Improvement of Assembly Line Efficiency by Using Lean Manufacturing Tools and Line Balancing Techniques

• Autorzy: Mortada Anass , Soulhi Aziz

Identyfikatory

DOI

10.12913/22998624/169257

• Języki publikacji: EN

Abstrakty

EN

This paper presents a solid methodology for improving the efficiency and productivity of assembly lines using Lean Manufacturing tools, in particular the Define, Measure, Analyze, Improve, and Control approach (DMAIC) and line balancing techniques, followed by a concrete application in a case study of a wiring industry assembly line. The first phase of the approach ensured a clear definition of the problem using the who, what, where, when, why, and how tool (5W1H) and a description of the manufacturing process. The measurement phase allowed the calculation of the Takt time (TT) and the timing of the cycle times of the 17 stations of the line with the use of data collected on the standardized work combination table (SWCT) documents. This facilitated the analysis phase by first establishing a Yamazumi chart showing the distribution of the load between the line's stations and allowing the identification of bottleneck stations, and then analyzing the situation through the 5-Why tools and the Ishikawa diagram. Thanks to the innovation phase and the ideal balancing conditions developed in this paper, it was possible to balance the line's stations using an action plan whose effectiveness was monitored during the control phase, improving efficiency from 78% to 95% with a saving in manpower by reducing the number of operators from 17 to 14.

Słowa kluczowe

EN

efficiency; line balancing; lean manufacturing; DMAIC; standardized work; Yamazumi chart

• Wydawca: Lublin University of Technology ; Polish Society of Ecological Engineering (PTIE), Branch of PTIE in Lublin
• Czasopismo: Advances in Science and Technology. Research Journal
• Rocznik: 2023
• Tom: Vol. 17, no 4
• Strony: 89--109
• Opis fizyczny: Bibliogr. 26 poz., fig.

Twórcy

autor

Mortada Anass

• Mohammedia School of Engineers, University Mohammed V-Agdal, Av. Ibn Sina, Rabat, Morocco

