Abstract
Most research studies on the economic production quantity (EPQ) model considered that produced items are of perfect quality. On the other hand, real production systems have some product defects. Considering the imperfect items makes the inventory model more complex, and more difficult to solve analytically rather than it is time consuming. Therefore, an efficient approach like D-optimal response surface methodology (RSM) is required since heterogeneous combination of data can be modeled to generate response surfaces and obtain optimum decision parameters values. This paper solves the EPQ model with sales return, rework, shortage and scrap by RSM optimization technique in order to optimize the long run average cost function. ANOVA analysis of data obtained from the total cost RSM quadratic model has shown that the Model is significant according to F, “Prob > F” and p-values.
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