The business world changes rapidly and customers’ demands are more varied than before, traditional push system which takes actions based on anticipated requirements and uses forecast to determine the manufacturing quantity is no longer effective enough for modeling market volatility. Therefore, the pull strategy, which is demand oriented, flexible and generates cost savings, is becoming more popular and prominent. The pull type supply chain management is also applied broadly in the high-tech industry where the market volatility is a very unique characteristic. In SCM, nonstructured oral communications make information sharing difficult and inefficient in a distributed environment. To solve this problem, Agent Technology (AT) is applied. AT in Business Intelligence (BI) has been proven that it is good tool in solving communication problems in distributed environments. This research focuses on the application of the make-to-plan (MTP) supply chain strategy and AT based technique. A case study of simulation of the MTP-based pull type supply chain is presented. Impacts of operator parameters, e.g., manufacturing throughput, forecast accuracy, and inventory on performance of the pull type control strategies are discussed in this study.
Cite this paper
T. Tseng, R. R. Gung and C. Huang, "Performance Evaluation for Pull-Type Supply Chains Using an Agent-Based Approach," American Journal of Industrial and Business Management, Vol. 3 No. 1, 2013, pp. 91-100. doi: 10.4236/ajibm.2013.31012.
 J. Heikkila, “From Supply to Demand Chain Management: Efficiency and Customer Satisfaction,” Journal of Operations Management, Vol. 20, No. 6, 2002, pp. 183-193.
 K. C. Tan, “A Framework of Supply Chain Management Literature,” European Journal of Purchasing & Supply Management, Vol. 7, No. 1, 2001, pp. 39-48.
 M. C. Bonney, Z. M. Zhang, M. A. Head, C. C. Tien and R. J. Barson, “Are Push and Pull Systems Really So Different?” International Journal of Production Economics, Vol. 59, No. 1-3, 1999, pp. 53-64.
 J. D. Pagh and M. C. Cooper, “Supply Chain Postponement and Speculation Strategies: How to Choose the Right Strategy,” Journal of Business Logistics, Vol. 19. No. 2, 1998, pp. 13-33.
 S. C. Graves, A. H. G. R. Kan and P. H. Zipkin, “Logistics of Production and Inventory,” Elsevier Science Publishers B.V., Amsterdam, 1993.
 S. Minner, “Multiple-Supplier Inventory Models in Supply Chain Management: A Review,” International Journal of Production Research, Vol. 81-82, No. 1, 2003, pp. 265-279.
 J. Miltenburg and D. Sparling, “Managing and Reducing Total Cycle Time: Models and Analysis,” International Journal of Production Economics, Vol. 46-47, No. 1, 1996, pp. 89-108. doi:10.1016/0925-5273(94)00084-0
 L. ?zdamar and T. Yazga?, “Capacity Driven Due Date Settings in Make-to-Order Production Systems,” International Journal of Production Economics, Vol. 49, No. 1, 1997, pp. 29-44. doi:10.1016/S0925-5273(96)00116-8
 W. K. Ching, “An Inventory Model for Manufacturing Systems with Delivery Time Guarantees,” Computers Operations Research, Vol. 25, No. 5, 1998, pp. 367-377.
 M. Rabe, F. W. Jaekel and H. Weinaug, “Supply Chain Demonstrator Based on Federated Models and HLA Application,” SCS Publishing House, Berlin, 2006.
 J. D. Lenard and B. Roy, “Multi-Item Inventory Control: A Multicriteria View,” European Journal of Operational Research, Vol. 87, No. 3, 1995, pp. 685-692.
 K. Ueda, A. Lengyela and I. Hatonob, “Research into Artifacts, Center for Engineering,” The University of Tokyo, Tokyo, Japan Information Science and Technology Center, Kobe University, Kobe, 2007.
