Reducing work in process (WIP) with fuzzy logic at job shop scheduling

The job shop is the most widely used production organization. The job shop production control system should schedule the incoming orders according to the capacity constraint of individual workstations or processes. One of the problems encountered at the job shop scheduling is minimum production size of machine, which is different from each other. Whereas 100 units order can be opened to some machine, 1000 units order can be opened another. This case increases WIP. In this study, a new approach was improved to reduce WIP. In this new approach, the parts, which materials are in stock and ordered very frequently are assigned to machine to reduce WIP. The new approach improved in this study is not applied at traditional job shop effectively. In this study, fuzzy logic is used to cope with this problem. Fuzzy logic determines which order assigned to the slack machine reviewing the minimum order size, materials size, load size of next machine, and order frequency. New approach was simulated at the job shop that has 15 machine and 50 orders. Simulation results show that new approach reduces WIP.