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This research uses Network Data EnvelopmentAanalysis (NDEA) by  undesirable factors to analyze and evaluate the performance of automotive industry. The modeling used is applied to five production lines of an automobile company by 16 indicators. The data used are for the year 2019. The main purpose is to provide a model to improve the quality of the product by evaluating the performance of quality health in production lines able  to rank by providing appropriate quality indicators to identify, formulate and achieve corrective measures. Accompanied with accurate problem solving and operational scheduling according to the most efficient organization/production line and so investigating the source of the problem and preventing the occurrence of the problem. Because determining the direction of performance and key performance indicators (KPI) of the organization and measuring them to increase its health efficiency requires an efficient and integrated system. On the other hand, creating a homogeneous and orderly development process between the elements of the organization as a common language to solve the quality problems by aiming the improvement of the performance, customer satisfaction, sustainable production and cost management has been proposed.

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This paper develops slacks-based measure (SBM) and additive SBM (ASBM) to evaluate efficiency of decision making units (DMUs) in a two-stage structure with undesirable outputs and feedback variables from the internal perspective. The SBM model is linearized  for a specific weight and the ASBM model is reformulated as a second order cone program. The target values for all inputs, outputs (both desirable and undesirable) and intermediate products are  provided. This study shows that unlike the SBM model, ASBM can be adapted to the preference of the decision maker by selecting the weights to aggregate stages in the network.
 

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Data Envelopment Analysis is one of the most appropriate methods in Evaluation of decision-making units in the real world. That is why researchers have always tried to improve and develop existing methods and approaches in this field. Network Data Envelopment Analysis is used to evaluate the efficiency of network systems by considering processes within divisions. In the evaluation of network systems, one of the challenges is the presence of undesirable and non-discretionary data in the system. Not many conducted have been done about the simultaneous presence of these factors in general two-stage network systems. For this reason, by extending CCR model and combining some methods in this study, we presented a model that is able to evaluate two-stage systems with the mentioned conditions. One of the strengths of the proposed model in this study is the achievement of the efficiency of the system and divisions simultaneously. At the end of the article, we analyzed the results with a numerical example. The results show the ability of the presented model in evaluating the systems under investigation.