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  • طراحی مدل تاب آوری در زنجیره تامین ایران خودرو با رویکرد مدل معادلات ساختاری و تکنیک های کیفی

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آدرس مقاله


کد مقاله : 536776 بازدید : 49 صفحه: 49 - 62

نوع مقاله: پژوهشی

طراحی مدل تاب آوری در زنجیره تامین ایران خودرو با رویکرد مدل معادلات ساختاری و تکنیک های کیفی

محورهای موضوعی : مدیریت صنعتی

Kazem Ravansetan 1 (Ph.D. Student, Economics and Administrative Sciences Faculty, university of Mazandaran, Babolsar, Iran)
Hasanali Aghajani 2 (Associate Prof., Economics and Administrative Sciences Faculty, university of Mazandaran, Babolsar, Iran)
Abdolhamid Safaei Ghadikolaei 3 (Associate Prof., Economics and Administrative Sciences Faculty, university of Mazandaran, Babolsar, Iran,)
Mahmood Yahyazaheh far 4 (Prof., Economics and Administrative Sciences Faculty, university of Mazandaran, Babolsar, Iran)

تاریخ دریافت : 1395/11/11 تاریخ پذیرش : 1396/07/25 تاریخ انتشار : 1396/10/03

کلید واژه: ایران خودرو, شکست, استراتژی, strategy, Disruption, resilience, تاب آوری, Iran khodro,

چکیده مقاله :

تحقیق حاضر به مطالعه و بررسی زنجیره تامین تاب آور شرکت ایران خودرو می پردازد. هدف این تحقیق تعیین استراتژی هایی است که بتواند از وقوع توقفات در خطوط تولید ایران خودرو جلوگیری کرده و یا در صورت توقف، با کمترین زمان ممکن به حالت قبل از شکست یا مطلوب تر از آن بازیابی شود. بعلاوه این تحقیق درصدد است تا مدل جامعی از تاب آوری در زنجیره تامین ایران خودرو معرفی نماید. در این تحقیق کلیه حالات شکست که پتانسیل توقف خطوط تولید ایران خودرو را دارد (12 حالت شکست) از طریق ادبیات تحقیق و نظرات خبرگان شناسایی شده است. جامعه آماری این تحقیق مدیران و کارشناسان واحدهای لجستیک، برنامه ریزی و بازرگانی شرکت ساپکو می باشد. در این تحقیق از تکنیک FMEA برای تعیین استراتژی های تاب آوری در زنجیره تامین قبل از بروز شکست و تکنیک جدید FAAO برای تعیین استراتژی های تاب آوری زنجیره تامین بعد از وقوع شکست استفاده شده است. همچنین با رویکرد مدل معادلات ساختاری و نرم افزار آموس مدل تاب آوری مورد تایید قرار گرفت. خبرگان از طریق تکنیک FMEA چهار حالت شکست که دارای بیشترین نمره اولویت ریسک (RPN) بوده اند را انتخاب و تعداد 21 استراتژی برای تاب آور ساختن زنجیره تامین ایران خودرو برای مقابله با این حالات شکست معرفی کردند. بعلاوه از طریق تکنیک FAAO نیز تعداد 6 استراتژی جهت تاب آور ساختن زنجیره تامین نسبت به شکست تعیین شد

چکیده انگلیسی:

This research deals with the resilient supply chain of Iran Khodro Company. The aim of this study is determining strategies going to be able to prevent the occurrence of stops in the production line of Iran Khodro, or in case of stop, how production lines are restored in the minimum time to the state of pre-disruption or the most favorable condition. This study intends to introduce a comprehensive model of resilience in the Iran Khodro supply chain. In this study, all failure modes that have the potential to stop Iran Khodro production lines (12 failure modes) have been identified through the research literature and expert opinions. The population of this research includes managers and experts of logistics and planning departments of Sapco Company. In this research, FMEA technique has been used to determine resilience strategies in the supply chain before the occurrence of failures and also a new technique which named failure analysis after occurrence (FAAO) is used to determine resilience strategies in the supply chain after the occurrence of a failure. Also, the resilience model is approved by structural equation modeling and Amos software. 4 failure modes that have the highest risk priority number (RPN) have been selected by experts using FMEA technique and 21 strategies have been introduced in order to make resilient the supply chain of Iran Khodro to deal with these failure modes. Moreover, 6 strategies have been determined using FAAO technique in order to make resilient the supply chain toward failure.

منابع و مأخذ:


