Document Type : Research Paper



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


Al-Najjar, B., & Alsyouf, I. (2004). Enhancing a company's profitability and competitiveness using integrated vibration-based maintenance: A case study. European Journal of Operational Research, 157(3), 643-657.
Alsyouf, I. (2006). Measuring maintenance performance using a balanced scorecard approach. Journal of Quality in Maintenance Engineering, 12(2), 133-149.
Arts, R., Knapp, G. M., & Mann Jr, L. (1998). Some aspects of measuring maintenance performance in the process industry. Journal of Quality in Maintenance Engineering, 4(1), 6-11.
Azadeh, A., Ghaderi, S., & Izadbakhsh, H. (2008). Integration of DEA and AHP with computer simulation for railway system improvement and optimization. Applied Mathematics and Computation, 195(2), 775-785.
Barabady, J., & Kumar, U. (2007). Availability allocation through importance measures, International Journal OF Quality & Reliability Management, 24(6) 63-657
Bertolini, M., & Bevilacqua, M. (2006). A combined goal programming—AHP approach to maintenance selection problem. Reliability Engineering & System Safety, 91(7), 839-848.
Bevilacqua, M., & Braglia, M. (2000). The analytic hierarchy process applied to maintenance strategy selection. Reliability Engineering & System Safety, 70(1), 71-83.
Chang, T.-Y., Chung, P.-H., & Hsu, S.-S. (2012). Two-stage performance model for evaluating the managerial efficiency of higher education: application by the Taiwanese tourism and leisure department. Journal of Hospitality, Leisure, Sport & Tourism Education, 11(2), 168-177.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
112 مطالعات مدیریت صنعتی – سال پانزدهم، شماره 44 ، بهار 69
Chen, K., & Guan, J. (2012). Measuring the efficiency of China's regional innovation systems: application of network data envelopment analysis (DEA). Regional Studies, 46(3), 355-377.
Cullinane, K., Wang, T.-F., Song, D.-W., & Ji, P. (2006). The technical efficiency of container ports: comparing data envelopment analysis and stochastic frontier analysis. Transportation Research Part A: Policy and Practice, 40(4), 354-374.
Dal, B., Tugwell, P., & Greatbanks, R. (2000). Overall equipment effectiveness as a measure of operational improvement-A practical analysis. International Journal of Operations & Production Management, 20(12), 1488-1502.
Du, j., (2008). Evaluation Of equipment Reliability, Availability and Maintainability in an oil sands processing plant. the university of British Colombia.
Fallah-Fini, S., Triantis, K., Jesus, M., & Seaver, W. L. (2012). Measuring the efficiency of highway maintenance contracting strategies: A bootstrapped non-parametric meta-frontier approach. European Journal of Operational Research, 219(1), 134-145.
Färe, R., & Grosskopf, S., (2000). Network DEA, Socio-Economic Planning Sciences, 34, 35-49.
Ghotbi, M. R., Monazzam, M. R., Baneshi, M. R., Asadi, M., & Fard, S. M. B. (2012). Noise pollution survey of a two-storey intersection station in Tehran metropolitan subway system. Environmental monitoring and assessment, 184(2), 1097-1106.
Halkos, G. E., Tzeremes, N. G., & Kourtzidis, S. A. (2014). A unified classification of two-stage DEA models. Surveys in operations research and management science, 19(1), 1-16.
Hassannayebi, E., Sajedinejad, A., & Mardani, S. (2014). Urban rail transit planning using a two-stage simulation-based optimization approach. Simulation Modelling Practice and Theory, 49, 151-166.
Hung, S.-W., Lu, W.-M., & Wang, T.-P. (2010). Benchmarking the operating efficiency of Asia container ports. European Journal of Operational Research, 203(3), 706-713.
ارزیابی عملکرد سیستم و زیر سیستم های تهویه قطار های مترو تهران... 111
Jitsuzumi, T., & Nakamura, A. (2010). Causes of inefficiency in Japanese railways: Application of DEA for managers and policymakers. Socio-Economic Planning Sciences, 44(3), 161-173.
Kao, C. (2009). Efficiency decomposition in network data envelopment analysis: A relational model. European Journal of Operational Research, 192(3), 949-962.
Kao, C. (2014). Network data envelopment analysis: A review. European Journal of Operational Research, 239(1), 1-16.
Kao, C., & Hwang, S.-N. (2008). Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European Journal of Operational Research, 185(1), 418-429.
Kao, C., & Hwang, S.-N. (2010). Efficiency measurement for network systems: IT impact on firm performance. Decision Support Systems, 48(3), 437-446.
Kao, C., & Lin, P.-H. (2012). Efficiency of parallel production systems with fuzzy data. Fuzzy Sets and Systems, 198, 83-98.
Kao, C., & Liu, S.-T. (2000). Fuzzy efficiency measures in data envelopment analysis, Fuzzy Sets and Systems 113, 427–437.
Kao, C., & Liu, S.-T. (2011). Efficiencies of two-stage systems with fuzzy data. Fuzzy Sets and Systems, 176(1), 20-35.
