Intelligent production planning by post-model analysis

Abstract

Aggregate Production Planning (APP) is concerned with the determination of production and workforce levels to meet fluctuating demand requirement. The traditional quantitative models to solve for the APP use only quantitative factors-at most quantified surrogates. However, most real APP problem needs to consider the important qualitative factors such as morale and goodwill explicitly. It is no doubt that the Aggregate Production Planning model deviates from the original problem if such qualitative factors are not taken into account appropriately. In this research, we seek to obtain the best solution which considers both quantitative factors and qualitative factors. For this purpose, the Post-Model Analysis(PMA) approach is adopted to support the trade-offs between the quantitative factors and qualitative factors. To do this the opportunity costs of qualitative goals are computed. The qualitative goals are organized in rule based knowledge and the expert system plays the role of evaluation and improvement of qualitative goals. To implement our approach, a prototype expert system, named IPPS(Intelligent Production Planning System), is developed.