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 to develop a fuzzy logic-based cost modelling system for the sugar sector. The information is gathered from sugar factories in Pakistan. Utilising a multistage fuzzy inference approach, the model is created. To analyse the cost of producing sugar, the model is verified using cost factors including the cost of raw materials, the cost of labour, and the cost of distribution. The main goal of the study was to ascertain how these uncontrollable cost factors affected the price of producing sugar. The sub-cost components were used to analyse the cost variables independently. For each cost variable, a different fuzzy inference technique was used to interpret their response. Then a complete Mamdani inference system for manufacturing cost was created. The final inference system's input was derived from the results of the sub inference systems. In order to design the system to assess the effects of specified cost drivers on the production cost, a total of three input variables, one output variable, and twenty-seven if-then rules were established. The created fuzzy 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 outcomes that are cost-effective is a major contribution.