Optimum Process Mean Setting for Product with Rework Process Under second order autocorrelation

Vispute S.¹ , Singh J. R.²

Section:Research Paper, Product Type: Isroset-Journal
Vol.1 , Issue.3 , pp.1-12, Jun-2014

Online published on Oct 20, 2014

Copyright © Vispute S. , Singh J. R. . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
In Paper the effects of second order autocorrelation on the determination of the optimum process mean in statistical process control. It directly affects the process defective rate, production cost, scrap cost, and rework cost. Lee et al.(2000) presented a filling problem for determining the optimum process mean and screening limits. They considered three grades of product, assumed a normal quality characteristic, and adopted the piecewise linear profit function for measuring the profit per item. However, they have not included the scrap cost and the perfect rework process in their model. In this chapter, we further propose a modified Lee et al.’s model with rework process for determining the optimum process mean under second order autocorrelation when the roots are (i) real and distinct (ii) real and equal and (iii) complex conjugate. Both perfect rework and imperfect rework processes for the product are considered in the model. Negative autocorrelation and positive autocorrelation are seriously affected on optimum mean and expected profit.

Key-Words / Index Term :
Optimum Process Mean, Autocorrelation, Scrap Cost Nomenclature

References :
[1]. Al-Sultan KS (1994) An algorithm for the determination of the optimum target values for two machines in series with quality sampling plans. Int. J. Prod. Res. 32(1), 37-45.
[2]. Al-Sultan, K. S. and Al-Fawzan, M. A., (1997). “Variance Reduction in a Process with Random Linear Drift,” International Journal of Production Research, Vol. 35, pp. 1523-1533 s
[3]. Al-Sultan, K. S. and Pulak, M. F. S., (1997). “Process Improvement by Variance Reduction for a Single Filling Operation with Rectifying Inspection,” Production Planning & Control, Vol. 8, pp. 431-436
[4]. Arcelus, F. J. and Rahim, M. A., (1990). “Optimal Process Levels for the Joint Control of Variables and Attributes,” European Journal of Operational Research, Vol. 45, pp. 224-230
[5]. Bisgaard, S., Hunter, W. G. and Pallesen, L., (1984). “Economic Selection of Quality of Manufactured Product,” Technometrics, Vol. 26, pp. 9-18
[6]. Boucher TO and Jafari MA (1991) The optimum target value for single filling operations with quality plans. J. Quality Tech. 23(1), 44-47.
[7]. Carlsson O (1984) Determining the most profitable process level for a production process under different sales conditions. J. Quality Tech. 16, 40-49.
[8]. Carlsson O (1989) Economic selection of a process level under acceptance sampling variables. Engng. Costs & Prod. Econ. 16, 69-78.
[9]. Duffuaa, S. O. and Siddiqi, A.W., (2002). “Integrated Process Targeting and Product Uniformity Model for Three- Class Screening,” International Journal of Reliability, Quality and Safety Engineering, Vol. 9, pp. 261-274
[10]. Golhar, D. Y. and Pollock, S. M., (1988). “Determination of the Optimal Process Mean and the Upper Limit of the Canning Problem,” Journal of Quality Technology, Vol. 20, pp. 188-192
[11]. Golhar, D. Y. and Pollock, S. M., (1992). “Cost Savings Due toVariance Reduction in a Canning Process,” IIE Transactions,Vol. 24, pp. 88-92
[12]. Golhar, D. Y., (1987). “Determination of the Best Mean Contents for a ‘Canning Problem’,” Journal of Quality Technology, Vol. 19, pp. 82-84
[13]. Golhar, D. Y., (1988). “Computation of the Optimal Process Mean and the Upper Limit for a Canning Problem,” Journal of Quality Technology, Vol. 20, pp. 193-195
[14]. Hunter WG and Kartha CP (1977) Determining the most profitable target value for a production process. J. Qual. Tech. 9(4), 176-181.
[15]. Lee, M. K. and Jang, J. S., (1997). “The Optimum Target Values for a Production Process with Three-Class Screening,” International Journal of Production Economics, Vol. 49, pp. 91-99
[16]. Li, M.-H. C. and Chirng, H.-S., (1999). “Optimal Setting of the Process Mean for Asymmetrical Linear Quality Loss Function,” 1999 Conference on Technology and Applications of Quality Management for Twenty-first Century, pp. 6-11
[17]. Li, M.-H. C. and Chou, C.-Y., (2001). “Target Selection for an Indirectly Measurable Quality Characteristic in Unbalanced Tolerance Design,” International Journal of Advanced Manufacturing Technology, Vol. 17, pp. 516-522.
[18]. Li, M.-H. C. and Wu, F.-W., (2002). “A General Model of Manufacturing Setting with Asymmetric Linear Loss Function,” The 38th Annual Conference of Chinese Society for Quality, pp. 1137-1143
[19]. Li, M.-H. C. andWu, F.-W., (2001). “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. 403-409
[20]. Li, M.-H. C., (1997). “Optimal Setting of the Process Mean for Asymmetrical Quadratic Quality Loss Function,” Proceedings of the Chinese Institute of Industrial Engineers Conference, pp. 415-419
[21]. Li, M.-H. C., (2002). “Optimal Process Setting for Unbalanced Tolerance Design with Linear Loss Function,” Journal of the Chinese Institute of Industrial Engineers, Vol. 19, pp. 17-22.
[22]. Li, M.-H.C. and Cherng, H.-S., (2000). “Unbalanced Tolerance Design with Asymmetric Truncated Linear LossFunction,” The 14th Asia Quality Symposium, pp. 162-165
[23]. Maghsoodloo, S. and Li, M.-H. C., (2000). “Optimal Asymmetrical Tolerance Design,” IIE Transactions, Vol. 32, pp. 1127-1137.
[24]. Misiorek, V. I. and Barrnett, N. S., (2000). “Mean Selection for Filling Processes underWeights and Measures Requirements,” Journal of Quality Technology, Vol. 32, pp. 111-121
[25]. Pulak and Sultan(1996). “The Optimum Targeting for a Single Filling Operation with Rectifying Inspection” Omega, Int. J. Mgmt Sci. Vol. 24, No. 6, pp. 727-733, 1996.
[26]. Pulak, M. F. S. and Al-Sultan, K. S., (1996). “The Optimum Targeting for a Single Filling Operation with Rectifying Inspection,” Omega, Vol. 24, pp. 727-733
[27]. Rahim, M. A. and Banerjee, P. K., (1988). “Optimal Production Run for a Process with Random Linear Drift,” Omega, Vol. 16, pp. 347-351
[28]. Springer, C. H., (1951). “A Method of Determining the Most Economic Position of a Process Mean,” Industrial Quality Control, Vol. 8, pp. 36-39
[29]. Wu, C. C. and Tang, G. R., (1998). “Tolerance Design for Products with Asymmetric Quality Losses,” International Journal of Production Research, Vol. 39, pp. 2529-2541