaluation or assessment were selected. Papers addressing the adoption of single practices or bundles (e.g. standalone implementation of JIT or TQM) and joint applications such as lean six sigma, lean-green or supply chain analyses were rejected, resulting in a total of 141 articles. Then, all abstracts were read, and 100 papers were excluded for lack of relevance to the study or for not having a comprehensive approach. From the 41 papers remaining, 19 were excluded after full-text reading, as these papers did not analyse any financial performance measures. During the reading process of the 22 remaining articles, the studies developed by Lewis (2000) and Hofer et al. (2012) , which have been considered by various authors from the list ( Bevilacqua et al. , 2017b ; Negrão et al. , 2017 ; Sahoo and Yadav, 2018 ), were not included in the initial sample and therefore were added. Both papers belong to the topic of interest of this study: Lewis (2000) studied financial performance while examining the sustainable competitive advantage of manufacturing firms; Hofer et al. (2012) investigated the relationship between lean production and performance but did not use the keyword “manufacturing” even though the empirical analysis developed is based on data from the US manufacturing firms. To avoid losing any other relevant articles, a final check was made of the references cited by the 24 papers already included in the sample. It was then found that there were no missing articles within the final paper selection. Finally, 24 papers over the period of 2000–2019 were identified and selected for the analysis.

The selection process developed and the final number of papers selected confirm that despite the great number of studies analysing the effects of lean on performance, only a small minority address properly the effects of lean practices on financial performance measures. Most of the studies are focused on the relationship between lean, lean six sigma or lean supply chain management practices and operational performance. As was stated before, the relationship between lean and operational performance has been deeply studied in literature as the effects of lean on operational measures are more noticeable rather than the impacts of lean on financial performance.

3. Literature review analysis

3.1 descriptive analysis.

A total number of 24 articles ( Appendix ) complied with the final selection criteria. Hence, these were all the articles that, to a certain extent, referred to lean and financial performance in operations management literature. The selected papers have been categorized according to various criteria: publication date, source of publication and research method used.

The first classification is presented in Figure 2 , which shows the sorting of the selected articles according to their publication date. To ensure greater clarity, the papers were grouped in five-year intervals starting from 2000 until 2019. The graph highlights the growing significance given in the literature to the study of the relationship between lean and financial performance, from 2010 onwards and particularly in the last 5 years.

Figure 3 shows the distribution of the selected papers by journal type. In terms of the number of publications per source, the Journal of Manufacturing Technology Management with 25% (6 articles) of the total number of lean-financial performance publications analysed, is the most repeated source of publication. Secondly, both the International Journal of Operations and Production Management and the International Journal of Production Economics contribute 12.5% each (3 articles each). These are followed by 3 journals with strong significance in the operations management field, with 2 publications each. The rest of the articles are subdivided in 6 different journals of high impact with one publication each.

The complete set of papers has been categorized in Figure 4 according to the research methodologies adopted.

As shown in Figure 4, 18 articles (75% of the total) investigated the topic through a survey-based methodology. Various survey studies employed a structural equation modelling (SEM) approach to test the theoretical relations ( Bevilacqua et al. , 2017a ; Chavez et al. , 2015 ; Fullerton et al. , 2014 ; Shrafat and Ismail, 2019 ). Other papers mainly used statistical methods such as regression analysis to process the survey data ( Forrester et al. , 2010 ; Galeazzo, 2019 ; Sahoo and Yadav, 2018 ). Studies such as Hofer et al. (2012) and Fullerton and Wempe (2009) analysed a combination of survey and secondary data to empirically investigate the relationship between lean production implementation and financial performance. Bhasin (2012) used a combination of primary data captured from 68 survey questionnaires and 7 case studies to validate research findings.

To a lesser extent, 13% of the studies (3 articles) analysed secondary data from a database. Both studies developed by Losonci and Demeter (2013) and Yang et al. (2011) used the International Manufacturing Strategy Survey (IMSS IV) data bank for their statistical analyses. This database contains 711 observations developed between February 2005 and March 2006 collected from 23 countries. In addition, Zhu and Lin (2017) developed an empirical analysis of Chinese manufacturing firms using data from the China Stock Market and Accounting Research (CSMAR) database and CNINFO information to understand if lean manufacturing adoption improves firm value.

Only one article from the final paper selection developed a literature review. The research conducted by Negrão et al. (2017) analyses 83 papers published until 2015. Authors examine articles that evaluate the degree of adoption of lean manufacturing practices and the links between them and operational, financial and environmental performance measures. Lewis (2000) analysed the empirical evidence drawn from three case studies to argue whether lean production can reinforce competitive advantage and improve firms' overall financial performance. Finally, Meade et al. (2010) studied the impact of lean manufacturing adoption on net profit utilising a multi-period simulation technique. In summary, these last three articles that approached the topic with three different methodologies represented 12% of the paper sample.

3.2 Content analysis

3.2.1 lean practices in literature.

The purpose of this section is to understand which lean practices or groups/bundles of lean practices are the most used in the sample of 23 manuscripts under analysis. The literature review paper was excluded from this analysis since it gathers previous results from other studies. Therefore, 47 different lean practices were found in the whole literature sample. Due to their relevance, the ten most used lean practices and bundles are listed in Figure 5 in descending order of citations. Both lean bundles and practices were included in the figure to emphasize whether scholars utilized single practices to study the effect of lean on financial performance or they preferred to gather them into groups of practices. It is worth noting that only lean practices that were quoted at least 6 times in the reviewed studies were included in the graph.

As stated above, various authors do not refer to single lean practices but to groups of lean tools: these are the well-known lean bundles developed by Shah and Ward (2003) . For this reason, it is possible to identify TPM and TQM as two of the most important lean techniques for the analysis of the effects of lean on financial performance. However, a deeper analysis allows identifying 5 out of 10 practices that match with the JIT lean bundle. These practices are pull/Kanban, SMED, continuous flow, cellular layouts and JIT, and authors such as Bhasin (2012) , Fullerton et al. (2014) and Nawanir et al. (2016) employed most of them in their empirical analyses. Hence, practices belonging to the JIT bundle seem to be the most frequently analysed by researchers in the field (see Figure 5 ).

Furthermore, practices included in both TQM and TPM bundles have been studied by many authors ( Galeazzo, 2019 ; Ghobakhloo and Azar, 2018 ; Sahoo and Yadav, 2018 ). In contrast, except for the employee involvement practice, which is ranked within the most utilized practices ( Bevilacqua et al. , 2017a ; Hofer et al. , 2012 ), HRM practices seem to receive less attention in the literature. This may occur because the “soft” part of lean (which is related to behavioural and social aspects) sometimes does not receive equal importance from companies than more technical lean tools, and therefore this is reflected in the results of previous research ( Sahoo, 2019 ).

3.2.2 Financial performance measures in literature

In this section, the attention is focused on the financial performance measures considered in the existing literature when analysing the relationships between lean implementation and financial performance of manufacturing firms.

Within the sample of 23 papers analysed (excluding the literature review article), a total number of 32 different financial/business performance metrics were found. In Figure 6 , the ten most used financial measures are listed in descending order of citations.

According to Figure 6 , the most used financial performance measure within the selected papers is the return on investment ratio (ROI). Out of 23 studies, 7 used this ratio to measure the degree of achievement of profit-oriented outcomes ( Hofer et al. , 2012 ; Yang et al. , 2011 ). This measure, according to Nawanir et al. (2016) , shows how the firm's assets have been used to make earnings, thus showing how proficient management is.

Secondly, 6 out of the 23 articles used the sales growth rate. This indicator is utilized to show how firms are performing in the market ( Bevilacqua et al. , 2017a ; Chavez et al. , 2015 ). Similarly, the absolute level of sales was utilized by 6 articles in order to assess market ( Yang et al. , 2011 ) and financial performance ( Lewis, 2000 ; Negrão et al. , 2019 ). Again, 6 articles used the return on assets ratio (ROA) to evaluate firms' efficiency improvements from a financial point of view ( Fullerton et al. , 2014 ; Zhu and Lin, 2017 ).

Thirdly, 2 measures were studied each by 5 papers out of the 23 under analysis. The level of net profit, together with other performance measures, was used by Sahoo (2019) to evaluate the strategic business performance of both soft and hard lean practices. Similarly, the profitability indicator was used by 5 articles. It is noteworthy that these studies did not indicate which specific ratio was used for its calculation in each company. The level of profitability of a firm can be calculated by several ratios considering its financial statements: for instance, Shrafat and Ismail (2019) measured it to evaluate one of the three dimensions of business performance (profitability, market share and customer satisfaction).

To a lesser extent, 4 out of 23 articles used profit margin as a financial performance measure ( Bevilacqua et al. , 2017b ; Chavez et al. , 2015 ; Nawanir et al. , 2013 , 2016 ). The same number of papers studied the return on sales ratio (ROS) since it is a widely accepted measure of profitability ( Hofer et al. , 2012 ) and eliminates some of the effects of reduced inventories in the arising of the ROA ratio ( Fullerton and Wempe, 2009 ). Finally, both revenue growth rate and asset turnover were considered each by 2 papers out of 23.

3.2.3 Time spans of analysis in literature

In previous sections, both lean practices and financial measures have been analysed separately according to their presence in literature. Besides, understanding which periods have been considered for the analysis of the implementation of lean practices is strongly significant. Generally, the time during which a company has been implementing lean principles and the extent of the implementation is known as lean maturity. Additionally, it is highly important to summarize how many years have been considered to analyse the financial performance of firms in previous studies. Both topics are crucial to find out which of the previous studies could be anecdotal and which were based on sustained data.

This section presents the time spans selected by each of the 23 papers (excluding the literature review) and describes how authors analysed both lean implementation and financial performance results.

