Flexibility is a key concept in the management of modern manufacturing systems. The principal motivation is to achieve rapid response to manager’s demands by improving the efficiency of a job-shop while retaining its flexibility. To achieve this goal, the term flexible manufacturing system (FMS) is defined. FMS is an integrated computer controlled complex of automated material handling devices and numerically controlled machine tools that can process medium-sized volumes of a variety of part types. Flexible manufacturing systems have many potential advantages including high flexibility and high machine utilization rate.
As scheduling is the core of this control system, it plays a decisive role in achieving a goal. FMS scheduling problems are more difficult than those of conventional production systems because of a number of reasons such as machine setup times, part routing and operations scheduling. Flexible manufacturing system scheduling problems are very difficult, so mathematical modeling methods need to be improved to solve them.
Pak Myong Chol, a researcher at the Robotics Institute, designed a scheduler based on a self-adaptive genetic algorithm and obtained the optimal solution for the job-shop schedule. Then, he constructed a flexible production simulation system with the scheduling module and Flexsim and conducted a simulation based on the optimized part scheduling.
The simulation results verified that it is possible to reduce the total machining completion time, increase machine utilization and realize process optimization.
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