Khalili-Damghani K, Taghavifard M (2012) A three-stage fuzzy DEA approach to measure performance of a serial process including JIT practices, agility indices, and goals in supply chains. International Journal of Services and Operations Management 13(2), 147–188
Khalili-Damghani, K., Taghavifard, M. (2013). Sensitivity and stability analysis in two-stage DEA models with fuzzy data. International Journal of Operational Research, 17(1), 1-37.
Khalili-Damghani, K., Taghavifard, M., Abtahi, A.R. (2012). A fuzzy two-stage DEA approach for performance measurement: real case of agility performance in dairy supply chains. International Journal of Applied Decision Sciences, 5(4), 293-317.
114 مطالعات مدیریت صنعتی – سال پانزدهم، شماره 44 ، بهار 69
Khalili-Damghani K, M Tavana . A new fuzzy network data envelopment analysis model for measuring the performance of agility in supply chains, The International Journal of Advanced Manufacturing Technology 69 (1-4), 291-318
Khalili-Damghani K ., Tavana, M. (2014), A new two-stage Stackelberg fuzzy data envelopment analysis model, Measurement 53, 277-296
Kutucuoglu, K., Hamali, J., Irani, Z., & Sharp, J. (2001). A framework for managing maintenance using performance measurement systems. International Journal of Operations & Production Management, 21(1/2), 173-195.
Madu, C. N. (2005). Strategic value of reliability and maintainability management. International Journal of Quality & Reliability Management, 22(3), 317-328.
Markovits-Somogyi, R. (2011). Measuring efficiency in transport: the state of the art of applying data envelopment analysis. Transport, 26(1), 11-19.
2001). An application of DEA to measure the efficiency of Spanish airports prior to privatization. Journal of Air Transport Management, 7(3), 149-157.
Marzouk, M., & Abdelaty, A. (2014). BIM-based framework for managing performance of subway stations. Automation in Construction, 41, 70-77.
Mather, D. (2005). Maintenance Scorecard, The: Industrial Press.
Narasimhan, R., Talluri, S., & Das, A. (2004). Exploring flexibility and execution competencies of manufacturing firms. Journal of Operations Management, 22(1), 91-106.
Ozbek, M. E., de la Garza, J. M., & Triantis, K. (2010). Data and modeling issues faced during the efficiency measurement of road maintenance using data envelopment analysis. Journal of Infrastructure Systems, 16(1), 21-30.
Ozbek, M. E., Jesús, M., & Triantis, K. (2010). Efficiency measurement of bridge maintenance using data envelopment analysis.
ارزیابی عملکرد سیستم و زیر سیستم های تهویه قطار های مترو تهران... 111
Journal of Infrastructure Systems.
Raje, D.V., Olaniya, R.S., Wakhare, P.D. & Deshpande, A.W. (2000). Availability assessment of a two-unit stand-by pumping system, Reliability Engineering and System Safety 68(3), 269–274.
Rouse, P., & Chiu, T. (2009). Towards optimal life cycle management in a road maintenance setting using DEA. European Journal of Operational Research, 196(2), 672-681.
Sampaio, B. R., Neto, O. L., & Sampaio, Y. (2008). Efficiency analysis of public transport systems: Lessons for institutional planning. Transportation Research Part A: Policy and Practice, 42(3), 445-454.
Scheraga, C. A. (2004). Operational efficiency versus financial mobility in the global airline industry: a data envelopment and Tobit analysis. Transportation Research Part A: Policy and Practice, 38(5), 383-404.
Seiford, L. M., & Zhu, J. (1999). Profitability and marketability of the top 55 US commercial banks. management science, 45(9), 1270-1288.
Sexton, T. R., & Lewis, H. F. (2003). Two-stage DEA: An application to major league baseball. Journal of Productivity Analysis, 19(2-3), 227-249.
Van den Bergh, J., De Bruecker, P., Beliën, J., De Boeck, L., & Demeulemeester, E. (2013). A three-stage approach for aircraft line maintenance personnel rostering using MIP, discrete event simulation and DEA. Expert Systems with Applications, 40(7), 2659-2668.
Wakchaure, S. S., & Jha, K. N. (2011). Prioritization of bridges for maintenance planning using data envelopment analysis. Construction Management and Economics, 29(9), 957-968.
Wang, W.-K., Lu, W.-M., & Liu, P.-Y. (2014). A fuzzy multi-objective two-stage DEA model for evaluating the performance of US bank holding companies. Expert Systems with Applications, 41(9), 4290-4297.
Yang, C., & Liu, H.-M. (2012). Managerial efficiency in Taiwan bank branches: A network DEA. Economic Modelling, 29(2), 450-461.
Zadeh, L. A. (1972). A fuzzy-set-theoretic interpretation of linguistic hedges.
119 مطالعات مدیریت صنعتی – سال پانزدهم، شماره 44 ، بهار 69
Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning—I. Information sciences, 8(3), 199-249.
Zhu, J. (2000). Multi-factor performance measure model with an application to Fortune 500 companies. European Journal of Operational Research, 123(1), 105-124