Optimization of process parameters based on fuzzy similarity relation

In chemical production, the managers generally set variable production indices aiming at the market demanding, this demands the technicians select the relative optimal technical parameters to reach the new production indices, In general, the technicians find new parameters mainly by consulting the past operating record and their experience, which is excessively subjective, thus, the goal of this paper is that normalize the processing of parameters selection. The method we developed here is as follow: Firstly, we build a production database based on SQL platform, which record each group technical parameters and its corresponding production effect, then, by calculating the fuzzy similarity relation between each production effect and production indices, find the production effect which is most approaching to production index and, make its corresponding technical parameters our standard parameters. This method is effective and widely useful for other production systems.