Optimizing Maintenance Management System: Identification of Critical Risk and Safety Factors in Human Error Based Corrective Maintenance in the SMEs using Fuzzy DEMATEL Approach

Authors

  • K Velmurugan Research Faculty, IRC-Center for Research and Automatic Control Engineering, Kalasalingam Academy of Research and Education, Krishnankoil – 626126, TamilNadu, India
  • Gianpaolo Di Bona Professor, Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Via G. Di Biasio 43 03043, Cassino (FR), Italy
  • Alessandro Silvestri Professor, Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Via G. Di Biasio 43 03043, Cassino (FR), Italy

DOI:

https://doi.org/10.31181/rme501

Keywords:

3D Printing Technology, Corrective Maintenance Management, Human Error-Based factors, Fuzzy set theory, Decision-Making Trial and Evaluation Laboratory, Small and Medium-sized Enterprises

Abstract

A better and optimal maintenance management system is a key source of a sustainable manufacturing environment in the competitive world. In response to improving drastic and competitive manufacturing working environments, many Small and Medium-sized Enterprises (SMEs) wish for an optimal maintenance management system for business success and customer satisfaction. For the purpose of organizing optimal Corrective Maintenance Management (CMM) effectively, some literature and direct industrial surveys have suggested several critical factors of Human Error-Based (HEB) CMM in the working environment of SMEs. HEB accidents and machine breakdowns have always been a major concern in this type of maintenance management system in SMEs, especially in the 3D printing technology applied automotive industries. Such undesirable problems are more prevalent in SMEs of developing countries, especially in the SMEs of southern Tamil Nadu, India. Moreover, ranking the most significant critical factors in HEB maintenance inevitably involves the vagueness of human judgment in the traditional way of approach. This research objective is to predict, analyze, and evaluate the HEB maintenance factors that trigger undesirable machine accidents and corrective maintenance activities of Sensors and switches manufacturing operations in SMEs. Hence, this real-time case study research presents a favorable method for combining fuzzy set theory and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to rank the critical factors for optimal CMM implementation in the working environment of SMEs. According to this analysis identified the most critical factors (Meshing around - 0.205, Poorly written procedures and manuals, and work instructions – 0.163) were identified under two major sub-categories, such as environmental and organizational factors generally influenced in the SMEs.  Also, an empirical case study is illustrated by presenting the proposed hybrid MCDM technique and demonstrating the application of implications.

References

Akyuz, E., & Celik, E. (2015). A fuzzy DEMATEL method to evaluate critical operational hazards during gas freeing process in crude oil tankers. Journal of Loss Prevention in the Process Industries, 38, 243-253. https://doi.org/10.1016/j.jlp.2015.10.006

Başhan, V., & Demirel, H. (2019). Application of fuzzy dematel technique to assess most common critical operational faults of marine boilers. Politeknik Dergisi, 22(3), 545-555. https://doi.org/10.2339/politeknik.426644

Demirel, H. (2020). A DEMATEL approach based on fuzzy sets for evaluating critical factors of gas turbine in marine engineering. Journal of Marine Science and Application, 19(3), 485-493. https://doi.org/10.1007/s11804-020-00164-0

Feng, X., Li, E., Li, J., & Wei, C. (2024). Critical influencing factors of employees’ green behavior: Three-stage hybrid fuzzy DEMATEL–ISM–MICMAC approach. Environment, development and sustainability, 26(7), 17783-17811. https://doi.org/10.1007/s10668-023-03364-0

Gökalp, Y., & Eti, S. (2025). Priority strategy development with intuitionistic fuzzy DEMATEL method for reducing energy costs in hospitals. Journal of soft computing and decision analytics, 3(1), 26-32. https://doi.org/10.31181/jscda31202548

Irfan, M., Rauniyar, A., Hu, J., Singh, A. K., & Chandra, S. S. (2024). Modeling barriers to the adoption of metaverse in the construction industry: An application of fuzzy-DEMATEL approach. Applied Soft Computing, 167, 112180. https://doi.org/10.1016/j.asoc.2024.112180

Kuzu, A. C. (2021). Risk analysis of break-in-two accident of ships using fuzzy DEMATEL method. Ocean Engineering, 235, 109410. https://doi.org/10.1016/j.oceaneng.2021.109410

Li, F., Wang, W., Dubljevic, S., Khan, F., Xu, J., & Yi, J. (2019). Analysis on accident-causing factors of urban buried gas pipeline network by combining DEMATEL, ISM and BN methods. Journal of Loss Prevention in the Process Industries, 61, 49-57. https://doi.org/10.1016/j.jlp.2019.06.001

Lin, R.-J. (2013). Using fuzzy DEMATEL to evaluate the green supply chain management practices. Journal of Cleaner Production, 40, 32-39. https://doi.org/10.1016/j.jclepro.2011.06.010

