Optimize transition stages of the integrated SPC/EPC process using improved ant colony algorithm

In many varieties and small batch mode, the unqualified products often take place in the transition stages, especial the startup procedure. So transition stages are the important section to influence the product quality. Aiming at the limit of existing studies and combining with actual process regulation during the transition periods, a flexible model is developed to determine optimal adjustment strategy for transition periods. But the model is very complex and nonlinear. We adopt improved ant colony algorithm to deal with the above model under the advanced machine choose rule: After all ants crawled, this algorithm could adjust pheromone aiming at whether it got into part convergence, this could help algorithm to get best solution faster. At the same time we give an operational flow to adjust the transition process in light of the model. The flow is divided into four stages: initialization, operation, adjustment, and completion. In the end, simulation experiments are done to verify the advantages. Results show that this algorithm can not only reduce the volatility of the process output and enhance system performance; and the integrated control method is more potential cost advantages.