A Markovian approach to determining process means with dual quality characteristics

Mohammad T. Khasawneh , Shannon R. Bowling , Byung Rae Cho

Journal of Systems Science and Systems Engineering ›› 2008, Vol. 17 ›› Issue (1) : 66 -85.

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Journal of Systems Science and Systems Engineering ›› 2008, Vol. 17 ›› Issue (1) : 66 -85. DOI: 10.1007/s11518-008-5064-z
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A Markovian approach to determining process means with dual quality characteristics

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Abstract

This paper studies a production system where products are produced continuously and whose specification limits are specified for screening inspection. In this paper, we consider dual quality characteristics and different costs associated with each quality characteristic that falls below a lower specification limit or above an upper specification limit. Due to these different costs, the expected total profit will greatly depend on the process parameters, especially a process mean. This paper develops a Markovian-based model for determining the optimum process means with the consideration of dual quality characteristics in a single-stage system. The proposed model is then illustrated through a numerical example and sensitivity analysis is performed to validate the model. The results showed that the optimum process mean for both quality characteristics have a significant effect on the performance of the system. Since the literature survey shows that dealing with multi-quality characteristics is extremely limited, the proposed model, coupled with the Markovian approach, provides a unique contribution to this field.

Keywords

Single-stage production / optimum process mean / Markov chains / dual quality characteristics

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Mohammad T. Khasawneh, Shannon R. Bowling, Byung Rae Cho. A Markovian approach to determining process means with dual quality characteristics. Journal of Systems Science and Systems Engineering, 2008, 17(1): 66-85 DOI:10.1007/s11518-008-5064-z

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References

[1]

Al-Fawzan M.A., Rahim M.A.. Optimal control of deteriorating process with a quadratic loss function. Quality and Reliability Engineering-International, 2001, 17(6): 459-466.

[2]

Al-Sultan K.S.. An algorithm for the determination of the optimum target values for two machines in series with quality sampling plan. International Journal of Production Research, 1994, 32(1): 37-45.

[3]

Al-Sultan K.S., Pulak M.F.S.. Optimum target values for two machines in series with 100% inspection. European Journal of Operational Research, 2000, 120(1): 181-189.

[4]

Arcelus F.J., Banerjee P.K.. Selection of the most economical production plan in a tool-wear process. Technometrics, 1985, 27(4): 433-437.

[5]

Arcelus F.J., Rahim M.A.. Optimal process levels for the joint control of variables and attributes. European Journal of Operations Research, 1990, 45(2–3): 224-230.

[6]

Bettes D.C.. Finding an optimal target value in relation to a fixed lower limit and an arbitrary upper limit. Applied Statistics, 1962, 11: 202-21.

[7]

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

[8]

Boucher T.O., Jafari M.A.. The optimum target value for single filling operations with quality plans. Journal of Quality Technology, 1991, 23(1): 44-47.

[9]

Bowling S.R., Khasawneh M.T., Kaewkuekool S., Cho B.R.. A Markovian approach to determining optimum process target levels for a multi-stage serial production system. European Journal of Operational Research, 2004, 159(3): 636-650.

[10]

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.

[11]

Chen C.H.. Determining the optimum process mean for the-larger-the-better Weibull quality characteristic. International Journal of Applied Science and Engineering, 2003, 1(2): 172-176.

[12]

Chen C.H., Chou C.Y.. Determining the optimum process mean of a one-sided specification limit. International Journal of Advanced Manufacturing Technology, 2002, 20(6): 439-441.

[13]

Chen C.H., Chou C.Y.. Determining the optimum manufacturing target based on an asymmetric quality loss function. International Journal of Advanced Manufacturing Technology, 2003, 21(3): 193-195.

[14]

Chen C.H., Chou C.Y.. Determining the optimum process mean under bivariate quality characteristics. International Journal of Advanced Manufacturing Technology, 2003, 21(3): 313-316.

[15]

Chen C.H., Chou C.Y.. Determining the optimum process mean under a beta distribution. Journal of the Chinese Institute of Industrial Engineers, 2003, 18(3): 27-32.

[16]

Chen C.H., Chou C.Y., Huang K.W.. Determining the optimum process mean for a poor process. International Journal of Advanced Manufacturing Technology, 2002, 20(10): 754-757.

[17]

Chen S.L., Chung K.J.. Selection of the optimal precision level and target value for a production process: the lower-specification-limit case. IIE Transactions, 1996, 28(12): 979-985.