First, 15 out of 23 papers did not consider any period of implementation of lean practices. Most authors relied on cross-sectional survey-based studies (e.g. Fullerton and Wempe, 2009 ; Ghobakhloo and Azar, 2018 ; Sahoo, 2019 ), evaluating lean practices' degree of implementation using Likert scales in the research questionnaires. In contrast, Bhasin (2012) only considered the number of years of lean practices' implementation at the time the survey was conducted by requesting it in the research questionnaire. Similarly, various scholars, in addition to the information about the years of lean implementation experience, requested a Likert scale evaluation of the degree of leanness ( Galeazzo and Furlan, 2018 ; Sahoo and Yadav, 2018 ) or to assess whether a lean practice has been implemented in the company or not ( Galeazzo, 2019 ). Other authors (4 out of 23 papers) evaluated jointly the degree of implementation and years of implementation of each practice using a Likert scale ( Bevilacqua et al. , 2017a , b ; Yang et al. , 2011 ) or by semi-structured interviews ( Lewis, 2000 ).

Secondly, 8 out of 23 of the papers did not consider a specific period for evaluating the variation of financial metrics. These studies generally used a Likert scale to analyse the evolution of companies’ financial measures either alone (e.g. Negrão et al. , 2019 ; Shrafat and Ismail, 2019 ) or compared to their main competitors ( Chavez et al. , 2015 ; Ghobakhloo and Azar, 2018 ). The rest of the articles studied the relationship between lean practices and financial measures considering different time spans of research. For instance, various authors analysed performance changes over three-year periods by rating their variation using a Likert scale ( Nawanir et al. , 2013 ; Yusuf and Adeleye, 2002 ); others used a database for extracting the indicators of the last three years ( Forrester et al. , 2010 ) or for obtaining financial measures in three different points in time ( Galeazzo and Furlan, 2018 ). In total, 9 out of 23 papers used a time span of three years.

In addition, Zhu and Lin (2017) considered a longer period of time and extracted firms' financial measures over five years from a database to analyse performance changes. Galeazzo (2019) used also a database to investigate performance changes over at least a two-year period. Bevilacqua et al. (2017a) and Meade et al. (2010) developed shorter analyses; the first study evaluated a time span of two years using a Likert scale in the survey questionnaire, while the second research used a single year period generating values with a simulation method. Lewis (2000) obtained data from the financial reports of the case firms under analysis at two different points in time: immediately before lean transformation and five years later as part of the qualitative analysis developed.

Finally, Bhasin (2012) requested the respondents of a survey to quote a percentage improvement or deterioration against each index as a direct consequence of the lean transformation. This was achieved by providing a scorecard within the survey containing the financial metrics under analysis and asking interviewees the time since lean production has been implemented.

4. The effect of lean practices on financial performance measures in literature

As a final analysis, this section describes the effects of lean practices on financial performance metrics found in the selected studies. For this purpose, the positive, mixed and negative results observed are acknowledged in the following paragraphs.

4.1 Positive effects of lean practices on financial performance measures

From the analyses carried in Sections 3.2.1 and 3.2.2 , it turned out that 47 lean practices and 32 financial performance measures were used in the studies considered. A first analysis of the papers after the full-text reading process permitted to conclude that many articles highlight a positive impact of lean practices on financial measures. Among the 23 papers, several lean practices with similar characteristics have been evaluated with a huge number of financial performance metrics, and some of these practices and metrics have the same scope but a different nomenclature.

The JIT bundle includes practices such as pull/Kanban, small lots of production, SMED, continuous flow production and cellular layouts.

The TQM bundle gathers lean practices like kaizen, customer involvement, visual management, statistical process control and 5S.

The TPM bundle contains practices related to preventive and autonomous maintenance

The last bundle, known as HRM, includes practices such as multiskilled workforce, employee involvement and lean leadership.

The ROI category includes the ROI ratio and ROI growth rate.

The sales group gathers metrics such as sales, net sales, ROS and sales growth rate.

The ROA category encompasses the ROA ratio and ROA growth rate.

The profit group includes measures of profitability, profit margin and net profit.

Table 2 illustrates the positive relationships found in the literature between the lean practice bundles and the financial performance categories. The value inside the cells shows the number of times a positive relationship has been found in the literature between the bundle in the row and the financial performance category of the column. In addition, the rightmost column in Table 2 shows the degree of importance of each lean bundle according to its positive effect on financial performance. Similarly, the last row indicates the financial categories that benefit the most from the implementation of lean practices according to extant literature. Nevertheless, it must be emphasized that not all the relationships found in the literature were positive. Some scholars suggest that lean does not necessarily improve firms' financial results, and, moreover, various authors state that lean may have negative impacts on financial performance metrics. This evidence is analysed in Section 4.2 .

The results shown in Table 2 suggest that the JIT bundle, with techniques related to production flow, could have a positive influence on the measures corresponding to sales and profit. For instance, Chavez et al. (2015) suggest that internal lean practices such as setup time reduction techniques (SMED) or pull production systems are positively associated with organizational performance metrics related to sales or profit. Negrão et al. (2019) added that some practices like continuous flow practices should be prioritized, rather than other practices to help firms produce positive effects on sales and profitability. Likewise, but with less relevance in the literature analysed, a comprehensive implementation of lean practices including cellular layouts and small lots production may entail an improvement on business performance metrics such as ROI ( Nawanir et al. , 2016 ). Authors such as Fullerton et al. (2014) suggested that a holistic implementation of lean practices including Kanban and one-piece flow contributed to the improvement of the ROA ratio.

Secondly, according to some scholars, TQM practices such as continuous improvement (or kaizen), 5S, customer involvement and statistical process control uncover and eliminate hidden wastes, inefficient processes and could enhance business performance parameters. Even soft lean practices included in this bundle such as customer involvement and supplier development and partnership contributed in some studies to the improvement of sales performance measures ( Sahoo, 2019 ). Besides, Shrafat and Ismail (2019) indicated that techniques such as statistical process control and 5S contributed to the profitability enhancement of the Jordanian companies investigated. Less evidence of a positive relationship between TQM practices and ROI and ROA ratios was found, and one of these studies was developed by Sahoo and Yadav (2018) .

Besides, the literature suggests that HRM practices such as employee involvement are critical to the successful adoption of lean production, and this improvement initiative has varied positive impacts on the ROS metric ( Fullerton and Wempe, 2009 ). In addition, profit measures might be improved using other soft lean practices such as flexible human resources as was remarked by Nawanir et al. (2013 , 2016) .

To a lesser extent, various studies have also indicated that TPM practices in a lean implementation context can contribute to enhancing financial performance measures. Literature has demonstrated the positive impact of this lean bundle, although with less emphasis, on measures such as profitability ( Bhasin, 2012 ), sales ( Hofer et al. , 2012 ), ROI ( Sahoo and Yadav, 2018 ) and ROA ( Galeazzo and Furlan, 2018 ).

As a final point, it is noteworthy that the figures in Table 2 are not identical to the figures included in Figures 5 and 6 . The reason is that in this table, only positive relationships present in the literature are analysed. For instance, if a paper suggests that two different practices produce improvements in one single performance measure in the same study, in this chart the article will be considered twice as it represents both effects of two practices in one performance measure. Furthermore, not all lean practices (47 practices) impacted positively on all financial metrics found in the literature sample (32 metrics), and therefore a lower number of practices and measures were used to compose the bundles-groups included in Table 2 .

4.2 Other effects of lean practices on financial performance measures

As previously stated, the results achieved to date seem to be encouraging towards the implementation of lean practices and principles to improve different dimensions of financial performance. However, eight studies suggest that lean does not necessarily improve companies' financial results.

By comparing firms with a high degree of application of lean practices and low lean implementers, Bevilacqua et al. (2017b) highlighted that there were no major differences between high lean performers and low lean performers in terms of business growth (i.e. profit margin) when firms vary the batch size, reduce production time, reduce the percentage of finished products which are subject to claim and increase investment in research and development.

Losonci and Demeter (2013) conclude that despite the strong positive link between lean production and good operational performance, financial and market benefits derived from lean implementation are not obvious in terms of sales, ROS and ROI. This occurs due to the influence of external factors such as market dynamics, new entrants and customization.

Similar conclusions were obtained previously by Lewis (2000) in his qualitative exploratory study. The paper discusses the impact that lean has had on the overall financial performance, with empirical material drawn from three case studies. Research findings confirm that becoming lean does not automatically result in improved financial performance in terms of gross profit and sales. Moreover, the study remarks that the main issue seems to be the company's ability to appropriate the value generated by any savings the firm can make. In fact, the organizations under analysis obtained very different results, and, moreover, the firm with less progress towards lean production achieved the best financial results.

Furthermore, authors such as Ghobakhloo and Azar (2018) suggest agile manufacturing as an enabler of marketing and financial performance (i.e. ROA, ROI and sales growth rate) as an alternative to lean manufacturing, which is primarily associated with operational performance. Among the main reasons for these results, authors remark the importance of both costs and benefits of the lean transformation. For instance, firms have to bear the costs of dismantling previous physical plant layouts or training employees. Therefore, as there are many potential costs and indirect benefits associated with lean implementation, its ability to increase financial results might be unclear.

These results are in line with the conclusions obtained previously by Yusuf and Adeleye (2002) . By comparing both lean and agile strategies in the UK context, authors concluded that the lean companies scored highly on cost and quality. These results turned out to have a limited relationship with financial metrics such as sales and net profit. Thus, the authors suggested adopting agile manufacturing strategies instead of lean strategies, since agile companies performed better.

Bevilacqua et al. (2017a) reject a direct relationship between lean practice bundles implementation and company growth performance (i.e. sales growth rate). Authors stress that the lack of a systematic and sustainable approach, such as value stream mapping, may lead to a misapplication of lean manufacturing tools. Moreover, the lack of employees' training, limited resources and the absence of any policy deployment are important limitations for the development of lean projects. This justifies the absence of connection between firm performances and lean practices.

In addition to these studies, some of the papers analysed suggest that lean may have negative impacts on financial performance metrics. In other words, these studies in some way reject a positive relationship between lean practices and financial performance. For example, Meade et al. (2010) suggest that lean tends to generate a negative impact on turnover and profit margins in the short term, due to stocks being reduced, and remarks that traditional financial reporting methods may be inadequate to accurately reflect operational improvements through the early stages of a lean programme.

