The varieties optimization of spare parts on data envelopment analysis

The choice of spares varieties is a major aspect for the continuous operation of equipment. With the cost of purchases and reserves getting much higher and the equipment becoming more complex, whether the component is classified as spare or not becomes particularly important. Data envelopment analysis (DEA) is an effective method to evaluate the relative efficiency of the decision-making units (DMUs) with multiple inputs and outputs. Aiming at the deficiencies of previous methods to determine spares varieties, this paper will select parameters which have great effect on the component to measure the importance of the part. Meanwhile, we will introduce DEA to varieties optimization. Firstly, through selecting the important quantifiable indicators which can reflect the performance of the equipment, we can get inputs and outputs. Then the optimization model based on DEA is proposed for the spare parts inventory system, at the same time the relative efficiency of each part can be obtained. After that, we can rank all the DMUs to realize varieties optimization. Finally, a numerical example will be provided to illustrate that this method of making spares varieties determination is more scientific and reasonable.