신경망을 이용한 금형공장용 일정계획 시스템에 관한 연구

A Study on Scheduling System for Mold Factory Using Neural Network

This paper deals with constructing a scheduling system for a mold manufacturing factory. The scheduling system is composed of 4 submodules such as pre-processor, neural network training, neural networks and simulation. Pre-processor analyzes the condition of workshop and generates input data to neural networks. Network training module is performed by using the condition of workshop, performance measures, and dispatching rules. Neural networks module presents the most optimized dispatching rule, based on previous training data according to the current condition of workshop. Simulation module predicts the earliest completion date of a mold by forward scheduling with the presented dispatching rules, and suggests a possible issue date of a material by backward tracking. The system developed shows a great potential when applied in real mold factory for automotive parts.