Finally, the results obtained by Galeazzo and Furlan (2018) showed that some lean bundles always have to be complemented by other lean bundles to improve financial metrics, because none of them can explain alone the firm's successful financial performance. According to the authors, JIT in combination with TQM or, instead, with TPM and HRM as complementary conditions is enough for achieving successful financial performance. In contrast, two combinations may produce limited results in terms of ROA; the first is characterized by a low level or lack of implementation of the TQM lean bundle, and the second combination complements the absence of HRM with the absence of TPM. They remark that with the limited implementation of the lean bundles, firms fail in obtaining good financial results.

5. Discussion and paths for future research

The aim of this research is to discuss whether firms that have applied lean principles and methods have improved their financial performance measures while analysing previous research on this topic. The main findings, inconsistencies and research gaps emerging from the SLR analysis can be examined as follows.

The study of the relationship between lean and financial metrics has experienced growing attention in recent years. Most of the papers have investigated the topic through a survey-based approach, which is an appropriate research method to understand whether there is a relationship between lean implementation and financial performance. Nevertheless, other research methodologies can be employed in order to complete the research results already obtained by a survey ( Negrão et al. , 2017 ; Sahoo, 2019 ). For example, by using qualitative research methods such as case studies, researchers may be able to better understand the nature and complexity of the complete phenomenon under analysis and to develop in-depth investigations in different contexts ( Yin, 1994 ). Furthermore, qualitative studies can be used to empirically identify linkages between variables (lean practices and financial metrics) and to provide practical tools for professionals dealing with these issues in their work practice ( Voss et al. , 2002 ).

As regards the most analysed lean practices, the literature review carried out in this paper highlighted the importance of JIT and TQM bundles. In parallel, financial performance indicators such as ROI, sales growth rate, sales, ROA, net profit, profitability, profit margin and ROS seem to be the most measured. These results are in line with the analysis of the relevant literature developed by Hofer et al. (2012) , who suggest that the JIT bundle is one of the most typically used by researchers in this area and remark that the JIT concept is part but not synonymous of lean production. Additionally, the same authors also acknowledge ROA and ROI as some of the most used financial performance metrics in previous research. Thus, other practices corresponding to the HRM bundle and to a lesser extent the TPM bundle, which have received less attention in the literature, should be prioritized in future analyses. These studies can be complemented with other financial performance measures that can broaden the spectrum of the analysis of the impact of lean on financial performance. Furthermore, a significant emphasis on financial outcomes is needed as more and more manufacturing firms reach higher lean maturity levels and are competing in similar conditions (e.g. lower production costs, superior responsiveness, higher quality levels and similar technologies) ( Inman et al. , 2011 ).

Regarding the time spans of research considered in the literature, most of the papers did not evaluate the implementation of lean practices during a specific time frame. In contrast, more than half of the studies considered different time spans ranging from 1 to 5 years to observe the financial performance variation of companies. The authors who do not consider a time interval for their analyses, acknowledge the cross-sectional nature of their studies as a limitation and suggest the development of longitudinal studies in order to gain more insights ( Sahoo and Yadav, 2018 ; Shrafat and Ismail, 2019 ) and analyse causal factors ( Negrão et al. , 2019 ; Sahoo, 2019 ). In this sense, it is important to understand that the lean transformation process usually lasts more than a year since it represents a strategic-changing activity ( Saad et al. , 2006 ). Moreover, lean benefits are visible only in the medium/long term, while investments in implementation, which should worsen financial results, are recorded in the short term ( Negrão et al. , 2017 ). In brief, short time spans of research when studying the effects of lean on performance may lead to less accurate results that may not be generalizable. As stated by Voss et al. (2002) , the longer the period over which a phenomenon is studied, the greater the opportunity to observe the sequential relationships of events. Hence, longitudinal studies represent a relevant research opportunity for scholars aiming to understand the nature and the evolution of the effects of lean on financial performance. This method allows the analysis of the evolution of financial performance metrics over time as firms achieve lean maturity.

The main results of this literature review suggest that lean initiatives could lead to an enhancement of financial performance measures according to various authors. More specifically, JIT (e.g. flow production, pull/Kanban, setup time reduction, cellular layouts) and TQM (e.g. customer involvement, statistical process control, supplier development, 5S) bundles seem to include the most impactful practices on financial measures such as sales and profit. These results are in line with previous findings that suggest that JIT practices enhance firms' profitability ( Callen et al. , 2000 ; Fullerton and McWatters, 2001 ) and that companies implementing quality improvement practices (TQM) will outperform competitors in terms of financial performance ( Eriksson and Hansson, 2003 ; Fullerton and Wempe, 2009 ). In addition, the HRM and TPM lean bundles did not present a high number of publications relating them to financial performance goals. The literature demonstrates that these lean practices may not negatively affect financial performance ( Negrão et al. , 2019 ; Sahoo, 2019 ; Yang et al. , 2011 ). Nevertheless, practices from both dimensions are increasingly being included in firms' lean implementation strategies since their deployment influences other practices. For instance, HRM practices have proven to be decisive due to their mediating role between soft and hard lean practices ( Sahoo, 2019 ). Similarly, TPM practices are crucial for achieving continuous flow production, equipment effectiveness and workplace improvement ( Galeazzo and Furlan, 2018 ). Thus, it might be interesting to obtain further empirical evidence about which HRM and TPM practices best improve financial performance metrics in lean contexts.

On the other hand, there are some existing divergences between lean and financial performance that have been already been acknowledged in the literature. Various authors suggest that lean practices no longer provide a competitive advantage as it is a highly spread strategy among competitors in sectors such as the motor industry. Moreover, approaches like agile manufacturing are recommended in some studies. According to diverse authors, agile firms consider external competitive factors and may incur in lower costs of implementation ( Ghobakhloo and Azar, 2018 ; Yusuf and Adeleye, 2002 ). The lean and agile approaches do not have to be mutually exclusive strategies in today's dynamic environments and many businesses are already considering the amalgamation of both strategies. Other studies suggest that lean practices' implementation must be done holistically in order to succeed ( Nawanir et al. , 2013 ; Sahoo and Yadav, 2018 ) since there is a complementarity between bundles that will lead to better financial performance than a separated implementation or an execution of single practices. Galeazzo and Furlan (2018) suggest that some specific lean practices' combinations may produce lower results. There is scope for future research adopting a more holistic approach and discerning the multifaceted concept of lean. Still, future studies must consider lean practices from all dimensions to observe the complementarities and the joint effect of the whole lean practices implemented by manufacturers. Besides, the study of different combinations of lean practices for improving financial metrics is beyond the scope of this research and still requires further research in the future.

Finally, Meade et al. (2010) propose that lean tends to generate negative impacts on turnover and profit margins in the short term, and they remark the importance of financial reporting methods. Moreover, Bevilacqua et al. (2017a) highlight that the lack of systematic and sustainable approaches justifies the absence of connection between firm performances and lean practices. Thus, evidence suggests that lean manufacturing is not a quick remedy to financial issues ( Galeazzo and Furlan, 2018 ). Table 3 presents eleven research questions that can guide future research paths in four research streams.

6. Conclusions, limitations and contributions

This article contributes to the lean body of knowledge by presenting a systematic review of the existing literature that considers the relationship between the implementation of lean practices and financial performance measures. The research findings and discussion provide new insights for scholars and contribute to the definition of clearer paths for further research.

By suggesting the utilization of research methods such as qualitative studies, long-term analyses and highlighting both lean practices and financial measures that need further investigation, this paper provides a relevant contribution for academics in the field. This paper also confirms that despite the great number of studies analysing the effects of lean on performance, only a small part of the literature addresses properly the study of the effects of lean practices on financial performance measures. This article differs from other literature review studies by developing a systematic approach to select papers that empirically analyse the effects of lean on financial performance indicators. The research methodology excludes papers utilizing combined paradigms (lean six sigma, lean-green or lean supply chain) or only focusing on operational performance measures. Furthermore, this study identifies and structures the results already obtained by previous empirical research to guide future empirical studies.

Additionally, there are several managerial implications considering best practices in the employment of lean production. Research findings may encourage firms, not entirely committed with the lean philosophy, to consider lean for achieving better financial results. Moreover, the results derived from the present research can provide managers with a general overview of the effects of lean practices on financial performance so they can develop deeper and richer knowledge on this topic. This research also encourages them, and hence their organizations, to implement lean practices in a coherent, sustained and holistic manner while measuring the impact of lean on financial performance indicators. This article may also be useful to understand the sequence of application of the practices to obtain specific financial outcomes. The study highlights which techniques could contribute to improve specific financial measures within a lean transformation context. In this regard, as suggested by Fullerton et al. (2014) , companies may need to adapt their financial and accounting control systems to align them with lean manufacturing initiatives. This may lead to an increasing interaction between operations and accounting functions ( Maskell et al. , 2011 ).

On the other hand, this research has encountered some limitations that need to be acknowledged. Two relevant papers were not included in the initial paper selection sample since they did not meet the searching criteria. To avoid missing any other important articles, a systematic approach was adopted and a reference checking approach was used. Furthermore, the authors used different labels for both practices and indicators to carry out their studies. This limitation was overcome by grouping lean practices and financial measures with the same scope, respectively, in bundles and generic names. Additionally, the results from this study need to be contextualized since each paper under investigation considered different types of analysis, and, moreover, each study encompassed firms with very specific characteristics. In other words, the cause-effect relationships between the use of a technique and the expected result on a specific financial performance metric also depend on the contextual conditions that are internal but also external to organizations ( Dieste et al. , 2020 ; Panizzolo, 1998 ). Moreover, lean practices work together as a system and may have different configurations that could explain successful (or unsuccessful) financial performance ( Galeazzo and Furlan, 2018 ).

Concluding, financial performance has always been one of the strategic imperatives for businesses and generally good results are connected to operational efficiency. Lean manufacturing practices have demonstrated in both practice and research that they can produce a relevant contribution to financial performance enhancement. Nevertheless, lean practices need to be implemented with coherence and holistically to support complementarities and should be assisted by an appropriate and sustained performance measurement system. Finally, lean production must be treated as a strategic activity whose effects are visible in the long run to achieve the best results.

