Vol. 5 No. 2 (2017): BUSINESS & MANAGEMENT STUDIES: AN INTERNATIONAL JOURNAL
Articles

USING DEMATEL-ANP INTEGRATED APPROACH FOR DECIDING PRODUCTION STRATEGY FOR A PRODUCTION LINE

PDF
  • Sinan APAK,
  • Rüya ÇETE
Sinan APAK
Maltepe University
Rüya ÇETE
Vaillant Group
DOI: https://doi.org/10.15295/bmij.v5i2.123

Published 2017-09-16

How to Cite

APAK, S., & ÇETE, R. (2017). USING DEMATEL-ANP INTEGRATED APPROACH FOR DECIDING PRODUCTION STRATEGY FOR A PRODUCTION LINE. Business & Management Studies: An International Journal, 5(2), 363–381. https://doi.org/10.15295/bmij.v5i2.123

Abstract

Production planning includes push, pull and hybrid production systems that production firms determine their production strategies according to many variables before starting production. The administration of this process requires experience and time. The intensity of rivalry makes this kind of decision processes important, because no firm has the luxury to waste time and to make a wrong decision. In order to solve this problem, research proposes to use integrated decision-making trial and evaluation laboratory (DEMATEL) and analytic network process (ANP) together which are methods of multi-criteria decision-making models. The process being used to establish which options are found to be most acceptable for operations managers has been demonstrated how applicable it is by using the generated model in automotive industry.

PDF

Downloads

Download data is not yet available.

