Abstract: An optimized producing environment is a key issue in bio-chemical industry production. Due to the complex mechanism of bio-chemical production, understanding the favorable environment is very difficult. On the other hand, a great amount of data has been accumulated through industry production over years. It is possible to find out valuable rules that may contribute to the improvement of production efficiency and quality through data mining and association rule mining. We proposed the concept of association rule mining with fixed decision items. The corresponding mining algorithm was introduced and the application was illustrated. The algorithm was based on the traditional Aprori and, due to an advanced pruning strategy was adopted, it showed much higher efficiency.