SLR phases and structure of the paper

Article classification by year of publication

Article classification by source of publication

Article classification by research method adopted

Lean practices most frequently studied

Financial measures most frequently studied

Article selection criteria

Summary of the positive effects of lean on financial performance measures

Research questions to guide further research

Articles included in the literature review

Abdel-Maksoud , A. , Dugdale , D. and Luther , R. ( 2005 ), “ Non-financial performance measurement in manufacturing companies ”, The British Accounting Review , Elsevier , Vol. 37 No. 3 , pp. 261 - 297 .

Bevilacqua , M. , Ciarapica , F.E. and De Sanctis , I. ( 2017a ), “ Lean practices implementation and their relationships with operational responsiveness and company performance: an Italian study ”, International Journal of Production Research , Taylor & Francis , Vol. 55 No. 3 , pp. 769 - 794 .

Bevilacqua , M. , Ciarapica , F.E. and De Sanctis , I. ( 2017b ), “ Relationships between Italian companies' operational characteristics and business growth in high and low lean performers ”, Journal of Manufacturing Technology Management , Emerald Publishing , Vol. 28 No. 2 , pp. 250 - 274 .

Bhasin , S. ( 2012 ), “ Performance of Lean in large organisations ”, Journal of Manufacturing Systems , The Society of Manufacturing Engineers , Vol. 31 No. 3 , pp. 349 - 357 .

Buchanan , D. and Bryman , A. ( 2009 ), The Sage Handbook of Organizational Research Methods , Sage Publications Ltd , London .

Callen , J.L. , Fader , C. and Krinsky , I. ( 2000 ), “ Just-in-time: a cross-sectional plant analysis ”, International Journal of Production Economics , Elsevier , Vol. 63 No. 3 , pp. 277 - 301 .

Chavez , R. , Gimenez , C. , Fynes , B. , Wiengarten , F. and Yu , W. ( 2013 ), “ Internal lean practices and operational performance ”, International Journal of Operations and Production Management , Emerald Group Publishing , Vol. 33 No. 5 , pp. 562 - 588 .

Chavez , R. , Yu , W. , Jacobs , M. , Fynes , B. , Wiengarten , F. and Lecuna , A. ( 2015 ), “ Internal lean practices and performance: the role of technological turbulence ”, International Journal of Production Economics , Elsevier , Vol. 160 , pp. 157 - 171 .

Cua , K.O. , McKone , K.E. and Schroeder , R.G. ( 2001 ), “ Relationships between implementation of TQM, JIT, and TPM and manufacturing performance ”, Journal of Operations Management , Elsevier , Vol. 19 No. 6 , pp. 675 - 694 .

Demeter , K. and Matyusz , Z. ( 2011 ), “ The impact of lean practices on inventory turnover ”, International Journal of Production Economics , Elsevier , Vol. 133 No. 1 , pp. 154 - 163 .

Dieste , M. , Panizzolo , R. , Garza-Reyes , J.A. and Anosike , A. ( 2019 ), “ The relationship between lean and environmental performance: practices and measures ”, Journal of Cleaner Production , Vol. 224 , pp. 120 - 131 .

Dieste , M. , Panizzolo , R. and Garza-Reyes , J.A. ( 2020 ), “ Evaluating the impact of lean practices on environmental performance: evidences from five manufacturing companies ”, Production Planning and Control , Vol. 31 No. 9 , pp. 739 - 756 .

Eriksson , H. and Hansson , J. ( 2003 ), “ The impact of TQM on financial performance ”, Measuring Business Excellence , Emerald Group Publishing , Vol. 7 No. 1 , pp. 36 - 50 .

Fink , A. ( 2005 ), Conducting Research Literature Reviews: From the Internet to Paper , Sage publications , Thousand Oaks .

Forrester , P.L. , Soriano-Meier , H. and Garza-Reyes , J.A. ( 2010 ), “ Lean production, market share and value creation in the agricultural machinery sector in Brazil ”, Journal of Manufacturing Technology Management , Vol. 21 No. 7 , pp. 853 - 871 .

Fullerton , R.R. and McWatters , C.S. ( 2001 ), “ The production performance benefits from JIT implementation ”, Journal of Operations Management , Elsevier , Vol. 19 No. 1 , pp. 81 - 96 .

Fullerton , R.R. and Wempe , W.F. ( 2009 ), “ Lean manufacturing, non-financial performance measures, and financial performance ”, International Journal of Operations and Production Management , Vol. 29 No. 3 , pp. 214 - 240 .

Fullerton , R.R. , Kennedy , F.A. and Widener , S.K. ( 2014 ), “ Lean manufacturing and firm performance: the incremental contribution of lean management accounting practices ”, Journal of Operations Management , Elsevier B.V. , Vol. 32 Nos 7–8 , pp. 414 - 428 .

Galeazzo , A. ( 2019 ), “ Degree of leanness and lean maturity: exploring the effects on financial performance ”, Total Quality Management and Business Excellence , Taylor & Francis , pp. 1 - 19 .

Galeazzo , A. and Furlan , A. ( 2018 ), “ Lean bundles and configurations: a fsQCA approach ”, International Journal of Operations and Production Management , Emerald Publishing , Vol. 38 No. 2 , pp. 513 - 533 .

Ghobakhloo , M. and Azar , A. ( 2018 ), “ Business excellence via advanced manufacturing technology and lean-agile manufacturing ”, Journal of Manufacturing Technology Management , Emerald Publishing , Vol. 29 No. 1 , pp. 2 - 24 .

Hofer , C. , Eroglu , C. and Hofer , A.R. ( 2012 ), “ The effect of lean production on financial performance: the mediating role of inventory leanness ”, International Journal of Production Economics , Elsevier , Vol. 138 No. 2 , pp. 242 - 253 .

Inman , R.A. , Sale , R.S. , Green , K.W. Jr and Whitten , D. ( 2011 ), “ Agile manufacturing: relation to JIT, operational performance and firm performance ”, Journal of Operations Management , Elsevier , Vol. 29 No. 4 , pp. 343 - 355 .

Lewis , M.A. ( 2000 ), “ Lean production and sustainable competitive advantage ”, International Journal of Operations and Production Management , Emerald Group Publishing , Vol. 20 No. 8 , pp. 959 - 978 .

Liker , J.K. ( 2004 ), The Toyota Way , McGraw-Hill , New York .

Losonci , D. and Demeter , K. ( 2013 ), “ Lean production and business performance: international empirical results ”, Competitiveness Review , Vol. 23 No. 3 , pp. 218 - 233 .

Maskell , B.H. , Baggaley , B. and Grasso , L. ( 2011 ), Practical Lean Accounting: A Proven System for Measuring and Managing the Lean Enterprise , CRC Press , Boca Raton .

Meade , D.J. , Kumar , S. and White , B. ( 2010 ), “ Analysing the impact of the implementation of lean manufacturing strategies on profitability ”, Journal of the Operational Research Society , Taylor & Francis , Vol. 61 No. 5 , pp. 858 - 871 .

Nawanir , G. , Lim , K.T. and Othman , S.N. ( 2013 ), “ Impact of lean practices on operations performance and business performance: some evidence from Indonesian manufacturing companies ”, Journal of Manufacturing Technology Management , Emerald Group Publishing , Vol. 24 No. 7 , pp. 1019 - 1050 .

Nawanir , G. , Lim , K.T. and Othman , S.N. ( 2016 ), “ Lean manufacturing practices in Indonesian manufacturing firms: are there business performance effects? ”, International Journal of Lean Six Sigma , Vol. 7 No. 2 , pp. 149 - 170 .

Negrão , L.L.L. , Godinho Filho , M. and Marodin , G. ( 2017 ), “ Lean practices and their effect on performance: a literature review ”, Production Planning and Control , Taylor & Francis , Vol. 28 No. 1 , pp. 33 - 56 .

Negrão , L.L.L. , Lopes de Sousa Jabbour , A.B. , Latan , H. , Godinho Filho , M. , Chiappetta Jabbour , C.J. and Ganga , G.M.D. ( 2019 ), “ Lean manufacturing and business performance: testing the S-curve theory ”, Production Planning and Control , Taylor & Francis , Vol. 31 No. 10 , pp. 771 - 785 .

Ohno , T. ( 1988 ), Toyota Production System: Beyond Large-Scale Production , Productivity Press , Portland .

Panizzolo , R. ( 1998 ), “ Applying the lessons learned from 27 lean manufacturers: the relevance of relationships management ”, International Journal of Production Economics , Vol. 55 No. 3 , pp. 223 - 240 .

Saad , S. , Perera , T. , Achanga , P. , Shehab , E. , Roy , R. and Nelder , G. ( 2006 ), “ Critical success factors for lean implementation within SMEs ”, Journal of Manufacturing Technology Management , Emerald Group Publishing , Vol. 17 No. 4 , pp. 460 - 471 .

Sahoo , S. ( 2019 ), “ Lean manufacturing practices and performance: the role of social and technical factors ”, International Journal of Quality and Reliability Management , Emerald Publishing , Vol. 37 No. 5 , pp. 732 - 754 .

Sahoo , S. and Yadav , S. ( 2018 ), “ Lean production practices and bundles: a comparative analysis ”, International Journal of Lean Six Sigma , Emerald Publishing , Vol. 9 No. 3 , pp. 374 - 398 .

Saunders , M. , Lewis , P. and Thornhill , A. ( 2009 ), Research Methods for Business Students , Pearson education , Essex .

Shah , R. and Ward , P.T. ( 2003 ), “ Lean manufacturing: context, practice bundles, and performance ”, Journal of Operations Management , Elsevier , Vol. 21 No. 2 , pp. 129 - 149 .

Shrafat , F.D. and Ismail , M. ( 2019 ), “ Structural equation modeling of lean manufacturing practices in a developing country context ”, Journal of Manufacturing Technology Management , Emerald Publishing , Vol. 30 No. 1 , pp. 122 - 145 .

Tranfield , D. , Denyer , D. and Smart , P. ( 2003 ), “ Towards a methodology for developing evidence‐informed management knowledge by means of systematic review ”, British Journal of Management , Wiley Online Library , Vol. 14 No. 3 , pp. 207 - 222 .

Voss , C. , Tsikriktsis , N. and Frohlich , M. ( 2002 ), “ Case research in operations management ”, International Journal of Operations and Production Management , Vol. 22 No. 2 , pp. 195 - 219 .

