Research Of Spare Parts Information Management System Based On Inventory Strategy

For large-scale manufacturing enterprises,the most important mission in the daily work is ensuring the production plans to be finished on time,so the most effective method to guarantee yield and profit is making relevant strategies to reduce the failure rate of production equipment.At present,preventive maintenance and after-maintenance are the two most common methods used in the maintenance of equipment failure.Preventive maintenance is a kind of proactive maintenance which can predict the demand for spare parts and facilitate the advance purchase of spare parts while the occurrence of after-maintenance is difficult to predict due to its passivity and randomness that leads to shortages caused by the loss of maintenance spare parts.In this paper,the mathematic model is built based on the demand forecasting of the spare parts to provide the theoretical basis for the setting of purchase quantity and ordering point by combining the two maintenance methods.Taken spare parts for equipment maintenance of automobile manufacturing enterprise as the research object,Analytic Hierarchy Process(AHP)was introduced to realize the classification method upgrading based on the traditional "ABC" classification method,using the proportion division to get more precise boundaries of spare parts classification and prepare theoretical foundation for the research of class B spare parts inventory model.Relative to the A,C class spare parts,class B spare parts are in a moderate position in the matter of spare parts types and inventory amount and its academic research are less,so it was taken as the research object for the spare parts inventory model in this paper.Bayesian method and second exponential smoothing method were used to forecast demand respectively and got the demand distribution based on the demand characteristics of spare parts which were from after-maintenance and preventive maintenance.In the meantime,AHP was introduced to reduce the dependency of the Bayesian method which uses human experience to calculate prior distribution probability.At last,the forecast methods were proved to be reasonable with the case verification.In this paper,the mathematical model of spare parts was established based on the demand forecasting which also took the basic idea of economic order quantity and the principle of "cost minimization".With the example of the actual spare parts inventorymanagement of an automobile company,the model was solved using the genetic algorithm to calculate the best order quantity,order point,the largest inventory and so on and verify the result to meet inventory service level requirements of the company.At last,the model was proved to achieve the goal of minimizing cost with the premise of meeting the demand for spare parts.With the development of information technology,information system is adopted by more and more enterprises to help the staff complete the daily work and provide the decision analysis for manager.Therefore,a set of information management system for maintenance spare parts is developed using C#,Visual Studio2010 and other tools based on the above theoretical research and the system has been successfully applied to the enterprise's spare parts management and achieve good results.