Safety Stock Identification in Beverage Soft Drink Industries by Using Dynamic Fuzzy Logic (Journal of University of Babylon for Engineering Sciences, 2018)
The optimization of Safety stock considered an important element in the supply chain of beverage industries. In this paper, dynamic fuzzy logic was used as an advanced approach to identify the safety stock level in the beverage industries with the objective of minimizing total cost and meet with customer requirements. The problem of shortage occurred in these organizations due to poor inventory strategies which considered negative storage driver, so provide advanced safety stock identification strategy will lead to overcome this problem especially for organizations work under make to stock policy. Three main steps are included here to identify safety stock level firstly, building of fuzzy sets for each variable, secondly, identifying max values to represent universe of discourse of variables and identify monthly input values of the variables, finally, execution of the proposed model in fuzzy logic tool embedded in Matlab software. In order to demonstrate the validity of proposed model, real data soft drink supply chain problem was presented. Reduction in stock-out of drinks about 99.9% was obtained by applying this model where the shortage was decreased from (53,423 package) to only (154 package). The obtained results of the research demonstrated the need to adopt advanced methodologies such as soft computing to identify safety stock level.