Womack , J.P. and Jones , D.T. ( 1996 ), Lean Thinking-Banish Waste and Create Wealth in Your Corporation , Simon & Schuster , New York .

Womack , J.P. , Jones , D.T. and Roos , D. ( 1990 ), The Machine that Changed the World , Simon & Schuster , New York .

Yang , M.G.M. , Hong , P. and Modi , S.B. ( 2011 ), “ Impact of lean manufacturing and environmental management on business performance: an empirical study of manufacturing firms ”, International Journal of Production Economics , Elsevier , Vol. 129 No. 2 , pp. 251 - 261 .

Yin , R.K. ( 1994 ), Case Study Research and Applications: Design and Methods , Sage publications , Thousand Oaks .

Yusuf , Y.Y. and Adeleye , E.O. ( 2002 ), “ A comparative study of lean and agile manufacturing with a related survey of current practices in the UK ”, International Journal of Production Research , Taylor & Francis , Vol. 40 No. 17 , pp. 4545 - 4562 .

Zhu , X. and Lin , Y. ( 2017 ), “ Does lean manufacturing improve firm value? ”, Journal of Manufacturing Technology Management , Vol. 28 No. 4 , pp. 422 - 437 .

Acknowledgements

This work was supported by the Veneto Region (Italy) [FSE/DGR n. 204-26/02/2019, Project code 6813-0001-204-2019].

Corresponding author

Related articles, all feedback is valuable.

Please share your general feedback

Report an issue or find answers to frequently asked questions

Contact Customer Support

Study and implementation of lean manufacturing strategies: A literature review

• February 2022
• Materials Today Proceedings 62(1(2))
• This person is not on ResearchGate, or hasn't claimed this research yet.

• Manipal University Jaipur

Abstract and Figures

Discover the world's research

• 25+ million members
• 160+ million publication pages
• 2.3+ billion citations
• Int J Qual Reliab Manag

• MULTIMED TOOLS APPL
• Fathimunisa Hanfy

• Sunita Bansal
• Rajender Kumar

• Karim Ahmed

• Hadis Bajrić

• Faris Deraković

• Ana Filipa Silva
• Giuliana Veronese
• Ana Sofia Matos
• Elafri Najwa

• Abrar Ali Deshmukh

• Anbesh Jamwal

• Chiara Cagnetti
• Tommaso Gallo

• Alessandro Ruggieri
• Vagner Agostinho

• Recruit researchers
• Join for free
• Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

Evaluating residual stresses in metal additive manufacturing: a comprehensive review of detection methods, impact, and mitigation strategies

• Published: 14 September 2024
• Volume 17 , article number  53 , ( 2024 )

Cite this article

• Mumtaz Rizwee   ORCID: orcid.org/0000-0002-0244-4778 1 &
• Deepak Kumar   ORCID: orcid.org/0000-0002-0760-1672 1  

The metal additive manufacturing (MAM) process has most employed methods to build complex geometry and lightweight 3-dimensional (3-D) parts directly from a computerized solid model. Distortion of the printed part is a highly significant concern within the MAM process. This issue is because of the heating and cooling effect of printing process that could accumulate residual stress (RS) during part building up. The aim of the literature work is to present various methodologies for measuring RS in MAM components and to furnish a brief summary of recent developments in the domain. These details aid scholars in the discernment of suitable techniques, namely destructive, semi-destructive, or non-destructive, contingent on their particular applications and the accessibility of these methods. Moreover, it facilitates the explication of their formation mechanisms, effectiveness of process parameters, prediction, and control techniques. The effect of RS on the mechanical characteristics of printed parts is analyzed and presented. Additionally, common defects incorporated into RS are discussed. Moreover, this review article discusses about the future challenges and opportunities in the RS analysis of MAM parts.

●Different technique of residual stress measurement in additive manufacturing process.

●Influence of process parameter on residual stress.

Scanning speed, layer height, laser power, laser energy density etc.

●Impact of residual stress on mechanical properties.

●Common defect due to residual stress.

Delamination, parts cracking, separation from support, grain boundary cracking etc.

●Impact of in-process and post-process techniques in residual stress modification.

Shot peening, heat treatment, hot isotatic pressing, laser shock peening etc.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Mercelis P, Kruth JP (2006) Residual stresses in selective laser sintering and selective laser melting. Rapid Prototyp J 12(5):254–265. https://doi.org/10.1108/13552540610707013 .

Article   Google Scholar  

Brinksmeier E, Cammett JT, Konig W, Leskovar P, Peters J, Tonshoff HK (1982) Residual stresses-measurement and causes in machining processes. Ann CIRP 31(2):491–510. https://doi.org/10.1016/S0007-8506(07)60172-3 .

Rossini NS, Dassisti M, Benyounis KY, Olabi AG (2012) Methods of measuring residual stresses in components. Mater Des 35:572–588. https://doi.org/10.1016/j.matdes.2011.08.022 .

Kruth JP, Froyen L, Van Vaerenbergh J, Mercelis P, Rombouts M, Lauwers B (2004) Selective laser melting of iron-based powder. J Mater Process Technol 149(1–3):616–622. https://doi.org/10.1016/j.jmatprotec.2003.11.051 .

Kruth JP, Deckers J, Yasa E, Wauthle R (2012) Assessing and comparing influencing factors of residual stresses in selective laser melting using a novel analysis method. Proc Inst Mech Eng B J Eng Manuf 226(6):1–12. https://doi.org/10.1177/0954405412437085 .

Zyl I, Yadroitsava I, Yadroitsev I (2016) Residual stress in Ti6Al4V objects produced by direct metal laser sintering. South Afr J Ind Eng 27(4):134–141. https://hdl.handle.net/10520/EJC199638

Google Scholar  

Norton JH, Rosenthal D (1944) Stress measurement by x-ray diffraction. Proc Soc Exp Stress Anal 1(2):73–76

Norton JH, Rosenthal D (1944) Application of the x-ray method of stress measurement to problems involving residual stress in metals. Proc Soc Exp Stress Anal 1(2):81–90

Wu AS, Brown DW, Kumar M, Gallegos GF, King WE (2014) An experimental investigation into additive manufacturing-induced residual stresses in 316L stainless steel. Metall Mater Trans A 45(13):6260–6270. https://doi.org/10.1007/s11661-014-2549-x

Chen M, Xing S, Liu H, Jiang C, Zhan K, Ji V (2020) Determination of surface mechanical property and residual stress stability for shot-peened SAF2507 duplex stainless steel by in situ X-ray diffraction stress analysis. J Mater Res Technol 9(4):7644–7654. https://doi.org/10.1016/j.jmrt.2020.05.028 .

Zhang Z, Feng Y, Tan Q, Zou J, Li J, Zhou X, Wang Y (2019) Residual stress distribution in Ni-based superalloy turbine discs during fabrication evaluated by neutron/X-ray diffraction measurement and thermomechanical simulation. Mater Design 166:107603. https://doi.org/10.1016/j.matdes.2019.107603 .

Swain D, Sharma A, Selvan SK, Thomas BP, Philip J (2019) Residual stress measurement on 3-D printed blocks of Ti-6Al-4V using incremental hole drilling technique. Procedia Struct Integr 14:337–344. https://doi.org/10.1016/j.prostr.2019.05.042 .

Zhan Y, Liu C, Zhang J, Mo G, Liu C, 762 (2019) 138093. https://doi.org/10.1016/j.msea.2019.138093

Liu C, Lin C, Wang J, Wang J, Yan L, Luo Y, Yang M (2020) Residual stress distributions in thick specimens excavated from a large circular wire + arc additive manufacturing mockup. J Manuf Process 56:474–481. https://doi.org/10.1016/j.jmapro.2020.05.007 .

De Oliveira AR, de Oliveira VF, Teixeira JC, Conte D, E. G (2021) Investigation of the build orientation effect on magnetic properties and Barkhausen noise of additively manufactured maraging steel 300. 38:101827. Additive Manufacturing https://doi.org/10.1016/j.addma.2020.101827 .

Rizwee M, Kumar D, Kumar R (2024) Computational analysis of the Mechanical Compression of Additive Manufactured Lattice structures: a Numerical Study. Advances in Industrial Engineering in the industry 4.0 era. CRC, pp 147–156

Olabi AG, Hashmi MSJ (1996) Stress relief procedures for low carbon steel (1020) welded components. J Mater Process Technol 56:552–562. https://doi.org/10.1016/0924-0136(95)01869-7 .

Kandil FA, Lord JD (2001) A review of residual stress measurement methods, a guide to technique selection. NPL Report MAT(A)04. http://eprintspublications.npl.co.uk/id/eprint/1873

Milbradt KP (1951) Ring-method determination of residual stresses. Proc SESA 9(1):63–74

Kiel S (1992) Experimental determination of residual stresses with the ring-core method and an online measuring system. Exp Tech 16(5):17–24. https://doi.org/10.1111/j.1747-1567.1992.tb00701.x

Kim S-H, Kim J-B, Lee W-J (2009) Numerical prediction and neutron diffraction measurement of the residual stresses for a modified 9Cr– 1Mo steel weld. J Mater Process Technol 209(8):3905–3913. https://doi.org/10.1016/j.jmatprotec.2008.09.012 .

Paradowska A, Price JWH, Ibrahim R, Finlayson T (2005) A neutron diffraction of residual stress due to welding. J Mater Process Technol;164– 165:1099–1105. https://doi.org/10.1016/j.jmatprotec.2005.02.092 .

Ajovalasit A, Petrucci G, Zuccarello B (1996) Determination of non-uniform residual stresses using the ring-core method. J Mater Process Technol 118(2):224–228. https://doi.org/10.1115/1.2804891 .

Altpeter I, Dobmann G, Kröning M, Rabung M, Szielasko S (2009) Micro-magnetic evaluation of micro residual stresses of the IInd and IIIrd order. NDT&E Int 42:283–290. https://doi.org/10.1016/j.ndteint.2008.11.007 .

