single-au.php

IJAT Vol.11 No.2 pp. 287-300
doi: 10.20965/ijat.2017.p0287
(2017)

Paper:

Development of Performance Simulation Model by Making Indices of Supply Chain Capabilities

Yoshinobu Ueno*, Jing Zhang**,†, and Kazuhiro Aoyama***

*Graduate School of Innovation Management, Kanazawa Institute of Technology
1-3-4 Atago, Minato-ku, Tokyo 105-0002, Japan

**School of Mathematics, Physics and Information Science, Zhejiang Ocean University
No.1, Haida South Road, Lincheng, Changzhi Island, Zhoushan, Zhejiang 316022, China

Corresponding author

***Department of Systems Innovation, The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Received:
January 8, 2016
Accepted:
January 20, 2017
Published:
March 1, 2017
Keywords:
supply chain, capability, modeling
Abstract

A supply chain (SC) is an organization in which multiple companies cooperate in supply functions, e.g., moving information or materials. Previous studies of SC designing and planning are categorized by their planning time periods into three categories, e.g., strategic, tactical, and operational. Top-down design of an SC, where design decisions are made in the sequence of strategic, tactical, and operational, is rational because of preventing rework of design work. But as few models supports strategic decision making quantitatively, top-down design of an SC has not been realized. In the present study, a method of quantitatively expressing SC’s capabilities of flowing information and materials and simulating its performance is developed. The method is then implemented with a system dynamic model to evaluate, qualitatively and quantitatively, the effectiveness of the model.

