The Study On Inventory Strategy Of Automotive Spare Parts Under Energy Consumption Constraint

With the growth of economic,the spare part demands of heavy duty truck face some new development opportunities,but the environment problems caused by energy consumption and carbon emissions have become serious restraints of the development of heavy duty truck enterprise.The spare parts inventory management directly affect the production planning and the satisfaction of customer demands,which is a significant mean to save cost,improve the competitiveness of companies.At present,the inventory of heavy duty truck companies is not only faced with the double pressure of costs and service level,but also more and more limitation by constraints of energy saving and emission reduction.Based on HY spare parts company as an example,this paper research inventory strategy from classification and ordering strategies of heavy auto spare parts company.First of all,based on the relevant theoretical research of inventory management,we put forward multi-criteria classification of spare parts strategy based on data analysis,apply K-means clustering method in spare parts classification with the real data of the five criteria,the spare parts classification scheme can provide subsequent accurate inventory ordering strategy with data basis and decision support.Secondly,based on the results of the classification scheme,this paper focus on spare parts with class A and class B,put forward an ordering model for various spare parts under energy consumption constraints,with minimization of inventory cost and shortage rates.At the same time.the model considers the uncertainty of spare parts demands and the characteristics of large energy consumption,carbon emissions constraints and expanded inventory capacity constraints are established.Combining with the characteristics of model structure,we design a Lagrangian relaxation heuristic algorithm to solve the model in this paper.Finally,the ordering strategy of HY company with 250 kinds of spare parts is carried on the case analysis,the rationality of the model and the effectiveness of the algorithm are validated by enterprise’s inventory data.We provide the inventory ordering strategy under the energy consumption,demonstrates that the proposed ordering strategy can save cost for the enterprise.At the same time,through the study of the sensitivity analysis of model parameters,we give the Pareto optimal solution between the inventory cost and service level under different parameters variation,which can provide decision support in terms of inventory management for the enterprise.