A production management system contains many qualitative descriptions and imprecise natures. The conventional crisp and/or stochastic model constructed in the computer integrated production management system (CIPMS) cannot describe these qualitative descriptions and imprecise natures. Therefore, it is difficult to mimic the way managers think, which is conceptual and comprehensive, and to absorb uncertainties such as order cancelled, unstable material supply etc, in a production system. This frequently accounts for why the CIPMS yields a poor performance. This paper presents a fuzzy approach to the CIPMS in order to model qualitative descriptions and imprecise natures. This approach includes two stages. In stage one, a management strategy can be determined in a way that is similar to the way humans think, in which ideas, pictures, images and value systems are formed. In stage two, a fuzzy linear programming model is developed to absorb these imprecise natures in a production system. In doing this, CIPMS can adapt a variety of non-crisp problems in an actual system, thereby improving the performance of CIPMS.