References

  1. Abdal,. P.L. (1989). Multi-product multi-market model for co-ordination of marketing and production decisions, International Journal of Systems Science 20(11). doi:10.1080/00207728908910284
  2. Absi, N., Kedad-Sidhoum, S. (2008). The multi-item capacitated lot-sizing problem with setup times and shortage costs, European Journal of Operational Research 185(3): 1351–1374. doi: 10.1016/j.ejor.2006.01.053
  3. Absi N., Kedad-Sidhoum, S., Dauzère-Pérès, S. (2011). Uncapacitated lot-sizing problem with production time windows, early productions, backlogs and lost sales, International Journal of Production Research 49(9): 2551-2566. DOI:10.1080/00207543.2010.532920.
  4. Aksakal, E., Dagdeviren, M. (2010). ANP ve DEMATEL Yöntemleri İle Personel Seçimi Problemine Bütünleşik Bir Yaklaşım, Gazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi, 25(4): 905-913.
  5. Angelos A.E., Kouikogloua, V.S. (2011). Lead-time analysis and a control policy for production lines, International Journal of Production Research 49(7). DOI:10.1080/00207541003627845
  6. Battini D., Boysen N., Emde. S. (2013). Just-in-time supermarkets for part supply in the automobile industry, Journal of Management Control, 24: 209–217, doi: 10.1007/s00187-012-0154-y.
  7. Boysen, N., Emde, S., Hoeck, M., Kauderer, M. (2015). Part logistics in the automotive industry: decision problems, literature review and research agenda, European Journal of Operational Research, 242(1): 107–120. http://dx.doi:10.1016/j.ejor.2014.09.065
  8. Bryan, N., Srinivasan, M.M. (2014). Real-time order tracking for supply systems with multiple transportation stages.” European Journal of Operational Research 236(2): 548-560. doi.org/10.1016/j.ejor.2014.01.062.
  9. Büyüközkan, G., and Güleryüz, S. (2016). An integrated DEMATEL-ANP approach for renewable energy resources selection in Turkey. An integrated DEMATEL-ANP approach for renewable energy resources selection in Turkey Volume 182, December 2016, Pages 435–448.
  10. Clément, C., Giard, V., Sali, M. (2015). High variety impacts on Master Production Schedule: a case study from the automotive industry, IFAC-PapersOnLine 48(3): 1073-1078.
  11. Chemweno, P., Pintelon, L., Van Horenbeek, A., Muchiri, P. (2015). Development of a risk assessment selection methodology for asset maintenance decision making: An analytic network process (ANP) approach, International Journal of Production Economics (170): 663-676.
  12. Faccio, M. (2014). “The impact of production mix variations and models varieties on the parts feeding policy selection in a JIT assembly system, International Journal Advance Manufacturing Technology 42(1–4): 543–560. DOI 10.1007/s00170-014-5675-0.
  13. Fazli, S., Kiani Mavi R., Vosooghidizaji, M. (2015). Crude oil supply chain risk management with DEMATEL–ANP, Operational Research 15:453–480 http://dx.doi.org/10.1007/s12351-015-0182-0
  14. Giard, V., Jeunet, J. (2010). Optimal sequencing of mixed models with sequence-dependent setups and utility workers on an assembly line, International Journal of Production Economics 123(2): 290-300. http://dx.doi:10.1016/j.ijpe.2009.09.001
  15. Golcuk, I., . Baykasoğlu, A. (2016). An analysis of DEMATEL approaches for criteria interaction handling within ANP, Expert Systems with Applications 46: 346-366.
  16. Holmström, J., Främling, K., Ala-Risku, T. (2010). The uses of tracking in operations management: Synthesis of a research program, International Journal of Production Economics 126(2): 267-275. http://dx.dodoi:10.1016/j.ijpe.2010.03.017.
  17. Jonsson, P., Ivert, L.K. (2015). Improving performance with sophisticated master production scheduling, International Journal of Production Economics 168: 118-130.
  18. Kılıç, H.S., Durmuşoğlu, M.B. (2015). Advances in assembly line parts feeding policies: a literature review, Assembly Automation 35(1): 57 – 68. http://dx.doi.org/10.1108/AA-05-2014-047.
  19. Li, C.W., Tzeng G H. (2009). Identification of a threshold Value for the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by a semiconductor intellectual property mall, Expert Systems with Applications 36(6): 9891-9898.
  20. Long, H.J., Wang, L.Y., Shen J., Wu, M.X., Jiang, Z.B. (2013). Product service system configuration based on support vector machine considering customer perception, International Journal of Production Research 51(18): 5450-5468. http://dx.doi.org/10.1080/00207543.2013.778432
  21. McDaniel, S.W., Moore, S.B. 2005. Pre-Production Relationship Marketing, Journal of Relationship Marketing 4:(1-2) 73-90. doi:10.1300/J366v04n01_06
  22. Olhager, J., Östlund, B. (1990). An integrated push-pull manufacturing strategy, European Journal of Operational Research 45(2–3): 135-142.
  23. Ozer, O., Uncu, O. (2015). Integrating dynamic time-to-market, pricing, production and sales channel decisions, European Journal of Operational Research 242(2): 487-500. http://dx.doi.org/10.1016/j.ejor.2014.09.001.
  24. Pandey, P.C., Khokhajaikiat, P. (1996). Performance modelling of multistage production systems operating under hybrid push/pull control, International Journal of Production Economics 43(2–3): 115-126.
  25. Puchkova, A., Romancer, J.L, McFarla, D. (2016). Balancing Push and Pull Strategies within the Production System. IFAC-PapersOnLine 49-2 (2016) 066–071. DOI. 10.1016/j.ifacol.2016.03.012
  26. Razaa, S.A., Turiac, M. (2016). Joint optimal determination of process mean, production quantity, pricing, and market segmentation with demand leakage, European Journal of Operational Research 249(1): 312-326. http://dx.doi.org/10.1016/j.ejor.2015.08.032
  27. Saaty, T.L. (2001). The analytic network process RWS Publications, Pittsburgh.
  28. Saaty, T.L. (1996). Dependence and Feedback the Analytic Network Process. RWS Publications, Pittsburgh.
  29. Sali, M., Sahin E. (2016). Line feeding optimization for Just in Time assembly lines: An application to the automotive industry. International Journal of Production Economics 174: 54–67. doi:10.1016/j.ijpe.2016.01.009
  30. Shao, J., Taisch, M., Ortega-Mier, M. (2016). A grey-DEMATEL analysis on the barriers between environmentally friendly products and consumers: practitioners' viewpoints on the European automobile industry, Journal of Cleaner Production 112: 3185-3194.
  31. Shi, N., Zhou, S., Wang, F., Xu S., Xiong, S. (2014). Horizontal cooperation and information sharing between suppliers in the manufacturer–supplier triad, International Journal of Production Research 52(15): 4526-4547. DOI:10.1080/00207543.2013.869630
  32. Shieh, J.I., Wu, H.H., Huang, K.K. (2010). A dematel metot in identifying key success factors of hospital service quality, Knowledge-Based Systems 23(3): 277-282.
  33. Slomp, J., Bokhorst, J.A.C., Germs, R. (2009). A lean production control system for high-variety/low-volume environments: a case study implementation, Production Planning & Control 20(7): 586-595. doi:10.1080/09537280903086164
  34. Spilbeeck, I V., Houdt, B.V. (2015). Performance of rate-based pull and push strategies in heterogeneous networks, Performance Evaluation (91): 2-15.
  35. Toni, A.D., Tonchia, S. (2002). New production models: A strategic view, International Journal of Production Research 40(18).
  36. Tseng, M.L., Lin, Y.H. (2008). Application of Fuzzy DEMATEL to Develop a Cause and Effect Model of Municipal Solid Waste, Environment Assessment 158: 519-533.
  37. Tzeng, G.H. Huang, J.J. (2011). Multi Attribute Decision Making: Methods and Applications, USA, CRC Press.
  38. Wu, K., Zhao, N., Gao, L., Lee, C.K.M. (2016). Production control policy for tandem workstations with constant service times and queue time constraints, International Journal of Production Research. Published online: 05 Jan 2016. DOI:10.1080/00207543.2015.1129468
  39. Yoon , S.Y., Ko, J., Mung, M. (2016). A model for developing job rotation schedules that eliminate sequential high workloads and minimize between-worker variability in cumulative daily workloads: Application to automotive assembly lines, Applied Ergonomics 55: 8–15. http://dx.doi:10.1016/j.apergo.2016.01.011