This paper seeks to address the production control problem of a failure‐prone manufacturing system producing a random fraction of defective items.
A fluid model with perfectly mixed good and defective parts has been proposed. This approach combines the descriptive capacities of continuous/discrete event simulation models with analytical models, experimental design, and regression analysis. The main objective of the paper is to extend the Bielecki and Kumar theory, appearing under the title “Optimality of zero‐inventory policies for unreliable manufacturing systems”, under which the machine considered produced only good quality items, to the case where the items produced are systematically a mixture of good as well as defective items.
The paper first shows that for constant demand rates and exponential failure and repair time distributions of the machine, the Bielecki‐Kumar theory, adequately revisited, provides new and coherent results. For the more complex situation where the machine exhibits non‐exponential failure and repair time distributions, a simulation‐based approach is then considered. The usefulness of the proposed models is illustrated through numerical examples and sensitivity analysis.
Although the decisions taken in response to demands for productivity have a direct impact on product quality, management quality and production management have been traditionally treated as independent research fields. In response to this need, this paper is considered as a preliminary work in the intersection between quality control and production control issues.
Mhada, F., Hajji, A., Malhamé, R., Gharbi, A. and Pellerin, R. (2011), "Production control of unreliable manufacturing systems producing defective items", Journal of Quality in Maintenance Engineering, Vol. 17 No. 3, pp. 238-253. https://doi.org/10.1108/13552511111157362
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