Development of realistic quality loss functions for industrial applications

Abdul-Baasit Shaibu , Byung Rae Cho

Journal of Systems Science and Systems Engineering ›› 2006, Vol. 15 ›› Issue (4) : 385 -398.

PDF
Journal of Systems Science and Systems Engineering ›› 2006, Vol. 15 ›› Issue (4) : 385 -398. DOI: 10.1007/s11518-006-6048-5
Article

Development of realistic quality loss functions for industrial applications

Author information +
History +
PDF

Abstract

A number of quality loss functions, most recently the Taguchi loss function, have been developed to quantify the loss due to the deviation of product performance from the desired target value. All these loss functions assume the same loss at the specified specification limits. In many real life industrial applications, however, the losses at the two different specifications limits are often not the same. Further, current loss functions assume a product should be reworked or scrapped if product performance falls outside the specification limits. It is a common practice in many industries to replace a defective item rather than spending resources to repair it, especially if considerable amount of time is required. To rectify these two potential problems, this paper proposes more realistic quality loss functions for proper applications to real-world industrial problems. This paper also carries out a comparison studies of all the loss functions it considers.

Keywords

Modified quadratic loss / type I exponential loss / type II exponential loss / expected loss / within-specification loss / out-of-specification loss

Cite this article

Download citation ▾
Abdul-Baasit Shaibu, Byung Rae Cho. Development of realistic quality loss functions for industrial applications. Journal of Systems Science and Systems Engineering, 2006, 15(4): 385-398 DOI:10.1007/s11518-006-6048-5

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Alexander S. M., Dillman M. A., Damodaran B.. Economic design of control charts using the Taguchi loss function. Computers & Industrial Engineering, 1995, 28(3): 671-679.

[2]

Al-Fawzan M. A., Rahim M. A.. Optimal control of a deteriorating process with a quadratic loss function. Quality and Reliability Engineering International, 2001, 17: 459-466.

[3]

Baker, T. B. (1986). Quality engineering by design: Taguchi’s philosophy. Quality Progress, pp. 32–42, December

[4]

Betes D. C.. Finding an optimal target value in relation to a fixed lower limit. Applied Statistics, 1962, 11(2): 202-210.

[5]

Bisgaard S., Hunter W. G., Pallesen L.. Economic selection of quality manufactured product. Technometrics, 1984, 26(1): 9-18.

[6]

Carlsson O.. Determining the most profitable process level for a production process under different sales conditions. Journal of Quality Technology, 1984, 16(1): 44-49.

[7]

Chan W. M., Ibrahim R. N.. Evaluating the Quality Level of a Product with Multiple Quality Characteristics. International Journal of Advanced Manufacturing Technology, 2004, 24: 738-742.

[8]

Chou C.-Y., Chen C.-H., Liu H.-R.. Economic-statistical design of $\bar X$ charts for non-normal data by considering quality loss. Journal of Applied Statistics, 2000, 27(8): 939-951.

[9]

Golhar D. Y.. Determination of the best mean contents for a canning problem. Journal of Quality Technology, 1987, 19(2): 82-84.

[10]

Golhar D. Y., Pollock S. M.. Determination of the optimal process mean and upper limit for a canning problem. Journal of Quality Technology, 1988, 20(3): 188-192.

[11]

Golhar D. Y., Pollock S. M.. Cost saving due to variance reduction in a canning problem. IIE Transactions, 1992, 24(1): 89-92.

[12]

Ho L. L., Quinino R.. Optimum mean location in a poor-capability process. Quality Engineering, 2003, 16(2): 257-263.

[13]

Hunter W. G., Kartha C. P.. Determining the most profitable target value for a production process. Journal of Quality Technology, 1977, 9(4): 176-181.

[14]

Kobayashi J., Arizono I., Takemoto Y.. Economic operation of $(\bar x,s)$ control chart indexed by Taguchi’s loss function. International Journal of Production Research, 2003, 41(6): 1115-1132.

[15]

Leon R. V., Wu C. F. J.. A theory of performance measure in parameter design. IIQP Research Report, 1989, Waterloo, Canada: University of Waterloo

[16]

Montergomery, D. C. (1995). Introduction to Statistical Quality Control. 2nd Edition. John Wiley

[17]

Phillips M. D., Cho B. R.. Modelling of optimal specification regions. Applied Mathematical Modelling, 2000, 24: 327-341.

[18]

Rahim M. A., Shaibu A.-B.. Economic selection of optimal target values. Process Control and Quality, 2000, 11(5): 369-381.

[19]

Schmidt R. L., Pfeifer P. E.. Economic selection of the mean and upper limit for a canning problem with limited capacity. Journal of Quality Technology, 1991, 23(4): 312-317.

[20]

Spiring, F. (1991). An Alternative to Taguchi’s Loss Function, ASQS Quality Congress Transactions — Milwaukee

[21]

Spiring F. A., Yeung A. S.. A general class of loss functions with industrial applications. Journal of Quality Technology, 1998, 30(2): 152-162.

[22]

Springer C. H.. A method for determining the most economic position of a process. Industrial Quality Control, 1951, 8(1): 36-39.

[23]

Taguchi G.. Online Quality Control during Production, 1981, Tokyo, Japan: Japanese Standards Association

[24]

Taguchi G.. Introduction to Quality Engineering: Designing Quality into Products and Processes, 1986, NY: Kraus, White Plains

[25]

Taguchi G., Elsayed E. A., Hsiang T.. Quality Engineering in Production Systems, 1989, New York, NY: Mc-Graw-Hill

[26]

Teeravaraprug J., Cho B. R.. Designing the optimal process target levels for multiple quality characteristics. International Journal of Production Research, 2002, 40(1): 37-54.

AI Summary AI Mindmap
PDF

132

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/