• https://orcid.org/0000-0001-8745-8652

autor

Soulhi Aziz

• Higher National School of Mines, Rabat, Morocco

• https://orcid.org/0000-0003-1904-513X

Bibliografia

• 1. Ariyanti S., Rifa’i Azhar M., Yamin Lubis M.S. Assembly Line Balancing with The Yamazumi Method. IOP Conf. Ser. Mater. Sci. Eng., 2020; 1007(1): 012078. DOI: 10.1088/1757-899X/1007/1/012078.
• 2. Haekal J. Improving Work Efficiency and Productivity with Line Balancing and TPS Approach and Promodel Simulation on Brush Sub Assy Line in Automotive Companies. Int. J. Sci. Adv. 2021; 2(3). DOI: 10.51542/ijscia.v2i3.24.
• 3. Shukla P., Malviya S., Jain S. Review of Some Recent Findings for Productivity Improvement Using Line Balancing Heuristic Algorithms. 2018; 5(6): 9.
• 4. Adnan A.N., Arbaai N.A., Ismail A. Improvement of overall efficiency of production line by using line balancing. 2016; 11(12), 8.
• 5. Rubinovitz J., Levitin G. Genetic algorithm for assembly line balancing. Int. J. Prod. Econ., 1995; 41(1– 3): 343–354. DOI: 10.1016/0925-5273(95)00059-3.
• 6. Hasta A., Harwati. Line Balancing with Reduced Number of Operator: A Productivity Improvement. IOP Conf. Ser. Mater. Sci. Eng. 2019; 528(1): 012060. DOI: 10.1088/1757-899X/528/1/012060
• 7. Nithish Kumar R., Mohan R., Gobinath N. Improvement in production line efficiency of hemming unit using line balancing techniques. Mater. Today Proc., 2021; 46: 1459–1463. DOI: 10.1016/j. matpr.2021.03.020.
• 8. Kłosowski G., Gola A., Świć A. Application of Fuzzy Logic Controller for Machine Load Balancing in Discrete Manufacturing System. Intelligent Data Engineering and Automated Learning – IDE- AL 2015, K. Jackowski, R. Burduk, K. Walkowiak, M. Wozniak, and H. Yin, Eds., in Lecture Notes in Computer Science. Cham: Springer International Publishing. 2015; 9375: 256–263. DOI: 10.1007/978-3-319-24834-9_31.
• 9. Operations and Business Analytics, University Science Malaysia, Penang, Malaysia. et al. Improvement of Operational Performance through Value Stream Mapping and Yamazumi Chart: A case of Bangladeshi RMG Industry. Int. J. Recent Technol. Eng. IJRTE. 2019; 8(4): 11977–11986. DOI: 10.35940/ijrte.D9926.118419.
• 10. Lam N.T., Toi L.M., Tuyen V.T.T., Hien D.N. Lean Line Balancing for an Electronics Assembly Line. Procedia CIRP. 2016; 40: 437–442. DOI: 10.1016/j. procir.2016.01.089.
• 11. Dzulkarnain M.F.A. Productivity Improvement in Automotive Component Company using Line Balancing, 2017.
• 12. Rathod B., Shinde P., Raut D., Waghmare G. Optimization of Cycle Time by Lean Manufacturing Techniques-Line Balancing Approach. 2016; 4.
• 13. Pieńkowski M. Waste measurement techniques for lean companies. 2014; 5(1): 17.
• 14. Mostafa S., Dumrak J., Soltan H. A framework for lean manufacturing implementation,” Prod. Manuf. Res. 2013; 1(1): 44–64. DOI: 10.1080/21693277.2013.862159.
• 15. Rewers P., Trojanowska J., Chabowski P. Tools and methods of Lean Manufacturing - a literature review. 2016; 7.
• 16. AlManei M., Salonitis K., Xu Y. Lean Implementation Frameworks: The Challenges for SMEs. Procedia CIRP. 2017; 63: 750–755. DOI: 10.1016/j. procir.2017.03.170.
• 17. Chaudhari T., Raut N. Waste Elimination by Lean Manufacturing. 2017; 4: 5.
• 18. De Oliveira R.I., Sousa S.O., De Campos F.C. Lean manufacturing implementation: bibliometric analysis 2007–2018. Int. J. Adv. Manuf. Technol., 2019; 101: 1–4: 979–988. DOI: 10.1007/ s00170-018-2965-y.
• 19. Montgomery D.C., Woodall W.H. An Overview of Six Sigma. Int. Stat. Rev., 2008; 76(3): 329–346. DOI: 10.1111/j.1751-5823.2008.00061.x.
• 20. Krishnan B.R., Prasath K.A. Six sigma concept and dmaic implementation. 2013; 5.
• 21. Knop K., Mielczarek K. Using 5W-1H and 4M Methods to Analyse and Solve the Problem with the Visual Inspection Process - case study. MATEC Web Conf. 2018; 183: 03006. DOI: 10.1051/ matecconf/201818303006.
• 22. Mariz R.N., Picchi F.A., Granja A.D. A review of the standardized work application in construction. Th Annu. Conf. Int. Group Lean Constr. 2012; 11.
• 23. Pereira A., et al. Reconfigurable Standardized Work in a Lean Company – A Case Study. Procedia CIRP. 2016; 52: 239–244. DOI: 10.1016/j. procir.2016.07.019
• 24. Hyie D.K.M., Bahsan R., Salleh F.M., Mahat M.M. Editorial executive, 38
• 25. Mandahawi N., Araidah O.A., Boran A., Khasawneh M. Application of Lean Six Sigma tools to minimise length of stay for ophthalmology day case surgery. Int. J. Six Sigma Compet. Advant. 2011; 6(3): 156. DOI: 10.1504/IJSSCA.2011.039716.
• 26. Nagyová A., Pačaiová H., Gobanová A., Turisová R. An Empirical Study of Root-Cause Analysis in Automotive Supplier Organisation. Qual. Innov. Prosper. 2019; 23(2), 34. DOI: 10.12776/qip. v23i2.1243.
• 27. Brancuşi C. Study to determine a new model of the ishikawa diagram for quality improvement. 2017; 1: 6.
• 28. Doshi J.A., Kamdar J.D., Jani S.Y., Chaudhary S.J. Root Cause Analysis Using Ishikawa Diagram For Reducing Radiator Rejection. 2012; 2(6): 6.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).