Scholtes B (2007) Residual stress analysis of components with real geometries using the incremental hole-drilling technique and a differential evaluation method. Kassel university press GmbH

Vishay measurements group (2007) http://www.vishaypg.com/ (accessed March 1, 2011)

Lee HY, Nikbin KM, Dowd PO (2005) A generic approach for a linear fracture mechanics analysis of components containing residual stress. Int J Press Vess Pip 82:797–806. https://doi.org/10.1016/j.ijpvp.2005.05.001 .

Acevedo R, Sedlak P, Kolman R, Fredel M (2020) Residual stress analysis of additive manufacturing of metallic parts using ultrasonic waves: state of the art review. J Mater Res Technol 9(4):9457–9477. https://doi.org/10.1016/j.jmrt.2020.05.092 .

Liu J, Zhu H, Xu W (2011) Analysis of residual stresses in thick aluminum friction stir welded butt joints. Mater Des 32(4):2000–2005. https://doi.org/10.1016/j.matdes.2010.11.062 .

Olabi AG, Hashmi MSJ (1995) The effect of post-weld heat treatment on mechanical properties and residual-stresses mapping in welded structural steel. J Mater Process Technol 55:117–122. https://doi.org/10.1016/0924-0136(95)01794-1 .

Shadley JR, Rybicki EF, Shealy WS (1987) Application guidelines for the parting out in a through-thickness residual stress measurement procedure. Strain 23:157–166. https://doi.org/10.1111/j.1475-1305.1987.tb00640.x .

Tebedge N, Alpsten G, Tall L (1973) Residual-stress measurement by the sectioning method. Exp Mech 13(2):88–96. https://doi.org/10.1007/BF02322389

Mazzolani FM (1995) Aluminum alloy structures. 2nd ed. E&FN Spon, An imprint of Chapman and Hal;, ISBN: 978-0419177708

Lagerqvist O, Olsson A (2001) Residual stresses in welded I-girders made of stainless steel and structural steel. In: Helsinki: Proceedings of the ninth nordic steel construction conference; pp. 737–744

Young B, Lui WM (2005) Behavior of Cold-formed high-strength stainless steel sections. J Struct Eng, ASCE;131(11):1738–45. https://doi.org/10.1061/(ASCE)0733- 9445(2005)131:11(1738)

Olabi AG, Hashmi MSJ (1998) Effects of the stress-relief conditions on a martensite stainless-steel welded component. J Mater Process Technol 77:216–225. https://doi.org/10.1016/S0924-0136(97)00420-2 .

Prime MB, Gonzales AR (2000) In: Proceedings of the sixth international conference on residual stresses. Oxford, UK: IOM Communications Ltd. pp. 617–24

Olabi AG, Casalino G, Benyounis KY, Rotondo A (2007) Minimisation of the residual stress in the heat affected zone by means of numerical methods. Mater Des 28:2295–2302. https://doi.org/10.1016/j.matdes.2006.08.005 .

Benyounis KY, Olabi AG, Abboud JH (2007) Assessment and minimization of the residual stress in dissimilar laser welding. Appl Mech Mater;7– 8:139–144. https://doi.org/10.4028/www.scientific.net/AMM.7-8.139 .

Leggatt RH, Smith DJ, Smith SD, Faure F (1996) Development and experimental validation of the deep hole method for residual stress measurement. J Strain Anal 31(3):177–186. https://doi.org/10.1243/03093247V313177 .

DeWald AT, Hill MR (2003) Improved data reduction for the deep hole method of residual stress measurement. J Strain Anal 38(1):65–78. https://doi.org/10.1243/030932403762671908 .

Flaman MT, Herring GA (1985) Comparison of four hole-producing techniques for the center-hole residual-stress measurement method. Exp Tech 9:30–32. https://doi.org/10.1111/j.1747-1567.1985.tb02036.x

Flaman MT, Herring GA (1986) Ultra-high-speed center-hole technique for difficult machining materials. Exp Tech 10:34–35. https://doi.org/10.1111/j.1747-1567.1986.tb01370.x .

Zhang B, Dembinski L, Coddet C (2013) The study of the laser parameters and environment variables effect on mechanical properties of high compact parts elaborated by selective laser melting 316L powder. Mater Sci Eng A 584:21–31. https://doi.org/10.1016/j.msea.2013.06.055 .

Venturi F, Taylor R (2023) Additive Manufacturing in the context of repeatability and reliability. J Mater Eng Perform 1–21. https://doi.org/10.1007/s11665-023-07897-3

Bartlett JL, Li X (2019) An overview of residual stresses in metal powder bed fusion. Addit Manuf 27:131–149. https://doi.org/10.1016/j.addma.2019.02.020 .

Rizwee M, Kumar D, Hussain MM (2024) Enhancing the tribological characteristics of the Biocompatible Ti-6Al-4V Alloy via Heat Treatment: an experimental analysis. Tribol Int 110052. https://doi.org/10.1016/j.triboint.2024.110052

He B, Bi C, Li X, Wang W, Yang G (2023) Residual stresses and deformations of laser additive manufactured metal parts: a review. IntJ Mater Form 16(1):7. https://doi.org/10.1007/s12289-022-01729-w

Mukherjee T, Manvatkar V, De A, DebRoy T (2017) Mitigation of thermal distortion during additive manufacturing. Scr Mater 127:79–83. https://doi.org/10.1016/j.scriptamat.2016.09.001 .

Hussein A, Hao L, Yan C, Everson R (2013) Finite element simulation of the temperature and stress fields in single layers built without support in selective laser melting. Mater Des (1980–2015). 52:638–647. https://doi.org/10.1016/j.matdes.2013.05.070 .

Shiomi M, Osakada K, Nakamura K, Yamashita T, Abe F (2004) Residual stress within metallic model made by selective laser melting process. CIRP Ann Manuf Technol 53(1):195–198. https://doi.org/10.1016/S0007-8506(07)60677-5 .

Loh L-E, Chua C-K, Yeong W-Y, Song J, Mapar M, Sing S-L et al (2015) Numerical investigation and an effective modeling on the selective laser melting (SLM) process with aluminium alloy 6061. Int J Heat Mass Transf 80:288–300. https://doi.org/10.1016/j.ijheatmasstransfer.2014.09.014 .

Lu Y, Wu S, Gan Y, Huang T, Yang C, Junjie L, Lin J (2015) Study on the microstructure, mechanical property and residual stress of SLM inconel718 alloy manufactured by differing island scanning strategy. Opt Laser Technol. https://doi.org/10.1016/j.optlastec.2015.07.009 . ;75197-206

Wu AS, Brown D, Kumar W, Gallegos M, King GF WE (2014) An experimental investigation into additive manufacturing-induced residual stresses in 316L stainless steel. Metall Mater Trans A 1–11. https://doi.org/10.1007/s11661-014-2549-x

Sun L, Ren X, He J, Zhang Z (2021) Numerical investigation of a novel pattern for reducing residual stress in metal additive manufacturing. J Mater Sci Technol 67:11–22. https://doi.org/10.1016/j.jmst.2020.05.080 .

Wang L, Jiang X, Zhu Y, Zhu X, Sun J, Yan B (2018) An approach to predict the residual stress and distortion during the selective laser melting of AlSi10Mg parts. Int J Adv Manuf Technol 97:3535e46. https://doi.org/10.1007/s00170-018-2207-3

Withers PJ, Bhadeshia HK (2001) Residual stress overview. Part 2 nature and origins. Mater Sci Technol 17:366–375. https://doi.org/10.1179/026708301101510087

Jayanath S, Achuthan A (2018) A computationally efficient finite element framework to simulate additive manufacturing processes. J Manuf Sci Eng 140:041009. https://doi.org/10.1115/1.4039093 .

Abusalma H, Eisazadeh H, Hejripour F, Bunn J, Aidun DK (2022) Parametric study of residual stress formation in Wire and Arc Additive Manufacturing. J Manuf Process 75:863–876. https://doi.org/10.1016/j.jmapro.2022.01.043 .

Promoppatum P, Yao SC (2020) Influence of scanning length and energy input on residual stress reduction in metal additive manufacturing: Numerical and experimental studies. J Manuf Process 49:247–259. https://doi.org/10.1016/j.jmapro.2019.11.020 .

Han Q, Gao J, Han C, Zhang G, Li Y (2021) Experimental investigation on improving the deposition rate of gas metal arc-based additive manufacturing by auxiliary wire feeding method. Weld World 65:35–45. https://doi.org/10.1007/s40194-020-00994-0

Li R, Xiong J, Lei Y (2019) Investigation on thermal stress evolution induced by wire and arc additive manufacturing for circular thin-walled parts. J Manuf Process 40:59–67. https://doi.org/10.1016/j.jmapro.2019.03.006 .

Jinoop AN, Paul CP, Bindra KS (2019) Laser-assisted directed energy deposition of nickel super alloys: a review. Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications , 233 (11), 2376–2400. https://doi.org/10.1177/1464420719852658

Barath Kumar MD, Manikandan M (2022) Assessment of process, parameters, residual stress mitigation, post treatments and finite element analysis simulations of wire arc additive manufacturing technique. Met Mater Int 28(1):54–111. https://doi.org/10.1007/s12540-021-01015-5

Fan D, Gao M, Li C, Huang J, Yu X (2022) Residual stress and microstructure properties by trailing cooling of argon gas of wire and arc additive manufacturing. J Manuf Process 77:32–39. https://doi.org/10.1016/j.jmapro.2022.03.007 .

Romano S, Bru¨ ckner-Foit A, Brando A, Gumpinger J, Ghidini T, Beretta S (2018) Fatigue properties of AlSi10Mg obtained by additive manufacturing: defect-based modelling and prediction of fatigue strength. Eng Fract Mech 187:165e89. https://doi.org/10.1016/j.engfracmech.2017.11.002 .

Jing S, Zhang Y, Ke S (2016) The numerical simulation for effect of vibratory stress relief on titanium alloy Ti-6Al-4V fatigue life. https://doi.org/10.1007/978-981-10-2669-0_57 . Springer Singapore

Prando D, Brenna A, Diamanti MV, Beretta S, Bolzoni F, Ormellese M, Pedeferri M (2017) Corrosion of titanium: part 1: aggressive environments and main forms of degradation. J Appl Biomater Funct Mater 15(4):e291–e302. https://doi.org/10.5301/jabfm.5000387

Zhang J, Song B, Cai C, Zhang L, Shi Y (2022) Tailorable microstructure and mechanical properties of selective laser melted TiB/Ti–6Al–4V composite by heat treatment. Adv Powder Mater 1(2):100010. https://doi.org/10.1016/j.apmate.2021.10.001 .