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_||_

  1. Ambulkar, S., Blackhurst, J., & Grawe, S. (2015). Firm’s resilience to supply chain disruptions: Scale development and empirical examination. Journal of Operations Management, 33–34, 111–122.
    2.
  2. Azadeh, A., Meydani, N. S., and Haghighi, S. M. (2017). Performance optimization of an aluminum factory in economic crisis by integrated resilience engineering and mathematical programming. Safety Science 91, 335–350.
    3.
  3. Azevedo, S. A., Machado, V. H., Barroso, A. P., & Cruz-Machado, V. (2008). Supply Chain Vulnerability: Environment Changes and Dependencies. International Journal of Logistics and Transport, 1, 41–55.
    4.
  4. Berle, Ø. &Rice Jr., J. B. & Asbjørnslett, B. E. (2011). Failure modes in the maritime transportation system: a functional approach to throughput vulnerability. Maritime Policy & Management, 38(6), 605–632.
    5.
  5. Blackhurst, J., Dunn, K. S., & Craighead, C. W. (2011). An Empirically Derived Framework of Global Supply Resiliency. Journal of Business Logistics, 32(4), 374–391.
    6.
  6. Cardoso, S. S., Barbosa-Povoa, A. P., Relvas, S., & Novais, A. Q. (2015). Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty. Omega 56, 53–73.
    7.
  7. Carvalho, H. (2012). Modelling resilience in supply chain. Faculdade de Ciências e Tecnologia and Universidade Nova de Lisboa.
    8.
  8. Carvalho, H., Barroso, A. P., Machado, V. H., Azevedo, S. G., & Cruz -Machado, V. (2012a). Supply chain redesign for resilience using simulation. Computers & Industrial Engineering, 62(1).
    9.
  9. Carvalho, H., Tavares, J. G., & Cruz-Machado, V. (2012b). A mapping framework for assessing Supply Chain resilience. International Journal of Logistics Systems and Management, 12(3), 354–373.
    10.
  10. Carvalho, H., & Cruz-Machado, V. (2011). Integrating Lean, Agile, Resilience and Green Paradigms in Supply Chain Management (LARG_SCM). INTECH Open Access Publisher.
    11.
  11. Christopher, M., & Peck, H. (2004). Building the Resilient Supply Chain. The International Journal of Logistics Management, 15(2), 1–14.
    12.
  12. Craighead, C. W., Blackhurst, J., Rungtusanatham, M. J., & Handfield, R. B. (2007). The Severity of Supply Chain Disruptions: Design Characteristics and Mitigation Capabilities. Decision Sciences, 38(1), 131–156.
    13.
  13. Falasca, M., Zobel, C.W., & Cook, D., (2008). A decision support framework to assess supply chain resilience. The Proceedings of the 5th International ISCRAM Conference, Washington, DC, USA, pp. 596–605.
    14.
  14. Hanna, J. B., Skipper, J. B., & Hall, D. (2010). Mitigating supply chain disruption: the importance of top management support to collaboration and flexibility. International Journal of Logistics Systems and Management, 6, 397.
    15.
  15. Klibi W., & Martel A. (2012). Modeling approaches for the design of resilient supply networks under disruptions. International Journal of Production Economics, 135, 882–98.
    16.
  16. Kleindorfer, P. R., & Saad, G. H. (2005). Managing Disruption Risks in Supply Chains. Production and Operations Management, 14(1), 53–68.
    17.
  17. Loh, H. S., & Thai, V. V. (2014). Managing Port-Related Supply Chain Disruptions: A Conceptual Paper. The Asian journal of shipping and logistics, 30, 97-116.
    18.
  18. Matsuo, H. (2015). Implications of the Tohoku earthquake for Toyota’s coordination mechanism: Supply chain disruption of automotive semiconductors. International Journal of Production Economics, 161, 217–227.
    19.
  19. Mensah, P., & Merkuryev, Y. (2014). Developing a resilient supply chain. Procedia- Social and Behavioral Sciences, 110, 309-319.
    20.
  20. Mitchell, G., & McDonald, A. (2015). Developing resilience to England's future droughts: Time for cap and trade?. Journal of Environmental Management, 149, 97-107.
    21.
  21. Narasimhan, R., & Talluri, S. (2009). Perspectives on risk management in supply chains. Journal of Operation Management. 27(2),114–118.
    22.
  22. Pettit, T. J., Fiksel, J., & Croxton, K. L. (2010). Ensuring supply chain resilience: development of a conceptual framework. Journal of Business Logistics, 31(1), 1–21.
    23.
  23. Ponomarov, S. Y., &  Holcomb, M. C. (2009). Understanding the concept of supply chain resilience. The International Journal of Logistics Management, 20(1), 124–143.
    24.
  24. Rajesh, R. (2016). Forecasting supply chain resilience performance using grey prediction. Electronic Commerce Research and Applications 20, 42–58.
    25.
  25. Rice, J. B., & Caniato, F. (2003). Building a secure and resilient supply network. Supply Chain Management Review, 7(7), 22–30.
    26.
  26. Sheffi, Y., & Rice, J. B. (2005). A supply chain view of the resilient enterprise. Sloan Management Review, 47(1), 41–48.
    27.
  27. Shu, T., Chen, S., Wang, S., & Lai, K. K. (2014). GBOM-oriented management of production disruption risk and optimization of supply chain construction. Expert Systems with Applications, 41, 59–68
    28.
  28. Soni, U., Jain, V., & Kumar, S. (2014). Measuring supply chain resilience using a deterministic modeling approach. Computers & Industrial Engineering, 74, 11–25.
    29.
  29. Svensson, G. (2001). Perceived trust towards suppliers and customers in supply chains of the Swedish automotive industry. International Journal of Physical Distribution & Logistics Management, 31(9), 647–662.
    30.
  30. Torabi, S.A., Baghersad, M., & Mansouri, S.A. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research Part, E 79, 22–48.
    31.
  31. Zsidisin, George A., & Wagner, S. M. (2010). Do Perceptions Become Reality? The Moderating Role of Supply Chain Resiliency on Disruption Occurrence. Journal of Business Logistics, 31(2), 1–20. 
    32.

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