Title: Joint determination of optimum process mean, production run length and specification limits for a deteriorating process

Authors: Muneeb A. Akram, Muhammad F. Al-Salamah, Abdul-Wahid A. Saif, Mohammed A. Rahim

Addresses: Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia. ' Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia. ' Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia. ' Faculty of Business Administration, University of New Brunswick, 7 MacAulay Lane, Fredericton, NB, Canada

Abstract: Most of the recent work found in literature solved the problem of determining the optimum values of process parameters by considering one or jointly two parameters using separate models under different assumptions. The objective of this work is to develop a trine model that can be used for joint determination of three process parameters, namely: optimum process mean, production run length and specification limits, under mixed quality loss function for processes that are subject to deterioration over time. This paper will summarise the recent related literature and outlining the technical information required for this work. In this work, the problem will be tracked in two ways: by minimising the total loss and by maximising the net profit. For achieving that, we developed different models that can be used to determine optimum values for process parameters; the analysis leads to the development of the trine model. Numerical examples parallel to each model are presented to illustrate its use in determining the desired optimum parameter value. Sensitivity analysis for different process parameters are also presented to study their effects on the net profit in the view of satisfying the manufacturing requirements.

Keywords: process parameters; optimum process mean; production run length; specification limits; deteriorating processes; quality loss function; modelling.

DOI: 10.1504/IJQET.2011.039126

International Journal of Quality Engineering and Technology, 2011 Vol.2 No.2, pp.129 - 147

Available online: 18 Mar 2011 *

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