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Diagnostics of production processes using selected lean manufacturing tools

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Modern manufacturing companies should adapt to the needs and requirements of customers, and the products manufactured should meet the needs of customers. Meeting these requirements is the key to maintaining an appropriate position on the market. In production systems, an important element of the efficient functioning of the production process is production logistics, therefore the aim of this publication was to diagnose logistics and production processes and propose improvements in this area. For this purpose, selected tools of the Lean Manufacturing concept were used: the SMED (Single Minute Exchange of Die) method and Goldratt's Theory of Constraints. SWOT analysis was used to determine the strengths and weaknesses of the company.
Czasopismo
Rocznik
Strony
art. no. 2024305
Opis fizyczny
Bibliogr. 40 poz., rys., tab.
Twórcy
  • Doctoral School, Military University of Technology, Kaliskiego 2B Street, 00-908 Warsaw, Poland
  • Faculty of Security, Logistics and Management, Military University of Technology, Kaliskiego 2B Street, 00-908 Warsaw, Poland
autor
  • Faculty of Security, Logistics and Management, Military University of Technology, Kaliskiego 2B Street, 00-908 Warsaw, Poland
Bibliografia
  • 1. Abu F, Saman MZM, Garza-Reyes JA, Gholami H, Zakuan N. Challenges in the implementation of lean manufacturing in the wood and furniture industry. Journal of Manufacturing Technology Management 2021; 33(1): 103-23. https://doi.org/10.1108/JMTM-01-2021-0029.
  • 2. Alefari M, Almanei M, Salonitis K. Lean manufacturing, leadership and employees: the case of UAE SME manufacturing companies. Production & Manufacturing Research 2020; 8(1): 222-43. https://doi.org/10.1080/21693277.2020.1781704.
  • 3. Benzaghta M, Elwalda A, Mousa M, Erkan I, Rahman M. SWOT analysis applications: An integrative literature review. Journal of Global Business Insights 2021; 6(1): 55-73. https://doi.org/10.5038/2640-6489.6.1.1148.
  • 4. Borucka A, Kozłowski E, Antosz K, Parczewski R. A new approach to production process capability assessment for non-normal data. Applied Sciences 2023; 13(11): 6721.
  • 5. Bragg S. Throughput accounting: a guide to constraint management. John Wiley & Sons; 2012.
  • 6. Moreira AC, Pais GCS. single minute exchange of die. A case study implementation. Journal of Technology Management & Innovation 2011; 6(1): 129-46. https://doi.org/10.4067/S0718-27242011000100011.
  • 7. Silva IB, Filho M. Single-minute exchange of die (SMED): a state-of-the-art literature review. The International Journal of Advanced Manufacturing Technology 2019; 102. https://doi.org/10.1007/s00170-019-03484-w.
  • 8. Dave P. The history of lean manufacturing by the view of Toyota-Ford. International Journal of Scientific and Engineering Research 2020; 11: 1598-602.
  • 9. Deshmukh M, Gangele A, Gope D, Dewangan S. Study and implementation of lean manufacturing strategies: A literature review. Materials Today: Proceedings 2022; 62. https://doi.org/10.1016/j.matpr.2022.02.155.
  • 10. Dieste M, Panizzolo R, Garza-Reyes JA. A systematic literature review regarding the influence of lean manufacturing on firms’ financial performance. Journal of Manufacturing Technology Management 2021; 32(9): 101-21. https://doi.org/10.1108/JMTM-08-2020-0304.
  • 11. García-Alcaraz J, Hernández F, Olguín Tiznado J, Realyvásquez A, Jiménez E, Javierre C. Effect of quality lean manufacturing tools on commercial benefits gained by Mexican Maquiladoras. Mathematics 2021; 9: 971. https://doi.org/10.3390/math9090971.
  • 12. Ghicajanu M. Application of SWOT technique in business management. Annals of the University of Petroşani. Economics 2021; 21(1): 161-168.
  • 13. Goldratt EM, Cox J. The goal: a process of ongoing improvement. 3rd ed. Routledge; 2016.
  • 14. Goldratt EM. Theory of constraints. Croton-onHudson: North River; 1990.
  • 15. Grzelak M, Borucka A, Guzanek P. Application of Linear Regression for Evaluation of Production Processes Effectiveness. Innovations in Industrial Engineering 2022; 36-47. https://doi.org/10.1007/978-3-030-78170-5_4.
  • 16. Gupta M, Digalwar A, Gupta A, Goyal A. Integrating Theory of Constraints, Lean and Six Sigma: a framework development and its application. Production Planning & Control 2022; 35: 1-24. https://doi.org/10.1080/09537287.2022.2071351.
  • 17. Gupta S, Jain SK. A literature review of lean manufacturing. International Journal of Management Science and Engineering Management 2013; 8(4): 241-9. https://doi.org/10.1080/17509653.2013.825074.
  • 18. Hartini S, Ciptomulyono U, Anityasari M, Sriyanto. Manufacturing sustainability assessment using a lean manufacturing tool: A case study in the Indonesian wooden furniture industry. International Journal of Lean Six Sigma 2020; ahead-of-print. https://doi.org/10.1108/IJLSS-12-2017-0150.
  • 19. Hernandez-Matias J, Ocampo J, Hidalgo A, Vizan A. Lean manufacturing and operational performance: Interrelationships between human-related lean practices. Journal of Manufacturing Technology Management 2020; 31: 217-35. https://doi.org/10.1108/JMTM-04-2019-0140.
