Mining data from simulation of beer production

Data mining is a methodology for the extraction of knowledge from data, especially, knowledge relating to a problem that we want to solve. Data mining from simulation outputs is performed in this paper. It focuses on techniques for extracting knowledge from simulation outputs for beer production and optimizing devices and labors with certain target. We first set up one simulation model for beer production process and construct optimization objective. Then we set up one data mining model based on witness miner. The mining results show that the model is able to find important information affecting target, make manager diagnose the bottlenecks of the beer production process, and help manager to make decisions rapidly under uncertainty.