Shi ZF, Guo HZ, Han JY, Yao ZK (2013) Microstructure and mechanical properties of TC21 titanium alloy after heat treatment. Trans Nonferrous Met Soc China 23(10):2882–2889. https://doi.org/10.1016/S1003-6326(13)62810-1 .

Sui S, Chew Y, Hao Z, Weng F, Tan C, Du Z, Bi G (2022) Effect of cyclic heat treatment on microstructure and mechanical properties of laser aided additive manufacturing Ti–6Al–2Sn–4Zr–2Mo alloy. Adv Powder Mater 1(1):100002. https://doi.org/10.1016/j.apmate.2021.09.002 .

Wang C, Jiang C, Fei C, Zhao Y, Zhu K, Chai Z (2016) Effect of shot peening on the residual stresses and microstructure of tungsten cemented carbide. Mater Des 95:159e64. https://doi.org/10.1016/j.matdes.2016.01.101

Paul R, Anand S, Gerner F (2014) Effect of thermal deformation on part errors in metal powder based additive manufacturing processes. J Manuf Sci Eng 136:31009. https://doi.org/10.1115/1.4026524 .

Dunbar AJ, Denlinger ER, Heigel J, Michaleris P, Guerrier P, Martukanitz R et al (2016) Development of experimental method for in situ distortion and temperature measurements during the laser powder bed fusion additive manufacturing process. Additive Manuf 12:25–30. https://doi.org/10.1016/j.addma.2016.04.007 .

Lai YB, Liu WJ, Zhao JB, Zhao YH, Wang FY, Han WC (2013) Experimental study on residual stress in titanium alloy laser additive manufacturing. Appl Mech Mater 431:20e6. https://doi.org/10.4028/www.scientific.net/AMM.431.20

Yadroitsev I, Yadroitsava I (2015) Evaluation of residual stress in stainless steel 316L and Ti6Al4V samples produced by selective laser melting. Virtual Phys Prototyp 10:67e76. https://doi.org/10.1080/17452759.2015.1026045 .

Parry L, Ashcroft IA, Wildman RD (2016) Understanding the effect of laser scan strategy on residual stress in selective laser melting through thermo-mechanical simulation. Additive Manuf 12:1–15. https://doi.org/10.1016/j.addma.2016.05.014 .

LN C. (2017) An experimental investigation of residual stress development during selective laser melting of Ti-6Al-4V. http://rave.ohiolink.edu/etdc/view?acc_num=wright1515112797193544

Chen Q, Liang X, Hayduke D, Liu J, Cheng L, Oskin J et al (2019) An inherent strain based multiscale modeling framework for simulating part-scale residual deformation for direct metal laser sintering. https://doi.org/10.1016/j.addma.2019.05.021 . Additive Manufacturing; 28:406 – 18

DebRoy, T., Wei, H. L., Zuback, J. S., Mukherjee, T., Elmer, J. W., Milewski, J. O.,… Zhang, W. (2018). Additive manufacturing of metallic components–process, structure and properties. Progress in Materials Science. 2018; 92, 112–224. https://doi.org/10.1016/j.pmatsci.2017.10.001

Montevecchi F, Venturini G, Grossi N et al (2017) Finite element mesh coarsening for effective distortion prediction in wire arc additive manufacturing. Addit Manuf 18:145–155. https://doi.org/10.1016/j.addma.2017.10.010 .

Xie D, Lv F, Zhao J et al (2021) Towards a comprehensive understanding of distortion in additive manufacturing based on assumption of constraining force. Virtual Phys Prototyp 16:85–97. https://doi.org/10.1080/17452759.2021.1881873

Prabhakar P, Sames W, Dehoff R et al (2015) Computational modeling of residual stress formation during the electron beam melting process for Inconel 718. Addit Manuf 7:83–91. https://doi.org/10.1016/j.addma.2015.03.003

Zhang Y, Zhang J (2017) Finite element simulation and experimental validation of dis- tortion and cracking failure phenomena in direct metal laser sintering fabricated component. Addit Manuf 16:49–57. https://doi.org/10.1016/j.addma.2017.05.002

Wen Y, Zhang B, Liu S et al (2020) A novel experimental method for in situ strain measurement during selective laser melting. Virtual Phys Prototyp 15(s1):83–95. https://doi.org/10.1080/17452759.2020.1842137 .

Wu A, Brown S, Donald W et al (2014) An experimental investigation into additive man- ufacturing-induced residual stresses in 316L stainless steel. Metall Mater Trans A 45(13):6260–6270. https://doi.org/10.1007/s11661-014-2549-x

Xiao Z, Chen C, Zhu H, Hu Z, Nagarajan B, Guo L et al (2020) Study of residual stress in selective laser melting of Ti6Al4V. Mater Des 193:108846. https://doi.org/10.1016/j.matdes.2020.108846 .

Marimuthu S, Clark D, Allen J et al (2012) Finite element modelling of substrate thermal distortion in direct laser additive manufacture of an aero-engine component. Proc Inst Mech Eng Part C J Mech Eng Sci 227(9):1987–1999. https://doi.org/10.1177/0954406212470363

Ghnatios C, Rai K, Hascoet N et al (2021) Reduced order modeling of selective laser melting: from calibration to parametric part distortion. Int J Mater Form 14:973–986. https://doi.org/10.1007/s12289-021-01613-z

Dunbar AJ, Denlinger ER, Gouge MF et al (2017) Comparisons of laser powder bed fusion additive manufacturing builds through experimental in situ distortion and temperature measurements. Addit Manuf 15:57–65. https://doi.org/10.1016/j.addma.2017.03.003 .

Denlinger ER, Gouge M, Irwin J et al (2017) Thermomechanical model development and in situ experimental validation of the laser powder-bed fusion process. Addit Manuf 16:73–80. https://doi.org/10.1016/j.addma.2017.05.001 .

Denlinger ER, Heigel JC, Michaleris P et al (2015) Effect of inter-layer dwell time on distortion and residual stress in additive manufacturing of titanium and nickel alloys. J Mater Process Technol 215:123–131. https://doi.org/10.1016/j.jmatprotec.2014.07.030 .

Denlinger ER, Heigel JC, Michaleris P (2015) Residual stress and distortion modeling of electron beam direct manufacturing Ti-6Al 4V. Proc Inst Mech Eng Part B J Eng Manuf 229(10):1803–1813. https://doi.org/10.1177/0954405414539494 .

Biegler M, Graf B, Rethmeier M (2018) In-situ distortions in LMD additive manufacturing walls can be measured with digital image correlation and predicted using numerical simulations. Addit Manuf 20:101–110. https://doi.org/10.1016/j.addma.2017.12.007

ANSYS Inc (2023) ANSYS Additive user guidance 2023R2

Inc ANSYS (2021) Ansys additive suite. Technical Report, Canonsburg, Pennsylvania, United States

Yang Y, Allen M, London T, Oancea V (2019) Residual strain predictions for a powder bed fusion inconel 625 single cantilever part. Integrat Mater Manuf Innovat 8(3):294–304. https://doi.org/10.1007/s40192-019-00144-5

Minetola P, Stiuso V, Calignano F, Galati M, Khandpur MS, Fontana L (2021) Experimental validation of laser powder bed fusion simulation. IOP Conf Ser : Mater Sci Eng 1091(1):012048. https://doi.org/10.1088/1757-899x/

Alvarez P, Ecenarro J, Setien I, Sebastian MS, Echeverria A, L (2016) Eciolaza, computationally efficient distortion prediction in powder bed fusion additive manufacturing. Int J Eng Res Sci 2(10):39–46

Gusarov AV, Pavlov M, Smurov I (2011) Residual stresses at laser surface remelting and additive manufacturing. Phys Proc 12:248–254. https://doi.org/10.1016/j.phpro.2011.03.032 .

Robinson J, Ashton I, Fox P, Jones E, Sutcliffe C (2018) Determination of the effect of scan strategy on residual stress in laser powder bed fusion additive manufacturing. Addit Manuf 23:13–24. https://doi.org/10.1016/j.addma.2018.07.001 .

Yadroitsava I, Grewar S, Hattingh D, Yadroitsev I (2015) Residual stress in SLM Ti6Al4V alloy specimens. Mater Sci Forum 828–829:305–310. https://doi.org/10.4028/www.scientific.net/MSF.828-829.305

Amato K, Hernandez J, Murr L, Martinez E, Gaytan S, Shindo P, Collins S (2012) Comparison of microstructures and properties for a Ni-base superalloy (alloy 625) fabricated by electron beam melting. J Mater Sci Res 1(2):3. https://doi.org/10.5539/jmsr.v1n2p3 .

Vrancken B, Thijs L, Kruth J, Van Humbeeck J (2012) Heat treatment of Ti6Al4V produced by selective laser melting: microstructure and mechanical properties. J Alloys Compd 541(0):177–185. https://doi.org/10.1016/j.jallcom.2012.07.022 .

Li C, Guo YB, Zhao JB (2017) Interfacial phenomena and characteristics between the deposited material and substrate in selective laser melting inconel 625. J Mater Process Technol. https://doi.org/10.1016/j.jmatprotec.2016.12.033 . ;243269-281

Waqar S, Guo K, Sun J (2022) Evolution of residual stress behavior in selective laser melting (SLM) of 316L stainless steel through preheating and in-situ re-scanning techniques. Opt Laser Technol 149:107806. https://doi.org/10.1016/j.optlastec.2021.107806 .

