Building a Cost Modeling System using Fuzzy Logic for Sugar Industry

Abstract

To understand the effects of cost factors on the overall production cost, the study's goal was todevelop a fuzzy logic-based cost modelling system for the sugar sector. The information is gathered fromsugar factories in Pakistan. Utilising a multistage fuzzy inference approach, the model is created. To analysethe cost of producing sugar, the model is verified using cost factors including the cost of raw materials, thecost of labour, and the cost of distribution. The main goal of the study was to ascertain how theseuncontrollable cost factors affected the price of producing sugar. The sub-cost components were used toanalyse the cost variables independently. For each cost variable, a different fuzzy inference technique wasused to interpret their response. Then a complete Mamdani inference system for manufacturing cost wascreated. The final inference system's input was derived from the results of the sub inference systems. Inorder to design the system to assess the effects of specified cost drivers on the production cost, a total ofthree input variables, one output variable, and twenty-seven if-then rules were established. The createdfuzzy logic-based system can assess the cost of producing sugar while taking uncertainty into consideration.As a result, the created system's offer of a cost estimating model that makes it easier to choose outcomesthat are cost-effective is a major contribution.