REFERENCES
- [1] Wu, C. C. and Tang, G. R., “Tol er ance De sign for Prod ucts with Asym met ric Qual ity Losses,” In ter national Jour nal of Pro duc tion Re search, Vol. 39, pp. 2529- 2541 (1998).
- [2] Li, M.-H. C., “Op ti mal Set ting of the Pro cess Mean for Asym met ri cal Qua dratic Qual ity Loss Func tion,” Pro - ceed ings of the Chi nese In sti tute of In dus trial En gineers Con fer ence, pp. 415-419 (1997).
- [3] Li, M.-H. C., “Op ti mal Set ting of the Pro cess Mean for an Asym met ri cal Trun cated Loss Func tion,” Pro ceedings of the Chi nese In sti tute of In dus trial En gi neers Con fer ence, pp. 532-537 (1998).
- [4] Li, M.-H. C., “Qual ity Loss Func tion Based Man u facturing Pro cess Set ting Models for Un bal anced Tol erance De sign,” In ter na tional Jour nal of Ad vanced Ma - n u fac turing Tech nol ogy, Vol. 16, pp. 39-45 (2000).
- [5] Li, M.-H. C., “Un bal anced Tol er ance De sign and Ma - nufacturing Set ting with Asym met ri cal Lin ear Loss Fun c tion,” In ter na tional Jour nal of Ad vanced Man ufac turing Tech nol ogy, Vol. 20, pp. 334-340 (2002).
- [6] Li, M.-H. C., “Op ti mal Pro cess Set ting for Un bal anced Tol er ance De sign with Lin ear Loss Func tion,” Jour nal of the Chi nese In sti tute of In dus trial En gi neers, Vol. 19, pp. 17-22 (2002).
- [7] Li, M.-H. C. and Chirng, H.-S., “Op ti mal Set ting of the Pro cess Mean for Asym met ri cal Lin ear Qual ity Loss Func tion,” 1999 Con fer ence on Tech nol ogy and Appli ca tions of Qual ity Man age ment for Twenty-first Cen tury, pp. 2-6~2-11 (1999).
- [8] Li, M.-H. C. and Cherng, H.-S., “Un bal anced Tol erance De sign with Asym met ric Trun cated Lin ear Loss Func tion,” The 14th Asia Qual ity Sym po sium, pp. 162- 165 (2000).
- [9] Maghsoodloo, S. and Li, M.-H. C., “Op ti mal Asymmet ri cal Tol er ance De sign,” IIE Trans ac tions, Vol. 32, pp. 1127-1137 (2000).
- [10] Phil lips, M. D. and Cho, B.-R., “A Non lin ear Model for De ter mining the Most Eco nomic Pro cess Mean Un der a Beta Dis tri bu tion,” In ter na tional Jour nal of Re li abil ity, Qual ity and Safety En gi neering, Vol. 7, pp. 61-74 (2000).
- [11] Li, M.-H. C. and Chou, C.-Y., “Tar get Se lec tion for an In di rectly Mea sur able Qual ity Char ac ter is tic in Un balanced Tol er ance De sign,” In ter na tional Jour nal of Advanced Man u fac turing Tech nol ogy, Vol. 17, pp. 516- 522 (2001).
- [12] Li, M.-H. C. and Wu, F.-W., “A Gen eral Model of Un - bal anced Tol er ance De sign and Man u fac tur ing Set ting with Asym met ric Qua dratic Loss Func tion,” Pro ceeding of Con fer ence of the Chi nese So ci ety for Qual ity, pp. 403-409 (2001).
- [13] Li, M.-H. C. and Wu, F.-W., “A Gen eral Model of Man u fac turing Set ting with Asym met ric Lin ear Loss Func tion,” The 38th An nual Con fer ence of Chi nese So - ci ety for Qual ity and The 6 th Na tional Qual ity Manage ment Sym po sium, pp. 1137-1143 (2002).
- [14] Lee, M. K., Kim, S. B., Kwon, H. M., and Hong, S. H., “Eco nomic Se lec tion of Mean Value for a Fill ing Pro - cess un der Qua dratic Qual ity Loss,” In ter na tional Journal of Re li abil ity, Qual ity and Safety En gi neering, Vol. 11, pp. 81-90 (2004).
- [15] Hunter, W. G., and Kartha, C. P., “De ter mining the Most Prof it able Tar get Value for a Pro duc tion Process,” Jour nal of Qual ity Tech nol ogy, Vol. 9, pp. 176-181 (1977).
- [16] Carlsson, O., “De ter mining the Most Prof it able Process Level for a Pro duc tion Pro cess un der Dif fer ent Sales Con di tions,“ Jour nal of Qual ity Tech nol ogy, Vol. 16, pp. 44-49 (1984).
- [17] Bisgaard, S., Hunter, W. G., and Pallesen, L., “Economic Se lec tion of Qual ity of Man u fac tured Prod uct,” Technometrics, Vol. 26, pp. 9-18 (1984).
- [18] Golhar, D. Y., “De ter mi na tion of the Best Mean Con - tents for a ‘Canning Prob lem’,” Jour nal of Qual ity Tech nol ogy, Vol. 19, pp. 82-84 (1987).
- [19] Golhar, D. Y. “Com pu ta tion of the Op ti mal Pro cess Mean and the Up per Limit for a Can ning Prob lem,” Jour nal of Qual ity Tech nol ogy, Vol. 20, pp. 193-195 (1988).
- [20] Golhar, D. Y. and Pollock, S. M., “De ter mi na tion of the Op ti mal Pro cess Mean and the Up per Limit of the Can ning Prob lem,” Jour nal of Qual ity Tech nol ogy, Vol. 20, pp. 188-192 (1988).
- [21] Golhar, D. Y. and Pollock, S. M., “Cost Sav ings Due to Vari ance Re duc tion in a Can ning Pro cess,” IIE Trans - ac tions, Vol. 24, pp. 88-92 (1992).
- [22] Misiorek, V. I. and Barrnett, N. S., “Mean Se lec tion for Fill ing Pro cesses un der Weights and Mea sures Require ments,” Jour nal of Qual ity Tech nol ogy, Vol. 32, pp. 111-121 (2000).
- [23] Lee, M. K., Hong, S. H., Kwon, H. M., and Kim, S. B., “Op ti mum Pro cess Mean and Screen ing Lim its for a Pro duc tion Pro cess with Three-class Screen ing,” In - ter na tional Jour nal of Re li abil ity, Qual ity and Safety En gi neering, Vol. 7, pp. 179-190 (2000).
- [24] Lee, M. K., Hong, S. H., and Elsayed, E. A., “The Op - ti mum Tar get Value un der Sin gle and Two-stage Scre - en ings,” Jour nal of Qual ity Tech nol ogy, Vol. 33, pp. 506-514 (2001).
- [25] Taguchi, G., In tro duc tion to Qual ity En gi neering. Asi - an Pro duc tiv ity Or ga ni za tion, To kyo, Ja pan (1986).