System Engineering and Productivity

System Engineering and Productivity

Risk Management of Outsourcing Projects in Auto Parts Manufacturing Companies by Using Failure Mode Analysis Method and Decision-Making Technique

Document Type : Research Paper

Authors
Reza Khodayari 1
Mehdi Yazdani 2
Adel Pourghader Chobar 3
Seyedeh Tannaz Salehan 4
1 M.Sc., Department of Industrial Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
2 Corresponding author: Associate Professor, Department of Industrial Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
3 Ph.D., Department of Industrial Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
4 Ph.D. Student, Department of Industrial Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
10.22034/msb.2024.2031280.1212
Abstract
This research deals with the risk management of outsourcing projects in automotive component manufacturing companies. The study has shown that automotive companies outsource many of their product sub-categories to external suppliers due to various constraints. This issue affects the risk management in the quality, productivity and profitability of the organization. The present research examines the risk management of outsourcing projects in automotive component manufacturing companies by using failure mode analysis and its effects and multi-criteria decision-making technique. The scope of this research includes companies that operate in the field of automotive component manufacturing. To collect information, the opinions of experts, managers and experts of outsourcing projects in automotive component manufacturing companies have been used. According to the analysis, seventy sub-criteria have been identified and the level of each risk has been examined using the failure mode analysis and its effects method. Then, ten criteria and seventeen sub-criteria were identified and prioritized using the DANP weighting method. The results showed that the most important criteria include infrastructure management, commercial, management, and contractor, and the most important sub-criteria include increased repair time, lack of awareness in plans and lengthening project time, errors in rejection or acceptance, and loss of key employees.




 

Highlights

  • Risk management in outsourcing projects in automotive component companies.
  • Identifying and prioritizing risks using the DANP method.
  • The most important criteria include infrastructure management, commercial, management and contractor.

Keywords
Risk Management
Automotive parts manufacturing: Outsourcing
Failure mode analysis method and its effects
Multi-axis decision-making
Subjects

Copyright ©, Reza Khodayari, Mehdi Yazdani, Adel Pourghader Chobar, Seyedeh Tannaz Salehan

 

License

This article is released under the Creative Commons Attribution (CC BY 4.0) license. Anyone is free to copy, share, translate, and adapt this article for any purpose, whether commercial or non-commercial, as long as proper citation is given to the authors and original publication.

 
     Abbasi, A., & Nikbakht, M. (2015). Providing a framework for identifying key indicators of outsourcing risks for aerospace products, Second International Conference on Management in the 21st Century. (In Persian).
     Aldisa, R. T., & Maulana, P. (2022). Project Risk Management on Agile Development Team: Case Study of an Outsourcing Company in Indonesia. Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi), 6(4), 556-560. DOI: https://doi.org/10.35870/jtik.v6i4.559
     Aubert, B. A., Dussault, S., Patry, M., & Rivard, S. (1999, January). Managing the risk of IT outsourcing. In Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences. 1999. HICSS-32. Abstracts and CD-ROM of Full Papers (pp. 10-pp). IEEE. DOI: https://doi.org/10.1109/HICSS.1999.772972.
     Avazkhah, H. & Mohebbi, A. H. (2011), Project Risk Management, Tehran, Sabz Rayaneh Kian. (In Persian).
     Barthelemy, J. (2003). The seven deadly sins of outsourcing. Academy of Management Perspectives, 17(2), 87-98. DOI: https://doi.org/10.5465/ame.2003.10025203.
     Behesht-Ayin, F., Anvari, A. Ronaghi, M. H. (2018). Evaluating and prioritizing outsourcing risks using the GDEMATEL and ISM methods (a case study of a power generation management company). Quarterly Strategic Management in Industrial Systems, 13 (43), 69-82. (In Persian).
     Bi, H., Lu, F., Duan, S., Huang, M., Zhu, J., & Liu, M. (2020). Two-level principal–agent model for schedule risk control of IT outsourcing project based on genetic algorithm. Engineering Applications of Artificial Intelligence, 91, 103584. DOI: https://doi.org/10.1016/j.engappai.2020.103584.
     Cai, X., Hall, N. G., Wang, S., & Zhang, F. (2023). Cooperation and contract design in project management with outsourcing. Journal of Systems Science and Systems Engineering, 32(1), 34-70. DOI: https://doi.org/10.1007/s11518-023-5548-x
     Dabiri G., Ghadiri Thani M., Vadaye Khairy H. (2009). Analysis of potential failure modes and their effects. Tehran: Iran Khodro Parts Design and Engineering Supply Company (SAPCO) Publications. (In Persian).
     Esmaeili-Najafabadi, E., Azad, N., Pourmohammadi, H., & Nezhad, M. S. F. (2021). Risk-averse outsourcing strategy in the presence of demand and supply uncertainties. Computers & Industrial Engineering, 151, 106906. DOI: https://doi.org/10.1016/j.cie.2020.106906.
     Hosseini Dehshiri, S. J. (2019). Using gray numbers theory in multi-attribute decision making methods for the evaluation the risk of outsourcing of information technology projects. Business Intelligence Management Studies, 7(28), 167-198. DOI: https://doi.org/10.22054/ims.2019.10243.
     Lu, F., Yan, T., Bi, H., Feng, M., Wang, S., & Huang, M. (2022). A bilevel whale optimization algorithm for risk management scheduling of information technology projects considering outsourcing. Knowledge-Based Systems, 235, 107600. DOI: https://doi.org/10.1016/j.knosys.2021.107600.
     Mousavi, S. N., & Feli, R. (2020). Interpretative-structural modeling of outsourcing human resources in Maroon Petrochemical Company. Strategic Studies in Petroleum and energy Industry, 11(42), 179-210. (In Persian).
     Qeydar Khaljani, J., & Taslimi, S. (2022). A Robust Model for Optimal Utilization of Resource in Outsourcable Projects with Uncertain Budget in Government Organization. Journal of Industrial Management Perspective, 12(2), 65-88. DOI: https://doi.org/10.52547/jimp.12.2.65.
     Silva, W. D. O., & Morais, D. C. (2022). Impacts and insights of circular business models’ outsourcing decisions on textile and fashion waste management: A multi-criteria decision model for sorting circular strategies. Journal of Cleaner Production, 370, 133551. DOI: https://doi.org/10.1016/j.jclepro.2022.133551.
     Somers, T. M., & Nelson, K. G. (2004). A taxonomy of players and activities across the ERP project life cycle. Information & Management, 41(3), 257-278. DOI: https://doi.org/10.1016/S0378-7206(03)00023-5.
     Tian, Q., & Guo, W. (2019). Reconfiguration of manufacturing supply chains considering outsourcing decisions and supply chain risks. Journal of Manufacturing Systems, 52, 217-226. DOI: https://doi.org/10.1016/j.jmsy.2019.04.005.
     Wideman, R. M. (1992). Project and program risk management: a guide to managing risks and opportunities. Project Management Institute, Pennsylvania, PA
System Engineering and Productivity
Volume 4, Issue 3 - Serial Number 12
Serial No. 12, Autumn Quarterly
Autumn 2024
Pages 31-48

  • Receive Date 05 June 2024
  • Revise Date 02 July 2024
  • Accept Date 16 August 2024
  • First Publish Date 17 October 2024
  • Publish Date 21 November 2024