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Supplier Selection for Mixed-Model Production: A Case Study from the Apparel Industry

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Treść / Zawartość
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Warianty tytułu
PL
Selekcja dostawców dla produkcji wielowersyjnej: Analiza przemysłu odzieżowego
Języki publikacji
EN
Abstrakty
EN
The mass-customization trend as flexible production philosophy has been adopted by many industries as a reaction to the fast changing customer demand environment. In relation to that mixed-model production (MMP) is a possibility for increasing flexibility, especially in the assembly department. However, many apparel companies have failed in their transition from traditional manufacturing to new, flexible manufacturing, which makes it difficult for them to be selected as suppliers who are capable of MMP. In most of the studies that have been done before, the problem of supplier selection was based on productivity and cost as the main selection criteria. As an alternative solution this research presents a new group of criteria for supplier selection with respect to the goal of MMP. The methodology of combining the analytical hierarchy process (AHP) with the support of the commercial software package Expert Choice and cluster analysis (CA) is proposed in this study. The results obtained present a new group of criteria, ranked by their importance, that the supplier needs to fulfil in order to be selected for MMP. Furthermore the large number of available suppliers was grouped into four clusters based on their similar characteristics by using CA. Finally the most acceptable cluster for MMP was selected using AHP. The methodology presented in this study can support the apparel industry in better decision making in the process of selecting the best group of suppliers for mixed-model production.
PL
W wielu przemysłach wprowadzono system zindywidualizowanej produkcji masowej jako reakcję na szybko zmieniające się wymagania konsumentów. Dotychczas selekcja dostawców oparta była na produktywności i analizie kosztów. Ten artykuł prezentuje alternatywne rozwiązanie z wyborem nowej grupy kryteriów. Przedstawiono metodologię połączenia metody hierarchicznej analizy z pakietem Expert Choice i analizą klastrów. W proponowanej metodzie dostawcy zostali podzieleni na cztery klastry na podstawie podobieństwa charakterystyk. W efekcie najbardziej akceptowalny klaster zostaje wybrany przy zastosowaniu metody hierarchicznej analizy. Metoda ta może wspomóc prawidłowe funkcjonowanie przemysłu odzieżowego.
Rocznik
Strony
8--12
Opis fizyczny
Bibliogr. 30 poz., rys., tab.
Twórcy
autor
  • Fashion Design and Engineering Department, Dong Hua University, Shanghai, P. R. China
autor
  • Fashion Design and Engineering Department, Dong Hua University, Shanghai, P. R. China
Bibliografia
  • 1. Black J. Design Rules for Implementing the Toyota Production System. International Journal of Production Research 2007; 45: 3639-36641.
  • 2. Ghosh S, Gagnon RJ. A Comprehensive Literature Review and Analysis of the Design, Balancing and Scheduling of Assembly Systems. International Journal of Production Research 1989; 27, 4: 637-670.
  • 3. Boysen N, Fliedner M, Scholl A. A Classification of Assembly Line Balancing Problems. European Journal of Operational Research 2007; 183: 674-693.
  • 4. Becker C, Scholl A. A Survey on Problems and Methods in Generalized Assembly Line Balancing. European Journal of Operational Research 2006; 168: 694-715.
  • 5. Boysen N, Fliedner M, Scholl A. Sequencing Mixed-model Assembly Lines: Survey, Classification and Model Critique. European Journal of Operational Research 2009; 192: 349-373.
  • 6. Chan FTS, Chan HK. An AHP Model for Selection of Suppliers in the Fast Changing Fashion Market. International Journal of Advanced Manufacturing Technology 2010; 51: 1195-1207.
  • 7. Dickson GW. An Analysis of Vendor Selection Systems and Decisions, Journal of Purchasing, 1966; 2/1: 5–17.
  • 8. Weber CA, Current J, Benton WC. Vendor Selection Criteria and Methods. European Journal of Operational Research 1991; 50: 2-18.
  • 9. Chai J, Liu JNK, Ngai EWT. Application of Decision –making Techniques in Supplier Selection: A Systematic Review of Literature. Expert Systems with Applications 2013; 40: 3872-3885.