References
  1. [1] Y. Tanimizu, “Flexible Multi-Layered Dynamic Supply Chain Models with Cooperative Negotiation,” Int. J. of Automation Technology, Vol.7, No.1, pp. 128-135, 2012.
  2. [2] A. R. Ravindran and D. P. Jr. Warsing, “Supply Chain Engineering: Models and Applications,” CRC Press, 2012.
  3. [3] J. F. Shapiro, “Bottom-Up Vs. Top-Down Approaches to Supply Chain Modeling,” Quantitative Models for Supply Chain Management, Vol.17 of the series, Int. Series in Operations Research & Management Science, pp. 737-759, 1999.
  4. [4] B. M. Beamon, “Supply Chain Design and Analysis: Models and Methods,” Int. J. of Production Economics, Vol.55, No.3, pp. 281-294, 1999.
  5. [5] M. Al-Mashari and M. Zairi, “Supply chain re-engineering using enterprise resource planning (ERP) software of a SAP R/3 implementation case,” Int. J. lf Phycical Distribution and Logistics Management, Vol.30, 3/4, pp. 296-313, 2000.
  6. [6] K. Alendorfer et al., “Periodical capacity setting methods for make-to-order multi-machine production systems,” Int. J. of Production Research, Vol.52, No.16, 2014.
  7. [7] T. Altiok and R. Raghav, “Multi-Stage, Pull-Type Production/Inventory Systems,” IIE Trans., Vol.27, pp. 190-200, 1995.
  8. [8] B. C. Arntzen, G. B. Brown, T. P. Harrison, and L. L. Trafton, “Global Supply Chain Management at Digital Equipment Corporation,” INTERFACES, Vol.25, pp. 69-93, 1995.
  9. [9] Y. Aviv, “The effect of collavorative forecasting on supply chain performance,” Management Science, Vol.47, No.10, pp. 1326-1343, 2001.
  10. [10] E. Bottani, “A fuzzy QFD approach to achive agility,” Int. J. Production Economics, 2009.
  11. [11] X. Brusset, “Does supply chain visibiilty enhance agility?,” Int. J. Production Economics, Vol.171, pp. 46-59, 2016.
  12. [12] J. D. Camm, T. E. Chorman, F. A. Dull, J. R. Evans, D. J. Sweeney, and G. W. Wegryn, “Blending OR/MS, Judgement, and GIS: Restructuring P&G’s Supply Chain,” INTERFACES, Vol.27, No.1, pp. 128-142, 1997.
  13. [13] D. P. Christy and J. R. Grout, “Safeguarding Supply Chain Relationships,” Int. J. of Production Economics, Vol.36, pp. 233-242, 1994.
  14. [14] Y. H. Choi and A. Fujioka, “Framework for Appropriate Supply Chain Management Strategies: Focusing on the Flexibility of Product Usability,” J. of The Society of Business Administration Ryukoku University, Vol.46, No.1, pp. 13-29, 2006.
  15. [15] M. A. Cohen and S. Moon, “Impact of Production Scale Economies, Manufacturing Complexity, and Transportation Costs on Supply Chain Facility Networks,” J. of Manufacturing and Operations Management, Vol.3, pp. 269-292, 1990.
  16. [16] P. Georgiadis, D. Vlachos, and E. Iakovou, “A system dynamics modeling framework for the strategic supply chain management of food chain,” Simulation Practice and Theory, Vol.8, pp.321-339, 2000.
  17. [17] A. N. Haq and G. Kannan, “Design of an integrated supplier selection and multi echelon distribution inventory model in a built-to-order supply chain environment,” Int. J. of Production Research, Vol.44, No.10, pp. 1963-1985, 2006.
  18. [18] I. Harris, C. L. Mumford, and M. M. Naim, “A hybrid multi-objective approach to capacitated facility location with flexible store allocation for green logistics modeling,” Transportation Research, Part E, Vol.66, pp. 1-22, 2014.
  19. [19] S. H. Huang et al., “Computer-assisted supply chain configuration based on supply chain operations reference (SCOR) model,” Computers & Industrial Engineering, Vol.48, pp. 377-394, 2005.
  20. [20] H. B. Hwarng, C. S. P. Chong, N. Xie, and T. F. Burgess, “Modeling a complex supply chain: Understanding the effect of simplified assumptions,” Int. J. of Production Research, Vol.43, No.13, pp. 2829-2872, 2005.
  21. [21] K. Ishii, K. Takahashi, and R. Muramatsu, “Integrated Production, Inventory and Distribution Systems,” Int. J. of Production Research, Vol.26, No.3, pp. 473-482, 1998.
  22. [22] J. Kauremaa and S. Suzuki, “Evaluating SCM Practices with the SCM Scorecard: Evidence from an Int. Study,” POMS 18th Annual Conf., 2007.
  23. [23] M. Kubo, “Logistics Engineering, New frontier of management science Vol.8,” Asakura Publishing Co., Ltd., 2001.
  24. [24] D. M. Lambert, “Supply Chain Management, Process, Partnerships, Performance,” Supply Chain Management Institute, 2006.
  25. [25] H. L. Lee and C. Billington, “Material Management in Decentralized Supply Chains,” Operations Research, Vol.41, No.5, pp. 835-847, 1993.
  26. [26] H. L. Lee and E. Feitzinger, “Product Configuration and Postponement for Supply Chain Efficiency, Institute of Industrial Engineers,” Proc. of Fourth Industrial Engineering Research Conf., pp. 43-48, 1995.
  27. [27] H. L. Lee, C. Billington, and B. Carter, “Hewlett-Packard Gains Control of Inventory and Service through Design for Localization,” INTERFACES, Vol.23, No.4, pp. 1-11, 1993.
  28. [28] H. L. Lee, V. Padmanabhan, and S. Whang, “Information Distortion in a Supply Chain: The Bullwhip Effect,” Management Science, Vol.43, No.4, pp. 546-558, 1997.
  29. [29] T. J. Lowe, R. E. Wendell, and G. Hu, “Screening location strategies to reduce exchange rate risk,” European J. of Operational Research, Vol.136, pp. 573-590, 2002.
  30. [30] L. Lu, “A one-vendor multi-buyer integrated model,” European J. of Operational Research, Vol.81, No.2, pp. 312-232, 1995.
  31. [31] A. Nagurney, “Optimal supply chain network design and redesign at minimal total cost and with demand satisfaction,” Int. J. of Production Economics, Vol.128, Issue 1, pp. 200-208, 2010.
  32. [32] D. D. Newhart, K. L. Stott, and F. J. Vasko, “Consolidating Product Sizes to Minimize Inventory Levels for a Multi-Stage Production and Distribution Systems,” J. of the Operational Research Society, Vol.44, No.7, pp. 637-644, 1993.
