Optimizing Inventory Costs in Manufacturing Systems Using Trapezoidal and Pentagonal Fuzzy Numbers

Every manufacturing industry strives to always provide impeccable goods. Due to machine failures, labor issues, etc., this is practically unachievable in real‐world situations during the manufacturing run time. As a result, things of subpar quality are produced by the equipment systems. The inferior‐quality products are improved at a cost to make them better, and then they are prepared for sale. The nonlinear programming Lagrangian method is used to determine the best solution, which affects the average monthly cost. In the suggested model, the graded mean integration representation method is used to describe defuzzification while trapezoidal and pentagonal fuzzy numbers are used to calculate the optimal cost though there are different types of fuzzy numbers available that are used to test the optimality. The main aim of the paper is to compare the trapezoidal and pentagonal fuzzy numbers to test the optimal total cost. As a result, the trapezoidal fuzzy number gives an accurate result in all cases, while in the pentagonal fuzzy number, there is a slight deviation in the fuzzy case. So when we go with a higher‐order fuzzy number, the accuracy of the optimal total cost changes. Finally, a graphic comparison using MATLAB is carried out for the two fuzzy numbers and the best out of them is found.