Development of PC-based Integrated Scheduling System with Demand Forecasting for PVC Plant
| Authors: | Park Sunwon, KAIST, Korea, Republic of
Kang Min-gu, KAIST, Korea, Republic of
Kang Sookil, KAIST, Korea, Republic of
Lee Ho-kyung, LG Chemical, Korea, Republic of |
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| Topic: | 5.2 Manufacturing Modelling for Management and Control |
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| Session: | Manufacturing Modelling, Management and Control |
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| Keywords: | scheduling, hybrid method, genetic algorithm, demand forecasting, safety inventory, PVC |
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Abstract
In this study, an integrated scheduling system with demand forecasting has been developed. The SARIMA (seasonal autoregressive integrated moving average) model is automated to forecast demand. In order to reduce cost and instability of production scheduling, a safety inventory determination model is added to forecasting model. A scheduling system based on the mathematical model and the efficient optimization approach has been proposed. The mathematical model has been proposed for scheduling of the entire process of a PVC (Poly Vinyl Chloride) plant, including production, inventory, packing and shipment. Additionally, a more efficient optimization approach has been studied. For validation purposes, two PVC plants with different characteristics were used.
