Computer Science and Information Engineering

Chung-Ho Chen This email address is being protected from spambots. You need JavaScript enabled to view it.1 and Chao-Yu Chou2

1Department of Management and Information Technology, Southern Taiwan University, Tainan, Taiwan 710, R.O.C.
2Department of Finance, National Taichung University of Science and Technology, Taichung, Taiwan, R.O.C.

 

Received: December 8, 2010
Accepted: November 28, 2011
Publication Date: March 1, 2012

Download Citation: ||https://doi.org/10.6180/jase.2012.15.1.05  


ABSTRACT

Determination of optimum mean of the process characteristic is an important theme in quality improvement. Meanwhile, economic selection of order quantity is a key factor in inventory management since an inappropriate order quantity may result in unreasonably high inventory or stockout cost. In the present paper, we modify Chen and Liu’s model [8] to simultaneously determine the optimal purchaser’s order quantity and producer’s process mean by incorporating an asymmetric loss function. The solution procedure for this modified model is developed and numerical examples are given for illustration. Based on the sensitivity analyses, the common parameters having significant effects on the expected total profit of the system are the selling price per unit to the customer (R) and the mean demand of customer (μx). Therefore, accurate estimation of R and μx in order to obtain the optimal control on the order quantity and the maximum expected total profit of the system would be highly desired.


Keywords: Order Quantity, Process Mean, Asymmetric Quadratic Quality Loss Function, Uniform Distribution, Normal Distribution


REFERENCES

  1. [1] Chen, C. H. and Chou, C. Y., “Determining the Optimum Process Mean under a Lognormal Distribution,” Quality & Quantity, Vol. 39, pp. 119124 (2005).
  2. [2] Chen, C. H., “The Optimum Selection of Imperfect Quality Economic Manufacturing Quantity and Process Mean by Considering Quadratic Quality Loss Function,” Journal of the Chinese Institute of Industrial Engineers, Vol. 23, pp. 1219 (2006).
  3. [3] Chen, C. H. and Lai, M. T., “Determining the Optimum Process Mean Based on Quadratic Quality Loss Function and Rectifying Inspection Plan,” European Journal of Operational Research, Vol. 182, pp. 755 763 (2007a).
  4. [4] Chen, C. H. and Lai, M. T., “Economic Manufacturing Quantity, Optimum Process Mean, and Economic Specification Limits Setting under the Rectifying Inspection Plan,” European Journal of Operational Research, Vol. 183, pp. 336344 (2007b).
  5. [5] Chen, C. H. and Khoo, M. B. C., “Joint Determination of Optimum Process Mean and Economic Specification Limits for Rectifying Inspection Plan with Inspection Error,” Journal of the Chinese Institute of Industrial Engineers, Vol. 25, pp. 389398 (2008).
  6. [6] Chen, C. H. and Khoo, M. B. C., “Optimum Process Mean and Manufacturing Quantity Settings for Serial Production System under the Quality Loss and Rectifying Inspection Plan,” Computers & Industrial Engineering, Vol. 57, pp. 10801088 (2009).
  7. [7] Pfohl, H. C., Cullmann, O. and Stolzle, W., “Inventory Management with Statistical Process Control: Simulation and Evaluation,” Journal of Business Logistics, Vol. 20, pp. 101120 (1999).
  8. [8] Chen, S. L. and Liu, C. L., “Procurement Strategies in the Presence of the Spot Market-an Analytical Framework,” Production Planning & Control, Vol. 18, pp. 297309 (2007).
  9. [9] Chen, S. L. and Liu, C. L., “The Optimal Consignment Policy for the Manufacturer under Supply Chain Coordination,” International Journal of Production Research, Vol. 46, pp. 51215143 (2008).
  10. [10] Li, J. and Liu, L., “Supply Chain Coordination with Manufacturer’s Limited Reserve Capacity: An Extended Newsboy Problem,” International Journal of Production Economics, Vol. 112, pp. 860868 (2008).
  11. [11] Darwish, M. A., “Economic Selection of Process Mean for Single-Vendor Single-Buyer Supply Chain,” European Journal of Operational Research, Vol. 199, pp. 162169 (2009).
  12. [12] Chen, S. L. and Huang, S. C., “Managing Supply Chain Risk with Options and Online Spot Markets,” Journal of Statistics & Management Systems, Vol. 13, pp. 389407 (2010).
  13. [13] Arshinder, K. A. and Deshmukh, S. G., “Supply Chain Coordination: Perspectives, Empirical Studies and Research Directions,” International Journal of Production Economics, Vol. 115, pp. 316335 (2008).
  14. [14] Taguchi, G., Introduction to Quality Engineering, Asian Productivity Organization, Tokyo, Japan (1986).
  15. [15] Liu, H. R., Chou, C. Y. and Chen, C. H., “MinimumLoss Design of X Charts for Correlated Data,” Journal of Loss Prevention in the Process Industries, Vol. 15, pp. 405411 (2002).
  16. [16] Chen, C. H. and Chou, C. Y., “Economic Design of Dodge-Romig LTPD Single Sampling Plans for Variables under Taguchi’s Quality Loss Function,” Total Quality Management, Vol. 12, pp. 511 (2001).
  17. [17] Chen, C. H. and Chou, C. Y., “Determining the Optimum Process Mean under the Bivariate Quality Characteristics,” International Journal of Advanced Manufacturing Technology, Vol. 21, pp. 313316 (2003).
  18. [18] Chen, C. H. and Chou, C. Y., “Tolerance Design for a Subsystem with Unequal Specification Limits Using Taguchi’s Quadratic Loss Function,” International Journal of Information and Management Sciences, Vol. 14, pp. 3136 (2003).
  19. [19] Chen, C. H. and Chou, C. Y., “Determining a OneSided Optimum Specification Limit under the Linear Quality Loss Function,” Quality & Quantity, Vol. 39, pp. 109117 (2005).

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