Research On OLAP And Its Application In The Production Of Evaluation System

Because product quality is the fundamental survival of the enterprise, how to establish an efficient and scientific Production Evaluation System (PES) is a crucial problems to be solved. In connection with the actual production status of a tobacco company in Hunan, the tobacco production evaluation algorithm was proposed in this paper, combining with the analytic hierarchy process (AHP) and fuzzy evaluation method, on this basis, adopting the data processing method based on On-line Analytical Processing technology (OLAP), the production evaluation system based on OLAP was developed. Include the following areas:First, analysis the research of production evaluation system both at home and abroad, introduce several classical evaluation model and algorithms, and analysis their advantages and disadvantages, then elaborate the available advantage of OLAP when it apply to the production evaluation system. Next, according to the needs analysis for the tobacco company, combining with OLAP, the system is divided into 4 parts: model building, model analysis, evaluation and production control optimization of batch analysis, then we design the framework of the production evaluation system based on OLAP, conclude the key issues and given the detailed solution.Second, in connection with the actual production status of the tobacco company, the production evaluation algorithm based on analytic hierarchy process-fuzzy Mathematics evaluation (AHP-FME) was proposed. The basic idea of the algorithm: according to the needs analysis of the enterprise, establish the hierarchy of production evaluation index system, establish the factor set, evaluation set, weight sets and fuzzy membership function sets etc. for the evaluation index, adopt analytic hierarchy process to determine the weight of each index, and normalize the evaluate indicators in unification and standardization, using the mapping method, efficacy coefficient method. Finally the fuzzy comprehensive evaluation result of the tobacco company was given. Practice shows that this method is objective and reasonable comparatively; it is able to quantize the production level of the tobacco companies as a good guide.Finally, according to the technical presentations and needs analysis above, we design and develop the production evaluation system. The first thing is analyzing the requirements of OLAP system and the efficiency of ETL processing: the Star Structure is fast polymerization, efficient analysis; while the Snowflake Structure is clearer and easier to get interactive with the OLAP system. So in practice, we combine both of the two structures to design the data warehouse. Pre-test results shows that the system provides some reliable tuning method to optimize the production control indeed, achieving our goal.