Development of A Fuzzy Logic-Based Cost Modeling System for Sugar Industry

Abstract

The objective of the study was to create a fuzzy logic-based cost modelling system for the sugar industry in order to comprehend the impacts of sugar cost determinants on total cost. The designed system takes into account variables such as fluctuating cane prices, cane weight, distribution distances, and crushing cessation. The data is collected from the cost statements of various Pakistani sugar refineries. The primary research objective was to determine the effects of the unpredictability of various cost variables on the ultimate price of sugar. The cost determinants were deemed input variables, while the cost of sugar production was considered an output variable. The cost variables were categorised as follows: cost of basic materials, cost of distribution, cost of labour, cost of operations, factory overheads, and crushing cessation (losses). The Mamdani Fuzzy Inference system was used to analyse the data. To develop the system, 729 fuzzy rules and three levels of fuzzy sets were created. The developed fuzzy logic-based system is able to evaluate the sugar cost structure and take uncertainty factors into account. Consequently, a significant contribution of the developed system is the provision of heuristic principles that facilitate the selection of cost-effective outcomes.