Developing a Model for Agility in Overhaul through Interpretive Structural Modeling (Case Study: Defensive Overhaul Center)

Document Type : Research Paper

Authors

1 MSc., Department of Industrial Engineering, Faculty of Managment and Soft Sciences, Malek Ashtar University, Tehran, Iran

2 Assistant Prof., Department of Industrial Engineering, Faculty of Managment and Soft Sciences, Malek Ashtar University, Tehran, Iran

Abstract

Objective: Today, organizations are confronted with a changing and unpredictable environment, and only those organizations which are able to quickly respond to these changes and actually have a decent level of agility can progress. In this paper, a model is presented that outlines the most important key factors in overhaul and agility.
Methods: Interpretative Structural Modeling (ISM) was used and to the data were collected based on interviews and questionnaires.
Results: After studying literature on the subject, 36 factors were identified and then confirmed by the experts. Then, using the brain Storming approach, a total of 16 factors were identified as the key factors in the overhaul industry. Afterwards, a questionnaire was designed based on the ISM approach and was made available to 17 experts. Upon reaching consensus, these factors were analyzed by that approach and were categorized into six levels, the most important of which were “the support of senior managers”, “the clear statement of managerial goals” and “focus and attention to the consumers (customers)”.
Conclusion: The findings of this research showed that using long-term and short-term plans by the hierarchy of command, exploiting the capabilities of industrial and academic centers of the country, using the knowledge and experience of the staff of the organization, we can reach to the desired level of agility in overhaul in defensive equipment.

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References
Aghae, A. & Aghae, R. (2014). Providing a conceptual model of organizational agility. Technology Development Quarterly, 10(39), 37-43. (in Persian)
Ansari, I. & Sadeghi Moghadam, M.R. (2014). Identification, Determination and Classification of Green Supply Chain Management Drives Using Structural Interpretive Modeling Approach. Strategic Management Studies Quarterly, 12(35), 123-150.(in Persian)
Dubey, R., Gunasekaran, A. (2014). International Journal of Advanced Manufacturing Technology, 76(9-12), 1-12.
Fendereski, A., Didehkhani, H., & Fendereski, A. (2014). The Identification and Ranking Related to Organizational Agility Using Analytic Hierarchical Processing. International journal of Basic Science & Applied Research, 3(7), 455-464.
Firozabadi, M., Bamdad, J. & Bigdeli, E. (2014). Identification and Classification of Factors Affecting Agility by QFD Method. Iranian Journal of Management Research, 17(4), 119-138. (in Persian)
Guru Dev, C.A., & Kumar, S. (2016). Analysis on Critical Success Factors for Agile Manufacturing Evaluation in Original Equipment Manufacturing Industry-An AHP Approach. Chinese Journal of Mechanical Engineering, 29(5), 880-888.
Karami, E., Arab, A., Falah Lajimi, H. (2015). Effects of Key Supply Chain Success Factors on Strategic Performance of Electronic Industries in Iran. Iranian Journal of Management Research, 19(4), 185-206.(in Persian)
Karmi Govareshaki, M., Eafandiyari, N., Moradi, M. (2015). Provides a hybrid approach based on Gap Analysis and FQFD to achieve agility. Strategic Management Studies, 13(93), 135-170.(in Persian)
Kumar, P., Singh, R.K., & Kumar, R. (2015). An integrated framework of interpretive structural modeling and graph theory matrix approach to fix the agility index of an automobile manufacturing organization.International Journal of System Assurance Engineering and Management. DOI 10.1007/s13198-015-0350.
Lee, S.G., Ma, Y. G., Thimm, L., Verstraeten, J. (2008). Product lifecycle management in aviation maintenance. Computer in Industry, 59(2-3), 296–303.
Muchiri, A.K., Ikua, B. W., Muchiri, P.N., & Irungu, P. K. (2014). Development of a theoretical framework for evaluating maintenance practices. International Journal of System Assurance Engineering and Management, 8(1), 198- 207.
Olfat, L., & Shahriyarinia, A. (2014). Interpretive Structural Modeling of Factors Affecting Peer Selection in Agile Supply Chain. Production and Operations Management, 5(2), 109-128.(in Persian)
Rahnavard, F., & Alijani, Z. (2016). The Impact of Information Technology on Organizational Agility in the light of Organizational Culture. Journal of Management Development and Transformation, 44, 45-55.(in Persian)
Raj, S. A., Vinodh, S., Gaurav, W., & Sundaram, S. S., (2014). Application of hybrid MCDM techniques for prioritising the gaps in an agile manufacturing implementation project. International Journal of Services and Operations Management, 17(4), 421-438.
Sharifi, H., & Zhang, Z. (1999). A methodology for achieving agility in manufacturing organisations: An introduction. International Journal of Production Economics, 62(1), 7-22.
Sindhwani, R., & Malhotra, V. (2016). Modelling and analysis of agile manufacturing system by ISM and MICMAC analysis. International Journal of System Assurance Engineering and Management, 8(2), 253-263.
Toloie Eshlaghy, A., Mashayekhi, A.N., Rajabzadeh, A., & Razavian, M. (2009). Applying path analysis method in defining, effective factors in organisation agility. International Journal of Production Research, 48(6), 1765-1786.
Vinodh, S., & Vimal, K. E. K. (2012). Thirty criteria based leanness assessment using fuzzy logic approach. The International Journal of Advanced Manufacturing Technology, 60(9-12), 1185-1195.
Vinodh, S., Aravindraj, S., Pushkar, B., & Kishore, S. (2012). Estimation of reliability and validity of agility constructs using structural equation modelling. International Journal of Production Research, 50(23), 6737-6745.
Zain, M., Rose, R.C., Abdullah, I. & Masrom, M. (2005). The relationship between information technology acceptance &organizational agility in Malaysia. Information & Management, 42(6), 829–839.