Lin, Y.-T., Yang, Y.-H., Kang, J.-S., & Yu, H.-C. (2011). Using DEMATEL method to explore the core competences and causal effect of the IC design service company: An empirical case study. Expert Systems with applications, 38(5), 6262-6268. https://doi.org/10.1016/j.eswa.2010.11.092

Luthra, S., Govindan, K., Kharb, R. K., & Mangla, S. K. (2016). Evaluating the enablers in solar power developments in the current scenario using fuzzy DEMATEL: An Indian perspective. Renewable and sustainable energy reviews, 63, 379-397. https://doi.org/10.1016/j.rser.2016.04.041

Massami, E. P., & Manyasi, M. M. (2019). Evaluation of the challenges facing on-board training in Tanzania: a dematel modelling approach. International Journal of Business Information Systems Strategies (IJBISS), 8(1/2/3). https://doi.org/10.14810/ijbiss.2019.8301

Meng, X., Chen, G., Zhu, G., & Zhu, Y. (2019). Dynamic quantitative risk assessment of accidents induced by leakage on offshore platforms using DEMATEL-BN. International Journal of Naval Architecture and Ocean Engineering, 11(1), 22-32. https://doi.org/10.1016/j.ijnaoe.2017.12.001

Mentes, A., Akyildiz, H., Yetkin, M., & Turkoglu, N. (2015). A FSA based fuzzy DEMATEL approach for risk assessment of cargo ships at coasts and open seas of Turkey. Safety science, 79, 1-10. https://doi.org/10.1016/j.ssci.2015.05.004

Mohammadfam, I., Aliabadi, M. M., Soltanian, A. R., Tabibzadeh, M., & Mahdinia, M. (2019). Investigating interactions among vital variables affecting situation awareness based on Fuzzy DEMATEL method. International Journal of Industrial Ergonomics, 74, 102842. https://doi.org/10.1016/j.ergon.2019.102842

Özdemir, Ü. (2016). Investigation of Occupational Accidents Occurred in Ports By Using Fuzzy DEMATEL and Fuzzy TOPSIS Methods. Journal of ETA Maritime Science, 4(3), 235-247. https://doi.org/10.5505/jems.2016.74936

Özdemir, Ü., Yılmaz, H., & Başar, E. (2016). Investigation of marine pollution caused by ship operations with DEMATEL method. TransNav: International Journal on Marine Navigation and Safety of Sea Transportation, 10(2). https://doi.org/10.12716/1001.10.02.14

Quezada, L. E., López-Ospina, H. A., Valenzuela, J. E., Oddershede, A. M., & Palominos, P. I. (2024). A method for formulating a manufacturing strategy using fuzzy DEMATEL and fuzzy VIKOR. Engineering Management Journal, 36(2), 147-163. https://doi.org/10.1080/10429247.2023.2224707

Vujanović, D., Momčilović, V., Bojović, N., & Papić, V. (2012). Evaluation of vehicle fleet maintenance management indicators by application of DEMATEL and ANP. Expert Systems with applications, 39(12), 10552-10563. https://doi.org/10.1016/j.eswa.2012.02.159

Wang, L., Cao, Q., & Zhou, L. (2018). Research on the influencing factors in coal mine production safety based on the combination of DEMATEL and ISM. Safety science, 103, 51-61. https://doi.org/10.1016/j.ssci.2017.11.007

Wang, S., Wang, J., & Wang, X. (2024). Risk analysis of human evacuation aboard passenger ships based on fuzzy DEMATEL-ISM-BN. Ocean Engineering, 313, 119520. https://doi.org/10.1016/j.oceaneng.2024.119520

Yang, J. L., & Tzeng, G.-H. (2011). An integrated MCDM technique combined with DEMATEL for a novel cluster-weighted with ANP method. Expert Systems with applications, 38(3), 1417-1424. https://doi.org/10.1016/j.eswa.2010.07.048

Yang, Y.-P. O., Shieh, H.-M., Leu, J.-D., & Tzeng, G.-H. (2008). A novel hybrid MCDM model combined with DEMATEL and ANP with applications. International journal of operations research, 5(3), 160-168. https://www.researchgate.net/publication/255620527_A_novel_hybrid_MCDM_model_combined_with_DEMATEL_and_ANP_with_applications

Zadeh, L. A. (2015). Fuzzy logic—a personal perspective. Fuzzy sets and systems, 281, 4-20. https://doi.org/10.1016/j.fss.2015.05.009

Zhou, Q., Huang, W., & Zhang, Y. (2011). Identifying critical success factors in emergency management using a fuzzy DEMATEL method. Safety science, 49(2), 243-252. https://doi.org/10.1016/j.ssci.2010.08.005

Downloads

Published

2025-12-18

How to Cite

Optimizing Maintenance Management System: Identification of Critical Risk and Safety Factors in Human Error Based Corrective Maintenance in the SMEs using Fuzzy DEMATEL Approach. (2025). Reports in Mechanical Engineering, 6(2), 23-36. https://doi.org/10.31181/rme501