[18]

Cho B.R.. Optimum process target for two quality characteristics using regression analysis. Quality Engineering, 2002, 15(1): 37-47.

[19]

Cho B.R., Ferrell W.G., Kimbler D.L.. Development of the optimum product specification for an exponential-type quality characteristic. International Journal of Reliability, Quality, and Safety Engineering, 1996, 3(3): 243-256.

[20]

Cho, B.R., Kaewkuekool, S., Bowling, S.R. & Khasawneh, M.T. (2003). The optimum target value for a process based on a quadratic loss function. In: Proceedings of the Industrial Engineering Research Conference, Portland, Oregon, May, 2003

[21]

Cho B.R., Leonard M.S.. Identification and extensions of quasiconvex quality loss functions. International Journal of Reliability, Quality and Safety Engineering, 1997, 4(2): 191-204.

[22]

Das C.. Selection and evaluation of most profitable process targets for control of canning quality. Computers and Industrial Engineering, 1995, 28(2): 259-266.

[23]

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

[24]

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

[25]

Hong S.H., Elsayed E.A.. The optimal mean for processes with normally distributed measurement error. Journal of Quality Technology, 1999, 31(3): 338-344.

[26]

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.

[27]

Kim Y.J., Cho B.R., Philips M.D.. Determination of the optimum process mean with the consideration of variance reduction and process capability. Quality Engineering, 2000, 13(2): 251-260.

[28]

Lasdon L.S., Waren A.D.. GRG2 user’s guide. School of Business Administration, 1986, TX: University of Texas at Austin

[29]

Lee M.K., Hong S.H., Elsayed A.E.. The optimum target value under single and two-stage screenings. Journal of Quality Technology, 2001, 33(4): 506-514.

[30]

Liu W., Taghavachari M.. The target mean problem for an arbitrary quality characteristic distribution. International Journal of Production Research, 1997, 35(6): 1713-1727.

[31]

Nelson L.S.. Best target value for a production process. Journal of Quality Technology, 1978, 10(2): 88-89.

[32]

Nelson L.S.. Nomograph for setting process to minimize scrap cost. Journal of Quality Technology, 1979, 11: 48-49.

[33]

Pakkala T.P.M., Rahim M.A.. Determination of an optimal setting and production run using Taguchi loss function. International Journal of Reliability, Quality and Safety Engineering, 1999, 6(4): 335-346.

[34]

Phillips D.M., Cho B.R.. A nonlinear model for determining the most economical process mean under a Beta distribution. International Journal of Reliability, Quality and Safety Engineering, 2000, 7(1): 61-74.

[35]

Pollock S.M., Golhar D.. The canning problem revisited: the case of capacitated production and fixed demand. European Journal of Operations Research, 1998, 105(3): 475-482.

[36]

Rahim M.A., Al-Sultan K.S.. Joint determination of the target mean and variance of a process. Journal of Quality Maintenance Engineering, 2000, 6(3): 192-199.

[37]

Rahim M.A., Banerjee P.K.. Optimal production run for a process with random linear drift. Omega, 1988, 16(4): 347-351.

[38]

Rahim M.A., Bhadury J., Al-Sultan K.S.. Joint economic selection of target mean and variance. Engineering Optimization, 2002, 34(1): 1-14.

[39]

Rahim M.A., Lashkari R.S.. Optimal decision rules for determining the length of the production run. Computers and Industrial Engineering, 1985, 9(2): 195-202.

[40]

Rahim M.A., Raouf A.. Optimal production run for a process having multilevel tool wear. International Journal of Systems Science, 1988, 19(1): 139-149.

[41]

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

[42]

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.

[43]

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

[44]

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

[45]

Teeravaraprug J., Cho B.R., Kennedy W.J.. Designing the most cost-effective process target using regression analysis: a case study. Process Control and Quality, 2000, 11(6): 469-477.

[46]

Tuffaha F., Rahim M.A.. An integrated model for determining the optimal initial settings of the process mean and the production run assuming quadratic loss functions. International Journal of Production Research, 2004, 42(16): 3281-3300.

[47]

Usher J.S., Alexander S.M., Duggines D.C.. The filling problem revisited. Quality Engineering, 1996, 9(1): 35-44.

[48]

Wen D., Mergen A.E.. Running a process with poor capability. Quality Engineering, 1999, 11(4): 505-509.

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