Research On Inventory Management Optimization Of Service Spare Parts For Wind-power Equipment Manufacturers

There is an unprecedented shortage of fossil energy with the development of economy.The pollution caused by fossil energy has been widely concerned and also pushed the development of some new energy industries.In recent years,China’s wind power industry has developed rapidly.Now,China is gradually conducting the supply-side reform,and the new machine market is shrinking day by day.But,at the same time,there is a huge increasing demand for maintenance and eco-renovation of the wind driven generators.In this context,many wind-power equipment manufacturers have focused on the quality of the maintenance service,and start to carry out the equipment environmental renovation service or upgrade service,in order to find a new profit growth point.However,most of them are manufacturing enterprises.These manufacturing enterprises use the management methods of raw material inventory to regulate the service parts warehouse and have caused lots of inactive stock.Inventory turnover speed directly affects the capital turnover efficiency.Inactive inventories not only occupy a large amount of money,but also increase too much additional costs.Besides,too long time in storage also aggravates the risk of quality degradation.So,it has become one of the most important management objectives for wind-power equipment manufacturing enterprises to reduce the creation of inactive inventories.In this paper,a famous wind-power equipment manufacturing enterprise is selected as the research object,which is trying to improve the quality of the wind driven generators maintenance service and the environmental renovation service.By using the data of service spare parts,we find the main problem in the inventory management of service spare parts and put forward the corresponding solutions.First,to solve the multi-index classification problem,directional service spare part is chosen as the main research object after considering the demand characteristics.Then,in order to improve the inventory turnover speed of this famous wind-power equipment manufacturing enterprise,dynamic association rule algorithm is applied to mine the valuable association rules hidden behind the sales data.According to the given threshold of support and confidence,we found the frequent item sets and some implied dynamic association rules.Since the association rules change with time obviously,so we can use the autoregressive integrated moving average model to find the future trend of that association rules.Compared with the expert modeler and exponential smoothing method,our prediction model shows higher reliability and stability.Besides,due to the high similarity between the factors which affect the demand of directional service spare part and which affect the association rules,we try to apply the same integrated autoregressive moving model to do the inventory forecast.The result shows that our model has good accuracy in the forecasting.Finally,this paper puts forward the improvement methods of enterprise system and inventory management of service spare parts.These methods have high reference value for those wind-power equipment enterprise with the similar inventory management problems.