Developing a DEA model to evaluate manufacturing performance: a case study

In the competitive situation of nowadays, organizations are continuously evaluating and surveying their performance. Understanding the components which involve performance , an organization may raise up its position in market. Data envelopment analysis has been accepted as an approach to compare and evaluate the performance which has been employed widely in the researches. In this paper, we use DEA to evaluate the monthly performance of an automobile parts manufacturer and to recognize the good and bad performance. What is important in this research is to use common weights to prevent iteration in solving the model because of alteration in data. In this paper, first we use DEA as an basic model to obtain monthly performance measures and then using common weights, we acquire the performance measures according to two set of historical and current data. Furthermore, we utilize control charts to recognize the months with bad performance from good one. Eventually, we use experts judgments to verify the results of model.