Evaluation of system and subsystem of Tehran's subway trains ventilation using three-stage fuzzy relational data envelopment analysis

Subway network extension, growing expansion an inherent management complexities, made it necessary to use scientific approach, modern technology and global experiences about maintenance. Many equipments and trains of subway network, consist of repairable items which consume considerable human and financial resources of the organization. This paper aims to measure the efficiency and rank ventilation system of Tehran's DC trains and it's subsystems using three-stage relational data envelopment analysis model. About the importance of Tehran’s subway ventilation system, we can say that for 8 months of the year, ventilation system after driving engines which support the movement of trains, gets most important attention of operation management. In this paper with defining ventilation system as decision-making units, we use it to evaluate the system performance and ultimately for maintenance strategy, including an estimate of the maintenance workshop capacity, spare parts and requiring labor. Due to various errors such as human errors, machinery errors, limitations of field data analysis and etc, in this paper fuzzy logic is used to overcome the uncertainly in data. Also, reliability, availability and maintainability analysis, which are most important indicators in the maintenance field, have been used to determine the ventilation system inputs and outputs.