چکیده:
Statistical process control and maintenance management are two key tools for controlling production processes. However, These two tools are traditionally separated (both in science and in business practice), their goals overlap a great deal. Their common goal is to achieve optimal product quality, little downtime and cost reduction by controlling variances in the process, that achieving these goals will increase the level of reliability of product quality. Using these two tools together can have better performance in terms of cost and quality for the organization; Therefore, in this research, an integrated model of statistical process control and maintenance management has been designed by considering the costs of two tools in Kish Wood Industries Company. The optimization criterion is to minimize the average total cost per unit time of these two systems. For this purpose, from MATLAB software and grid search approach to find the optimal values of sampling size (n), width of control limits (L), sampling interval (h) and number of sampling times during the planned maintenance (k) is used.The values of n, h, L and k for the laminating process were calculated as 5, 1, 2.9 and 30, respectively. The results of this optimization in the studied process show that the duration of the planned maintenance should be increased compared to the existing program, and this can be due to compensatory maintenance when the false alarm is out of control of the process.
خلاصه ماشینی:
Using these two tools in an integrated manner can provide better efficiency in terms of cost and quality for the organization; therefore, in this article, an integrated model of statistical process control and maintenance management has been designed, considering the costs of both tools in Kish Wood Industries Company.
Duncan (1956) presented the first economic model for determining three parameters of the x-bar control chart with the aim of minimizing the average cost during the time when the process is out of control [1].
Rahim (1994) and Ben-Daya (2000) investigated the integration of the x-bar control chart and maintenance management for a case where the machine failure process during the in-control period follows a general distribution with an increasing event rate [7, 8, and 9].
Based on the cost model of Alexander (1995), he investigated the economic behavior of the integrated model and addressed the optimal design of sample size, control limit width, sampling interval, and the number of sampling instances within the scheduled maintenance time interval that minimizes the total cost per hour.
(Refer to the page image) In practice, four parameters n (sample size), L (width of control limits), h (sampling time interval from the process), and k (number of sampling times during the scheduled maintenance interval) must be determined such that the average system cost per unit time is minimized.
The average cost and cycle time are calculated from the following relations: (Refer to the page image) The integrated model for control charts and maintenance and repair management applies to various types of control charts.
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