  33. [33] O. R. Ovalle and A. C. Marquez, “The effectiveness of using e-collaboration tools in the supply chain: an assessment study with system dynamics,” J. of Purchasing & Supply Management, Vol.9, pp. 151-163, 2003.
  34. [34] M. Ozbayrak, T. C. Papadopoulou, and M. Akgun, “System dynamics modeling of a manufacturing supply chain system,” Simulation Modeling Practice and Theory, Vol.15, pp. 1338-1355, 2007.
  35. [35] P. Palaminos, L. Quezada, and G. Moncada, “Modeling the response capability of a production system,” Int. J. of Production Economics, Vol.122, pp. 458-468, 2009.
  36. [36] D. F. Pyke and M. A. Cohen, “Performance Characteristics of Stochastic Integrated Production-Distribution Systems,” European J. of Operational Research, Vol.68, No.1, pp. 23-48, 1993.
  37. [37] D. F. Pyke and M. A. Cohen, “Multi-product Integrated Production-Distribution Systems,” European J. of Operational Research, Vol.74, No.1, pp. 18-49, 1994.
  38. [38] C. Schnessweis and K. Zimmer, “Hierarchical coordination mechanisms within the supply chain,” European J. of Operational Research, Vol.153, pp. 687-703, 2004.
  39. [39] The Supply Chain Council, Inc., “SCOR Overview Ver. 9.0,” 2008.
  40. [40] A. Svoronos and P. Zipkin, “Evaluation of One-for-One Replenishment Policies for Multiechelon Inventory Systems,” Management Science, Vol.37, No.1, pp. 68-83,1991.
  41. [41] D. R. Towill, “Supply Chain Dynamics,” Int. J. of Computer Integrated Manufacturing, Vol.4, No.4, pp. 197-208, 1991.
  42. [42] D. R. Towill and A. D. Vecchio, “The Application of Filter Theory to the Study of Supply Chain Dynamics,” Production Planning and Control, Vol.5, No.1, pp. 82-96, 1994.
  43. [43] D. R. Towill, M. M. Naim, and J. Wikner, “Industrial Dynamics Simulation Models in the Design of Supply Chains,” Int. J. of Physical Distribution and Logistics Management, Vol.22, No.5, pp. 3-13, 1992.
  44. [44] S. Tzafestass and G. Kapsiotis, “Coordinated Control of Manufacturing/Supply Chains Using Multi-Level Techniques,” Computer Integrated Manufacturing Systems, Vol.7, No.3, pp. 206-212, 1994.
  45. [45] S. Vickery, R. Calantone, and C. Droge, “Supply Chain Flexibility: An Empirical Study,” J. of Supply Chain Management, Vol.35, Issue 2, pp. 16-24, 1999.
  46. [46] C. J. Vidal and M. Goetschalckx, “A global supply chain model with transfer pricing and transportation cost allocation,” European J. of Operational Research, Vol.129, pp. 134-158, 2001.
  47. [47] V. T. Voudouris, “Mathematical Programming Techniques to Debottleneck the Supply Chain of Fine Chemical Industries,” Computers and Chemical Engineering, Vol.20, S1269-S1274, 1996.
  48. [48] E. T. G. Wnag and H. L. Wei, “Interorganizational Governance Value Creation: Coodinating for Information Visibility and Flexibility in Supply Chain,” Decision Sciences, Vol.38, No.4, 2007.
  49. [49] J. Wikner, D. R. Towill, and M. Naim, “Smoothing Supply Chain Dynamics,” Int. J. of Production Economics, Vol.22, No.3, pp. 231-248, 1991.
  50. [50] F. Wu, S. Yeniyurt, D. Kim, and S. T. Cavusgil, “The impact of information technology on supply chain capability and firm performance: A resource-based view,” Industrial marketing Management, Vol.35, pp. 493-504, 2006.
  51. [51] Y. Y. Yusuf, A. Gunasekaranb, E. O. Adeleyec, and K. Sivayoganathanc, “Agile supply chain capabilities: Determinants of competitive objectives,” European J. of Operational Research, Vol.159, Issue 2, pp. 379-392, 2004.
  52. [52] C. Zhang and C. Zhang, “Design and simulation of demand information sharing in a supply chain,” Simulation Modeling Practice and Theory, Vol.15, pp. 32-46, 2007.
  53. [53] X. Zhao, J. Xie, and W. J. Zhang, “Coordination of joint pricing-production decisions in a supply chain,” IIE Trans., Vol.34, No.8, pp. 251-266.
  54. [54] H. Komoto and N. Mishima, “A Simulation System to Analyze Effects of Relocation of Machine Tools on Supply Chain Robustness,” Int. J. of Automation Technology, Vol.6, No.3, pp. 304-311, 2012.
  55. [55] L. Berrah, “Towards an aggregation performance measurement system model in a supply chain concept,” Computers in Industry, Vol.58, pp. 709-719, 2007.
  56. [56] J. Y. Chai, “Dynamic Controls of Genetic Algorithm Scheduling in Supply Chain,” Int. J. of Automation Technology, Vol.4, No.2, pp. 169-177, 2009.
  57. [57] G. Tomas, “Strategic Supply Chain Management: Improving Performance Through a Culture of Competitiveness and Knowledge Development,” Strategic Management J., Vol.28, pp. 1035-1052, 2007.
  58. [58] A. Yamasaki, K. Arashida, and T. Enkawa, “A Study on relationship between logistic performance and financial outcomes using SCM Logistics Score card and some consideration role of logistics department,” J. of Japan Logistics Society, Vol.2004, No.12, 2004.
  59. [59] R. Handfield and E. Nicholas, “Introduction to Supply Chain Management,” Pearson Educations, 1998.
  60. [60] J. Cox and M. Spencer, “The Constraints Management Handbook,” CRC press LLC, 1998.
  61. [61] J. Ashayeri and L. Lemmes, “Economic value added of supply chain demand planning: A system dynamics simulation,” Robotics and Computer-Integrated Manufacturing, Vol.22, pp. 550-556, 2006.
  62. [62] N. B. Kamath and R. Roy, “Capacity augmentation of a supply chain for a short lifecycle product: A system dynamics framework,” European J. of Operations Research, Vol.179, pp. 334-351, 2007.
  63. [63] L. Berrah, “Towards an aggregation performance measurement system model in a supply chain concept,” Computers in Industry, Vol.58, pp. 709-719, 2007.
  64. [64] L. Rabelo, H. Eskandari, T. Shaalan, and M. Hela, “Value chain analysis using hybrid simulation and AHP,” Int. J. Production Economics, Vol.105, pp. 536-547, 2007.
  65. [65] L. Kopczak and H. Lee, “Hewlett-Packard Company Deskjet Printer Supply Chain (A),” Stanford Graduate School of business, case GS-3A, 2004.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Dec. 12, 2017