DEVELOPMENT OF FUZZY LOGIC APPROACH TO OPTIMIZE SAFETY STOCK LEVEL IN DETERIORATED PRODUCTS/A SUPPLY CHAIN DAIRY INDUSTRIES CASE STUDY

Abstract

In today's complex environment, a high responding ability represents a core for each organization to survive in a competitive environment. To grip your position in intense competition market, the organization must design high efficiency inventory system that has the ability to respond to changes in demand and at the same time reduce holding cost of accommodation to the lowest possible value by controlling inventory drivers such as safety stock level (SS). The traditional approaches of safety stock are limited to deal with dynamic behavior of market. Advanced approaches based on soft computing allow the dynamic updating of SS level. In this paper, a highly advanced dynamic fuzzy logic (DFL) has been suggested as an innovation step to identify safety stock level in dairy industries with objective of minimizing total cost and meet with customer requirements. The proposed approach consists of three main steps firstly, identifying demand uncertainty conditions by applying fuzzy logic steps embedded by identifying dynamic (N) factor which represents the increasing level in demand in period time. Secondly, identifying of raw material availability conditions by applying fuzzy logic steps, and finally, identification of inventory on hand conditions by applying fuzzy logic steps. It is necessary to identify the level of SS dynamically in fuzzy logic as an output embedded with identifying of period specification concept which describes states of demand in a specific period in which the demand is high, medium, or low which leads to identify maximum values of universe of discourse of output (safety stock). Here Matlab program was used. The provided solution demonstrates the proposed model validity. There has been a significant reduction in safety stock level ranging from (7-98)% depending on product type and period specification with a reduction also in holding cost, while keeping the requirements fulfillment of customers demand