Simulation Model of Outsourcing Decision for Tyre Rim Assembly Operation

Yıl 2020, Cilt: 25 Sayı: 2, 743 - 754, 31.08.2020

Duygu Yılmaz Eroğlu

https://doi.org/10.17482/uumfd.591155

Öz

The decision of outsourcing has been one of the critical issues in organization management. The main purpose of outsourcing is often reducing the costs, focusing on the core business, solving capacity problems, improving service quality, and accessing to intellectual capital. In cases where just in time delivery required or high logistic costs occurred, global outsourcing has been replaced by suppliers that are locally close to manufacturer, in automotive logistic industry. In this article, a simulation study has been carried out to make the decision of assembly operation insourcing or outsourcing for tyre and rim parts which have high transportation cost due to high volume. Utilizing the simulation model and experimental design, the best scenario has been determined to reduce the work in process inventory between outsource firm - manufacturer and appropriate values have been obtained for delivery frequency, delivery quantity and number of employees. The contributions of the article to the literature can be considered in two titles. The first one is the detailed explanation of the methodology that might be followed, if the outsourcing decision is made with simulation techniques and experimental design. The second one is demonstration of applicability of the method by obtained results using masked production data for tyre-rim assembly

Anahtar Kelimeler

Tyre-Rim Assembly, Simulation, Design of Experiment

LASTİK JANT BİRLEŞTİRME OPERASYONU İÇİN DIŞ KAYNAK KULLANIM KARARI BENZETİM MODELİ

Öz

İşletmelerde dış kaynak kullanım (outsourcing) kararı, organizasyon yönetimindeki kritik konularından biridir. Dış kaynak kullanımının ana amacı, çoğu zaman maliyet düşürmek, ana işe odaklanmayı sağlamak, kapasite problemlerini çözmek, servis kalitesini arttırmak, entelektüel sermayeye erişebilmektir. Otomotiv üretim endüstrisinde ise küresel dış kaynak kullanımı, tam zamanında sevkiyat yapılması gereken durumlarda ya da lojistik maliyetlerinin yüksek olduğu durumlarda, yerini üretici firmaya yakın bölgelerdeki tedarikçilere bırakmaktadır. Bu makalede de, hacmi gereği taşıma maliyetleri yüksek olan lastik ve jant parçalarının birleştirme operasyonunun üretici firma içinde ya da dış kaynak kullanarak yapma kararının verilebilmesi için simülasyon çalışması yapılmıştır. Simülasyon modeli ve deneysel tasarım ile tedarikçi ile üretici arasındaki ara stok miktarını düşürebilecek en iyi senaryo belirlenmiş, taşıma sıklığı, taşıma miktarı, çalışan sayısı gibi faktörler için en uygun değerlerler elde edilebilmiştir. Makalenin literatüre katkısı iki başlıkta derlenebilir. İlki, dış kaynak kullanımı kararının simülasyon teknikleri ve deneysel tasarım ile verilmesi durumunda izlenebilecek yöntemin ayrıntılarıyla aktarılmasıdır. İkincisi ise, lastik-jant birleştirme operasyonu için, gerçek üretim verileriyle elde edilen sonuçlarla yöntemin uygulanabilirliğinin ortaya koyulabilmesidir.

