Implementation of Fuzzy Inference System for Production Planning Optimisation

Activities in manufacturing become uncertain and complex as there is always ambiguity in different states due to their diversity. In other words, the uncertainty can make the operations in the manufacturing companies become finite and result in unnecessary waste of resources in terms of money, labour or time. Therefore, production planning are essential activities to accurately predict production in the manufacturing sector. In the context of such factors, the purpose of this research is to introduce the Fuzzy Inference System (FIS) as an effective method that can assist in determining an optimal result to production variable. The fuzzy variables of customer demand, production and inventory are used to practice the theory, synthesising the activities in manufacturing in order to attain an effective and efficient operation in the industry. However, assumptions have been made that capacity of resources, machines and warehouse are not considered in this study. The finding of production data show the comparison performance between actual production and FIS Tsukamoto production, where FIS Tsukamoto production show a stable graph compared to actual production. Moreover, total production for FIS Tsukamoto is less than actual production. In general, FIS Tsukamoto is a simple method that can help to determine the optimal and appropriate quantity of manufactured goods to be handled within the operation by using the variables in the form of fuzzy numbers.