Analysis of Decision-Making Systems for Production Optimization Using the Fuzzy Logic-Based Mamdani Fuzzy Inference System Method: A MATLAB Application

Abstract

Production system uncertainties often arise due to fluctuations in stock levels and unpredictable demand patterns. These challenges can be addressed using fuzzy logic through the Mamdani fuzzy inference system method. The fuzzy inference system algorithm consists of several key steps: analyzing input and output variables, defining input-output relationships, performing fuzzification to establish fuzzy sets, constructing rule bases, and executing defuzzification. This study implements the algorithm using MATLAB version 8. The centroid method is utilized to calculate daily production volumes, ensuring precision in decision-making. For instance, on a Wednesday, with an input variable of demand set at 4,000 packages and a current stock inventory of 400 units, the system determines an optimal production volume of 4,280 packages. By employing the Mamdani fuzzy logic method, uncertainties in demand and inventory can be effectively managed, resulting in a more reliable and adaptive production system.