 F. F. Easton and D. R. Moodie, “Pricing and Lead-Time Decisions for Make-to-Order Firms with Contingent Orders,” European Journal of Operational Research, Vol. 116, No. 2, 1999, pp. 305-318.
 T. Burgess, B. Hwarng, N. Shaw and C. De Mattos, “Enhancing Value Stream Agility: The UK Speciality Chemical Industry,” European Management Journal, Vol. 20, No. 2, 2002, pp. 199-212.
 E. Feitzinger and H. L. Lee, “Mass Customization at Hewlett-Packard: The Power of Postponement,” Harvard Business Review, Vol. 75, No. 1, 1997, pp. 116-121.
 Z. Hu, K. Lee and J. Hur, “Determination of Optimal Build Orientation for Hybrid Rapid-Prototyping,” Journal of Materials Processing Technology, Vol. 130-131, No. 1, 2002, pp. 378-383.
 H. H. Chang, “A Model of Computerization of Manufacturing Systems: An International Study,” Information & Management, Vol. 39, No. 7, 2002, pp. 605-624.
 A. C. Lin, S. Y. Lin, D. Diganta and W. F. Lu, “An Integrated Approach to Determining the Sequence of Machining Operations for Prismatic Parts with Interacting Features,” Journal of Materials Processing Technology, Vol. 73, No. 1-3, 1998, pp. 234-250.
 S. F. Lou and Y. W. Si, “Fuzzy Adaptive Agent for Supply Chain Management,” Proceedings of the IEEE/WIC/ ACM International Conference on Intelligent Agent Technology (IAT’06), Hong Kong, 18-22 December 2006, pp. 313-320. doi:10.1109/IAT.2006.69
 Z. Chen, S. Ma and J. S. Shang, “Integrated Supply Chain Management for Efficiency Improvement,” International Journal of Productivity and Quality Management, Vol. 1, No. 1-2, 2006, pp. 183-206.
 F. Dignum and M. Greaves, “Agent Communication: An Introduction in Issues in Agent Communication,” Springer-Verlag, Berlin, 2000.
 S. H. Kang, “Intelligent Knowledge Acquisition Using Case-Based Reasoning: Knowledge Sharing and Reuse,” Thesis, University of Wollongong, Wollongong, 2003.
 J. Yang, H. Yan and S. P. Sethi, “Optimal Production Planning in Pull Lines with Multiple Products,” European Journal of Operational Research, Vol. 119, No. 3, 1999, pp. 582-604. doi:10.1016/S0377-2217(98)00358-0
 A. Hinkkanen, R. Kalakota, P. Saengcharoenrat, J. Stalaert and A. B. Whinston, “Distributed Decision Support Systems for Real Time Supply Chain Management Using Agent Technologies,” In: R. Kalakota and A. B. Whinston, Eds., Readings in Electronic Commerce, Addision-Wesley, Boston, 1997, pp. 275-291.
 N. R. Jennings, “Controlling Cooperative Problem Solving in Industrial Multi-Agent Systems Using Joint Intentions,” Artificial Intelligence, Vol. 75, No. 2, 1995, pp. 195-240. doi:10.1016/0004-3702(94)00020-2
 N. R. Jennings, P. Faratin, M. J. Johnson, T. J. Norman, P. O’Brien and M. E. Wiegand, “Agent-Based Business Process Management,” International Journal of Cooperative Information Systems, Vol. 5, No. 2-3, 1996, pp. 105-130.
 J. L. Alty, D. Griffiths, N. R. Jennings, E. H. Mamdani, A. Struthers and M. E. Wiegand, “ADEPT-Advanced Decision Environment for Process Tasks: Overview and Architecture,” Proceedings of the BCS Expert Systems Conference, Applications Track, Cambridge, 1994, pp. 359-371.
 S. Buckley, M. Ettl, G. Lin and K. Y. Wan, “Sense and Respond Business Performance Management,” Supply Chain Management on Demand, Vol. 2, No. 1, 2005, pp. 287-311.