  • 10. Ho W, Xu X, Dey PK. Multi-criteria Decision Making Approaches for Supplier Evaluation and Selection: A Literature Review. European Journal of Operation Research 2010; 202: 16-24.
  • 11. Vaidya OS, Kumar S. Analytic Hierarchy Process: An Overview of Applications. European Journal of Operational Research 2006;169: 1-29.
  • 12. Akarte MM, Surendra NV, Ravi B, Rangaraj N. Web Based Casting Supplier Evaluation Using Analytical Hierarchy Process. Journal of the Operational Research Society 2001; 52: 511-522.
  • 13. Chan FTS, Chan HK, Ip RWL, Lau HCW. A Decision Support System for Supplier Selection in the Airline Industry. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 2007; 221: 741-758.
  • 14. Levary RR. Using the Analytic Hierarchy Process to Rank Foreign Suppliers based on Supply Risks. Computers & Industrial Engineering 2008; 55: 535-542.
  • 15. Chan FTS, Chan HK. Development of the Supplier Selection Model - A Case Study in the Advanced Technology Industry. Proceeding of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 2004; 218: 1807-1824.
  • 16. Ozkan B, Basligil H, Sahin N. Supplier Selection Using Analytic Hierarchy Process: An Application from Turkey. WCE 2011; 2: 1160-1165.
  • 17. Gungor A, Coskun S, Durdur G, Guner Goren H. A Supplier Selection, Evaluation and Re-evaluation Model for Textile Retail Organizations. Tekstil ve Konfeksiyon 2010; 3: 181-187.
  • 18. Erbasi A. Use of Analytic Hierarchy Process Method in Determination of Performance Indicators: The Case of Turkish Textile Industry. Tekstil ve Konfeksiyon 2012; 3: 177-184.
  • 19. Ertugrul I, Ozbay B. Supply Chain Optimization and Distribution Network Application with AHP in Yarn Company. Tekstil ve Konfeksiyon 2013; 23: 87-93.
  • 20. Koprulu A, Albayrakoglu MM. Supply Chain Management in the Textile Industry: A Supplier Selection Model with the Analytical Hierarchy Process. In: ISAHP, Vina Del Mar, Chile, August 3-6, 2007.
  • 21. Yayla AY, Ozbek A, Yildiz A. Fuzzy TOPSIS Method in Supplier Selection and Application in the Garment Industry. Fibres & Textiles in Eastern Europe 2012; 20: 20-23.
  • 22. Shtub A, Dar-el EM. A Methodology for the Selection of Assembly Systems. International Journal of Production Research 1989; 27: 175-186.
  • 23. Sen CG, Cinar G. Evaluation and Pre-allocation of Operators with Multiple Skills: A Combined Fuzzy AHP and Max-min Approach. Expert Systems with Applications 2010; 37: 2043-2053.
  • 24. Anzanello MJ, Fogliatto FS. Selecting the Best Clustering Variables for Grouping Mass-customized Products Involving Worker’s Learning. Int. J. Production Economics 2011;130: 268-276.
  • 25. Bottani E, Rizzi A. An Adapted Multicriteria Approach to Suppliers and Products Selection – An Application Oriented to Lead- time Reduction. International Journal of Production Economics 2008; 111: 763-781.
  • 26. Saaty TL. An Exposition of the AHP in Reply to the Paper: Remarks on the Analytic Hierarchy Process. Management Science 1990; 36: 259–268.
  • 27. Saaty TL. Decision Making with the Analytic Hierarchy Process. International Journal of Services Sciences 2008; 1: 83-98.
  • 28. Ishizaka A, Labib A. Analytic Hierarchy Process and Expert Choice: Benefits and Limitations. OR Insight 2009; 22: 201-220.
  • 29. www.expertchoice.com
  • 30. Spahija S, Shehi E, Guxho G. Evaluation of Production Effectiveness in Garment Companies through Key Performance Indicators. Autex Research Journal 2012; 12: 62-66.
Typ dokumentu
Bibliografia
Identyfikator YADDA
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