Journal of Applied Science and Engineering

Published by Tamkang University Press

1.30

Impact Factor

2.10

CiteScore

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

1Department of Industrial Management, Southern Taiwan University of Technology Yungkang, Taiwan 710, R.O.C.


 

Received: September 16, 2004
Accepted: April 27, 2005
Publication Date: December 1, 2005

Download Citation: ||https://doi.org/10.6180/jase.2005.8.4.07  


ABSTRACT


This article presents the design of integrating Dodge-Romig average outgoing quality limit (AOQL) single sampling plans (SSP) by variables and specification limits. By solving the modified Kapur and Wang’s model, we not only have the economic specification limits, but also obtain the optimal inspection policy of Dodge-Romig AOQL SSP by variables.


Keywords: Dodge-Romig Table, Average Total Inspection (ATI), Average Outgoing Quality Limit (AOQL), Specification Limits, Quadratic Loss Function


REFERENCES


  1. [1] Tagaras, G., “Economic Acceptance Sampling by Variables with Quadratic Quality Costs,” IIE Transactions, Vol. 26, pp. 2935 (1994).
  2. [2] Sower, V. E., Motwani, J., and Savoie, J M., “Are Acceptance Sampling and SPC Complementary or Incompatible ?,” Quality Progress, pp. 8589 (1993).
  3. [3] Dodge, H. F. and Romig, H. G., Sampling Inspection Tables, John Wiley, New York, NY, U.S.A. (1959).
  4. [4] Montgomery, D. C., Introduction To Statistical Quality Control, John Wiley, New York, NY, U.S.A. pp. 623624 (1991).
  5. [5] Klufa, J., “Acceptance Sampling by Variables When the Remainder of Rejected Lots Is Inspected,” Statistical Papers, Vol. 35, pp. 337349 (1994).
  6. [6] Klufa, J., “Dodge-Romig AOQL Single Sampling Plans for Inspection by Variables,” Statistical Papers, Vol. 38, pp. 111119 (1997).
  7. [7] Taguchi, G., Introduction To Quality Engineering, Tokyo, Asian Productivity Organization (1986).
  8. [8] Wu, C. C. and Tang, G. R., “Tolerance Design for Products with Asymmetric Quality Losses,” International Journal of Production Research, Vol. 36, pp. 2529 2541 (1998).
  9. [9] Li, M.-H. C., “Optimal Setting of the Process Mean for Asymmetrical Quadratic Quality Loss Function,” Proceedings of the Chinese Institute of Industrial Engineers Conference, pp. 415419 (1997).
  10. [10] Li, M.-H. C., “Optimal Setting of the Process Mean for an Asymmetrical Truncated Loss Function,” Proceedings of the Chinese Institute of Industrial Engineers Conference, pp. 532537 (1998).
  11. [11] Li, M.-H. C., “Quality Loss Function Based Manufacturing Process Setting Models for Unbalanced Tolerance Design,” International Journal of Advanced Manufacturing Technology, Vol. 16, pp. 39 45 (2000).
  12. [12] Maghsoodloo, S. and Li, M.-H. C., “Optimal Asymmetrical Tolerance Design,” IIE Transactions, Vol. 32, pp. 11271137 (2000).
  13. [13] Phillips, M. D. and Cho, B.-R., “A Nonlinear Model for Determining the Most Economic Process Mean Under a Beta Distribution,” International Journal of Reliability, Quality and Safety Engineering, Vol. 7, pp. 6174 (2000).
  14. [14] Li, M.-H. C. and Chou, C.-Y., “Target Selection for an Indirectly Measurable Quality Characteristic in Unbalanced Tolerance Design,” International Journal of Advanced Manufacturing Technology, Vol. 17, pp. 516 522 (2001).
  15. [15] Li, M.-H. C. and Wu, F.-W., “A General Model of Unbalanced Tolerance Design and Manufacturing Setting with Asymmetric Quadratic Loss Function,” Proceeding of Conference of the Chinese Society for Quality, pp. 403409 (2001).
  16. [16] Duffuaa, S. O. and Siddiqui, A. W., “Integrated Process Targeting and Product Uniformity Model for Threeclass Screening,” International Journal of Reliability, Quality and Safety Engineering, Vol. 9, pp. 261274 (2002).
  17. [17] Rahim, M. A. and Tuffaha, F., “Integrated Model for Determining the Optimal Initial Setting of the Process Mean and the Optimal Production Run Assuming Quadratic Loss Functions,” International Journal of Production Research, Vol. 42, pp. 3281 3300 (2004).
  18. [18] Kapur, K. C. and Wang, C. J., “Economic Design of Specifications Based on Taguchi’s Concept of Quality Loss Function,” Quality: Design, Planning, and Control, edited by DeVor, R. E. and Kapoor, S. G., The Winter Annual Meeting of the American Society of Mechanical Engineers, Boston, MA, U.S.A. pp. 2336 (1987).
  19. [19] Kapur, K. C., “An Approach for Development of Specifications for Quality Improvement,” Quality Engineering, Vol. 1, pp. 6377 (1988).
  20. [20] Kapur, K. C. and Cho, B.-R., “Economic Design and Development of Specifications,” Quality Engieering, Vol. 6, pp. 401417 (1994).
  21. [21] Kapur. K. C. and Cho, B.-R., “Economic Design of the Specification Region for Multiple Quality Characteristics,” IIE Transactions, Vol. 28, pp. 237248 (1996).
  22. [22] Chen, C.-H. and Chou, C.-Y., “Applying Quality Loss Function in the Design of Economic Specification Limits for Triangular Distribution,” Asia Pacific Management Review, Vol. 8, pp. 112 (2003).
  23. [23] Chen, C.-H. and Chou, C.-Y., “Economic Specification Limits Under the Inspection Error,” Journal of The Chinese Institute of Industrial Engineers, Vol. 20, pp. 2732 (2003).
  24. [24] Chen, C.-H., “Economic Design of Dodge-Romig Sampling Plans Under Taguchi’s Quality Loss Function,” Economic Quality Control, Vol. 19, pp. 1924 (1999).
  25. [25] 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).