Lu X, Lin X, Chiumenti M, Cervera M, Hu Y, Ji X, Huang W (2019) Residual stress and distortion of rectangular and S-shaped Ti-6Al-4V parts by Directed Energy Deposition: Modelling and experimental calibration. Additive Manuf 26:166–179. https://doi.org/10.1016/j.addma.2019.02.001

Kudryavtsev Y, Kleiman J (2011) Residual stress management: measurement, fatigue analysis and beneficial redistribution. In: Conference Proceedings for the Society for Experimental Mechanics Series. pp. 119–29. https://doi.org/10.1007/978-1-4614-0225-1

Guz’ AN, Makhort FG (2000) The physical fundamentals of the ultrasonic non-destructive stress analysis of solids. Int Appl Mech, Springer;36(9):1119–49. https://doi.org/10.1023/A:1009442132064

Newell DJ, O’Hara RP, Cobb GR, Palazotto AN, Kirka MM, Burggraf LW et al (2019) Mitigation of scan strategy effects and material anisotropy through supersolvus annealing in LPBF IN718. Mater Sci Eng A 764:138230. https://doi.org/10.1016/j.msea.2019.138230

Keller S, Chupakhin S, Staron P, Maawad E, Kashaev N, Klusemann B (2018) Experimental and numerical investigation of residual stresses in laser shock peened AA2198. J Mater Process Technol 255:294–307. https://doi.org/10.1016/j.jmatprotec.2017.11.023 .

Sun R, Li L, Zhu Y, Guo W, Peng P, Cong B, Liu L (2018) Microstructure,residual stress and tensile properties control of wire-arc additive manufactured 2319 aluminum alloy with laser shock peening. J Alloys Compd 747:255–265. https://doi.org/10.1016/j.jallcom.2018.02.353

Varin S, Agarwal M, Chugh A, Manikandan M, Prabhakaran S, Kalainathan S, Arivazhagan N (2019) Effect of laser shock peening on commercially pure titanium-1 weldment fabricated by gas tungsten arc welding technique. Trans Indian Inst Met 72:1569–1573. https://doi.org/10.1007/s12666-019-01704-1

Ye C, Zhang C, Zhao J, Dong Y (2021) Effects of post-processing on the surface finish, porosity, residual stresses, and fatigue performance of additive manufactured metals: a review. J Mater Eng Perform 30:6407–6425. https://doi.org/10.1007/s11665-021-06021-7

Shiva S, Palani IA, Paul CP, Bindra KS (2021) Laser shock peening of Ni-Ti bulk structures developed by laser additive manufacturing. J Mater Eng Perform 30(8):5603–5613. https://doi.org/10.1007/s11665-021-05799-w

Ali H, Ma L, Ghadbeigi H, Mumtaz K (2017) In-situ residual stress reduction, martensitic decomposition and mechanical properties enhancement through high temperature powder bed pre-heating of selective laser melted Ti6Al4V. https://doi.org/10.1016/j.msea.2017.04.033 . Mat Sci Eng-A;695211-220

Li C, Liu ZY, Fang XY, Guo YB (2018) Residual stress in metal additive manufacturing. In: 4th CIRP Conference on Surface Integrity. pp. 348–53. https://doi.org/10.1016/j.procir.2018.05.039

Buchbinder D, Meiners W, Pirch N, Wissenbach K, Schrage J (2014) Investigation on reducing distortion by pre-heating during manufacture of aluminum components using selective laser melting. J Laser Appl 26(1):012004. https://doi.org/10.2351/1.4828755 .

Ali H, Ghadbeigi H, Hosseinzadeh F, Oliveira J, Mumtaz K (2019) Effect of pre-emptive in situ parameter modification on residual stress distributions within selective laser-melted Ti6Al4V components. Int J Adv Manuf Technol 103:4467–4479. https://doi.org/10.1007/s00170-019-03860-6

Liu H, Li Z, Li W, Zhang W, Wang T, Liu W (2022) Influence of Arc pre-heating on stress and strain of Additive Manufactured Components. J Mater Eng Perform 1–14. https://doi.org/10.1007/s11665-022-07565-y

Martina F, Roy MJ, Szost BA, Terzi S, Colegrove PA, Williams SW et al (2016) Residual stress of as-deposited and rolled wire + arc additive manufacturing Ti-6Al-4V components. Mater Sci Technol 32(14). https://doi.org/10.1080/02670836.2016.1142704 .

Nemani AV, Ghaffari M, Nasiri A (2020) Comparison of microstructural characteristics and mechanical properties of shipbuilding steel plates fabricated by conventional rolling versus wire arc additive manufacturing. Additive Manuf 32:101086. https://doi.org/10.1016/j.addma.2020.101086 .

Hönnige JR, Colegrove PA, Ganguly S, Eimer E, Kabra S, Williams S (2018) Control of residual stress and distortion in aluminium wire + arc additive manufacture with rolling. Additive Manuf 22:775–783. https://doi.org/10.1016/j.addma.2018.06.015 .

Colegrove PA, Coules HE, Fairman J, Martina F, Kashoob T, Mamash H, Cozzolino LD (2013) Microstructure and residual stress improvement in wire and arc additively manufactured parts through high-pressure rolling. J Mater Process Technol 213(10):1782–1791. https://doi.org/10.1016/j.jmatprotec.2013.04.012

Abbaszadeh, M., Hönnige, J. R., Martina, F., Neto, L., Kashaev, N., Colegrove, P.,… Klusemann, B. (2019) Numerical investigation of the effect of rolling on the localized stress and strain induction for wire + arc additive manufactured structures. Journal of Materials Engineering and Performance; 28 , 4931–4942. https://doi.org/10.1007/s11665-019-04249-y

Lu Y, Wu S, Gan Y, Huang T, Yang C, Junjie L et al (2015) Study on the microstructure, mechanical property and residual stress of SLM inconel-718 alloy manufactured by differing island scanning strategy. Opt Laser Technol 75:197–206. https://doi.org/10.1016/j.optlastec.2015.07.009 .

Aba-Perea PE, Pirling T, Preuss M (2016) In-situ residual stress analysis during annealing treatments using neutron diffraction in combination with a novel furnace design. Mater Des 110(15):925–931. https://doi.org/10.1016/j.matdes.2016.07.078 .

Wang J, Lin X, Wang M, Li J, Wang C, Huang W (2020) Effects of subtransus heat treatments on microstructure features and mechanical properties of wire and arc additive manufactured Ti–6Al–4V alloy. Mater Sci Engineering: A 776:139020. https://doi.org/10.1016/j.msea.2020.139020 .

Shen, C., Pan, Z., Ding, D., Yuan, L., Nie, N., Wang, Y., … Li, H. (2018) The influence of post-production heat treatment on the multi-directional properties of nickel-aluminum bronze alloy fabricated using wire-arc additive manufacturing process. Additive Manufacturing;23, 411–421. https://doi.org/10.1016/j.addma.2018.08.008

Wang X, Chou K (2019) The effects of stress relieving heat treatment on the microstructure and residual stress of Inconel 718 fabricated by laser metal powder bed fusion additive manufacturing process. J Manuf Process 48:154–163. https://doi.org/10.1016/j.jmapro.2019.10.027 .

Ge J, Pillay S, Ning H (2023) Post-process treatments for additive-manufactured metallic structures: a Comprehensive Review. J Mater Eng Perform 1–50. https://doi.org/10.1007/s11665-023-08051-9

Matsumoto Y, Hashimoto F, Lahoti G (1999) Surface integrity generated by precision hard turning. CIRP Ann Manuf Technol 48(1):59–62. https://doi.org/10.1016/S0007-8506(07)63131-X .

Guo YB, Li W, Jawahir IS (2009) Surface integrity characterization and prediction in machining of hardened and difficult-to-machine alloys: a state-of-art research review and analysis. Mach Sci Technol 13:437–470. https://doi.org/10.1080/10910340903454922 .

Tang ZT, Liu ZQ, Wan Y, Ai X (2008) Study on residual stresses in milling aluminum alloy 7050-T7451. Advanced design and manufacture to gain a competitive edge. Springer, pp 169–178. https://doi.org/10.1007/978-1-84800-241-8_18

Oyelola O, Crawforth P, Saoubi R, Clare AT (2017) On the machinability of directed energy deposited Ti6Al4V. https://doi.org/10.1016/j.addma.2017.11.005 . Addit Manuf;245

Yamaguchi H, Fergani O, Wu PY (2017) Modification using magnetic field-assisted finishing of the surface roughness and residual stress of additively manufactured components. https://doi.org/10.1016/j.cirp.2017.04.084 . CIRP Ann Manuf Technol;1642

Portella Q, Chemkhi M, Retraint D (2018) Residual stresses in analysis in AISI 316L processed by selective laser melting (SLM) treated by mechanical post-processing treatments. Mater Res Proc 6:271–276 ECRS-10

Galitelli D, Retraint D, Rouhaud E (2014) Comparison between conventional shot peening (SP) and surface mechanical attrition treatment (SMAT) on a titanium alloy. Adv Mater Res 996:964–968. https://doi.org/10.4028/www.scientific.net/AMR.996.964

Gao H, Dutta RK, Huizenga RM, Amirthalingam M, Hermans MJM et al (2014) Stress relaxation due to ultrasonic impact treatment on multi-pass welds. Sci Technol Weld Join 19(6). https://doi.org/10.1179/1362171814Y.0000000219 .

Download references

Acknowledgements

The authors thank to Mr. Mohammad Akhtar (Mechanical Engineering Department), Al-Kabir Polytechnic Jamshedpur and Mr. Swaroop Kumar Mandal, NIT Jamshedpur, for their assistance and support, which enhanced the quality of the manuscript.

Author information

Authors and affiliations.

Advanced Composite and Smart Material Laboratory, Department of Mechanical Engineering, National Institute of Technology Jamshedpur, Jharkhand, 831014, India

Mumtaz Rizwee & Deepak Kumar

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Deepak Kumar .

Ethics declarations

Competing interest, additional information, publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Rizwee, M., Kumar, D. Evaluating residual stresses in metal additive manufacturing: a comprehensive review of detection methods, impact, and mitigation strategies. Int J Mater Form 17 , 53 (2024). https://doi.org/10.1007/s12289-024-01855-7

Download citation

Received : 02 March 2024

Accepted : 03 September 2024

Published : 14 September 2024

DOI : https://doi.org/10.1007/s12289-024-01855-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Mechanical properties
• RS control method
• Find a journal
• Publish with us
• Track your research