Optimization of fuzzy inventory lot-size with scrap and defective items under inspection policy

The paper aims to provide a technical framework for the enactment of procedures for the production management of large-scale industry. During production, the inspection process aids in the identification of high-quality and scrapped items. Furthermore, the deterioration of perishable products and machine breakdowns during production run time complicate the production. To handle such things, this paper incorporates the proportion of defective items and the proportion of scrap items with a uniform distribution to attain an optimal solution. The uncertainties in the data related to the proportion of scrap items, and the repair time are treated as pentagonal fuzzy numbers. An optimization model to minimize the total cost is stated with fuzzy parameter features. A graded mean differentiation method is used to defuzzify the fuzzy output. The major outcome acquired from this model is the optimal total cost, order quantity, and expected total profit of the production process. Additionally, a value-added process for degradable items has been used to develop an economic production quantity model. Finally, a sensitivity analysis has been conducted to show how the optimal values vary when the various cost parameters are varied.