  • 20. Internal materials of the „Silikaty-Białystok” company.
  • 21. Islami X. Lean manufacturing and firms’ financial performance: the role of strategic supplier partnership and information sharing. Benchmarking: An International Journal 2022; 30. https://doi.org/10.1108/BIJ-02-2022-0084.
  • 22. Jimenez G, Santos G, Sá J, Ricardo S, Pulido J, Pizarro A, et al. Improvement of productivity and quality in the value chain through lean manufacturing - a case study. Procedia Manufacturing 2019; 41: 882-9. https://doi.org/10.1016/j.promfg.2019.10.011.
  • 23. Khalfallah M, Lakhal L. The impact of lean manufacturing practices on operational and financial performance: the mediating role of agile manufacturing. International Journal of Quality & Reliability Management 2020; ahead-of-print. https://doi.org/10.1108/IJQRM-07-2019-0244.
  • 24. Kumar N, Hasan S, Srivastava K, Akhtar R, Yadav R, Choubey V. Lean manufacturing techniques and its implementation: A review. Materials Today: Proceedings 2022; 64. https://doi.org/10.1016/j.matpr.2022.03.481.
  • 25. Liang Z, Zhong P, Zhang C, Yang W, Xiong W, Yang S, et al. A genetic algorithm-based approach for flexible job shop rescheduling problem with machine failure interference. Eksploatacja i Niezawodność - Maintenance and Reliability 2023; 25(4). https://doi.org/10.17531/ein/171784.
  • 26. Liao MH, Wang CT. Using Enterprise Architecture to Integrate Lean Manufacturing, Digitalization, and Sustainability: A Lean Enterprise Case Study in the Chemical Industry. Sustainability 2021; 13(9): 4851. https://doi.org/10.3390/su13094851.
  • 27. Mabin VJ, Balderstone SJ. The world of the theory of constraints: A Review of the International Literature [Internet]. 1st ed. 2020. https://doi.org/10.4324/9780429273056.
  • 28. Marinelli M, Deshmukh A, Janardhanan MN, Nielsen I. Lean manufacturing and Industry 4.0 combinative application: Practices and perceived benefits. IFACPapersOnLine 2021; 54: 288-93. https://doi.org/10.1016/j.ifacol.2021.08.034.
  • 29. Maware C, Okwu M, Adetunji O. A systematic literature review of lean manufacturing implementation in manufacturing-based sectors of the developing and developed countries. International Journal of Lean Six Sigma 2021; ahead-of-print. https://doi.org/10.1108/IJLSS-12-2020-0223.
  • 30. Pacheco DA de J, Antunes Junior JAV, de Matos CA. The constraints of theory: What is the impact of the Theory of Constraints on Operations Strategy? International Journal of Production Economics 2021; 235(C).
  • 31. Palange A, Dhatrak P. Lean manufacturing a vital tool to enhance productivity in manufacturing. Materials Today: Proceedings 2021; 46. https://doi.org/10.1016/j.matpr.2020.12.193.
  • 32. Racewicz S, Kazimierczuk P, Kolator B, Olszewski A. Use of 3 kW BLDC motor for light two-wheeled electric vehicle construction. IOP Conference Series: Materials Science and Engineering 2018; 421: 042067. https://doi.org/10.1088/1757-899X/421/4/042067.
  • 33. Ramakrishnan V, Jayaprakash J, Elanchezhian C, Vijaya Ramnath B. Implementation of lean manufacturing in indian SMEs-A case study. Materials Today: Proceedings 2019; 16: 1244-50. https://doi.org/10.1016/j.matpr.2019.05.221.
  • 34. Rudawska A, Flechsig A, Miturska I. Technical and Organisational Changes in a Selected Production Process. MATEC Web of Conferences 2019;252: 06014. https://doi.org/10.1051/matecconf/201925206014.
  • 35. Ścibiorek Z, Borucka A. Information in the decisionmaking process. Systemy Logistyczne Wojsk 2022; 56(1): 147-60. https://doi.org/10.37055/slw/155072.
  • 36. Sundar R, Balaji AN, Kumar RMS. A Review on lean manufacturing implementation techniques. Procedia Engineering 2014; 97: 1875-85. https://doi.org/10.1016/j.proeng.2014.12.341.
  • 37. Swarnakar V, Tiwari AK, Singh AR. Assessing benefits of lean six sigma approach in manufacturing industries: An Indian Context. Operations Management and Systems Engineering 2021; 127-44. https://doi.org/10.1007/978-981-15-6017-0_8.
  • 38. Urdan T, Kaplan A. The origins, evolution, and future directions of achievement goal theory. Contemporary Educational Psychology 2020; 61: 101862. https://doi.org/10.1016/j.cedpsych.2020.101862.
  • 39. Zhang Q, Yang L, Duan J, Qin J, Zhou Y. Research on integrated scheduling of equipment predictive maintenance and production decision based on physical modeling approach. Eksploatacja i Niezawodność - Maintenance and Reliability 2023; 26(1). https://doi.org/10.17531/ein/175409.
  • 40. Ziółkowski J, Borucka A. Markov model in logistic management of enterprise / Model Markowa w logistycznym zarządzaniu przedsiębiorstwem. Journal of KONBiN 2016; 38. https://doi.org/10.1515/jok-2016-0027.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8273080a-8a5e-41a1-a75a-d1b4464a02d2
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