Anahtar Kelimeler

Lastik-Jant Birleştirme, benzetim, deneysel tasarım

Kaynakça

• 1. Antràs, P.(2003) Firms, contracts, and trade structure, The Quarterly Journal of Economics, 118(4), 1375-1418. doi:10.3386/w9740
• 2. Antràs, P. (2005) Incomplete contracts and the product cycle, American Economic Review, 95(4), 1054-1073. doi: 10.3386/w9945
• 3. Campa, J., ve Goldberg, L.S.(1997) The evolving external orientation of manufacturing industries: evidence from four countries (No. w5919). National Bureau of Economic Research. doi:10.3386/w5919
• 4. Cao, Q., ve Wang, Q. (2007) Optimizing vendor selection in a two-stage outsourcing process, Computers & operations research, 34(12), 3757-3768. doi:10.1016/j.cor.2006.01.013
• 5. Chan, F.T. S., Chan, H.K., ve Lau, H.C.W. (2002) The state of the art in simulation study on FMS scheduling: a comprehensive survey, The International Journal of Advanced Manufacturing Technology, 19(11), 830-849. doi:10.1115/esda2006-95077
• 6. Chan, F. T., ve Chan, H. K. (2004) A comprehensive survey and future trend of simulation study on FMS scheduling, Journal of Intelligent Manufacturing, 15(1), 87-102. doi:10.1023/b:jims.0000010077.27141.be
• 7. de Almeida, A.T. (2007) Multicriteria decision model for outsourcing contracts selection based on utility function and ELECTRE method, Computers & Operations Research, 34(12), 3569-3574. doi:10.1016/j.cor.2006.01.003
• 8. Drauz, R. (2014) Re-insourcing as a manufacturing-strategic option during a crisis—Cases from the automobile industry, Journal of Business Research, 67(3), 346-353. doi:10.1016/j.jbusres.2013.01.004
• 9. Feenstra, R.C.(1998) Integration of trade and disintegration of production in the global economy, Journal of economic Perspectives, 12(4), 31-50. doi:10.1257/jep.12.4.31
• 10. Gençosman, B., Orbak, Â., ve Orbak, İ. (2015) Deneysel tasarım ile sulu çözeltilerden metal ayrışımına etki eden faktörlerin optimizasyonu, Uludağ University Journal of The Faculty of Engineering, 20(1), 39-49. doi:10.17482/uujfe.24520
• 11. Grossman, G.M., ve Helpman, E.(2005) Outsourcing in a global economy, The Review of Economic Studies, 72(1), 135-159. doi:10.1111/0034-6527.00327
• 12. Halim, N.H.A., Yusuf, N., Jaafar,R., Jaffar, A., Kaseh, N.A.I., ve Azira, N.N. (2015) Effective material handling system for JIT automotive production line, Procedia Manufacturing, 2, 251-257. doi:10.1016/j.promfg.2015.07.044
• 13. Harrell, C., Bowden, R., ve Ghosh, B. K. (2000) Simulation using promodel, McGraw-Hill Higher Education.
• 14. Hayter, R. (1997) The dynamics of industrial location: the factory, the firm and the production system. Wiley.
• 15. Ingemansson, A., Bolmsjö, G., ve Harlin, U. (2002, October) A survey of the use of the discrete-event simulation in manufacturing industry, In Proceedings of the 10th international manufacturing conference.
• 16. Jahangirian, M., Eldabi, T., Naseer, A., Stergioulas, L.K., ve Young, T. (2010), Simulation in manufacturing and business: A review, European Journal of Operational Research, 203(1), 1-13. doi:10.1016/j.ejor.2009.06.004
• 17. Küresel Tedarik Zinciri Trendleri,(2010) Erişim Adresi: https://www.consultancy.nl/media/PRTM%20Supply%20Chain%20Trends%202010-2012-1019.pdf (Erişim Tarihi: 11.07.2019).
• 18. Masood, S. (2006) Line balancing and simulation of an automated production transfer line, Assembly Automation, 26(1), 69-74. doi: 10.1108/01445150610645684
• 19. McMillan, J. (1995) Reorganizing vertical supply relationships. Trends in business organization: Do participation and cooperation increase competitiveness, 203-222.
• 20. Montgomery, D. C. (2007) Introduction to statistical quality control.,John Wiley & Sons.
• 21. Negahban, A., ve Smith, J. S. (2014) Simulation for manufacturing system design and operation: Literature review and analysis, Journal of Manufacturing Systems, 33(2), 241-261. doi: 10.1016/j.jmsy.2013.12.007
• 22. Roy, R. K. (2001) Design of experiments using the Taguchi approach: 16 steps to product and process improvement, John Wiley & Sons.
• 23. Ruiz-Torres, A.J., ve Mahmoodi, F. (2008) Outsourcing decision in manufacturing supply chains considering production failure and operating costs, International Journal of Integrated Supply Management, 4(2), 141-158. doi: 10.1504/ijism.2008.016615
• 24. Sarkis, J., ve Sundarraj, R.P. (2000) Factors for strategic evaluation of enterprise information Technologies, International journal of physical distribution & logistics management, 30(3/4), 196-220. doi: 10.1108/09600030010325966
• 25. Sarkis, J., ve Talluri, S. (2002) A model for strategic supplier selection. Journal of supply chain management, 38(4), 18-28. doi:10.1111/j.1745-493x.2002.tb00117.x
• 26. Scholl, A., ve Klein, R. (1999) ULINO: Optimally balancing U-shaped JIT assembly lines, International Journal of Production Research, 37(4), 721-736. doi:10.1080/002075499191481
• 27. StatSoft, I. N. C. (2001) STATISTICA (data analysis software system), version 6. Tulsa, USA, 150.
• 28. WORLD TRADE ORGANIZATION (1998) Annual Report 1998 (Geneva: World Trade Organization).