Digital transformation in the context of maintenance management systems in SMEs: critical factors and empirical effects

K. Velmurugan; S. Saravanasankar; P. Venkumar; R. Sudhakara Pandian

Authors

K. Velmurugan Department of Mechanical Engineering, Kalasalingam Academy of Research and Education, Krishanankoil-626126, Tamil Nadu, India
S. Saravanasankar Department of Mechanical Engineering, Kalasalingam Academy of Research and Education, Krishanankoil-626126, Tamil Nadu, India
P. Venkumar Department of Mechanical Engineering, Kalasalingam Academy of Research and Education, Krishanankoil-626126, Tamil Nadu, India
R. Sudhakara Pandian School of Mechanical Engineering, Vellore Institute of Technology, Vellore-632014, Tamil Nadu, India

Keywords:

digital transformation, maintenance management system, predictive maintenance, Q-methodology, small and medium-sized enterprises

Abstract

Nowadays, digital transformation is an inevitable measure in all industries to reap the benefits of Industry 4.0, and so all Small and Medium-sized Enterprises (SMEs) also, strive to digitize their detrimental functions to their sustained growth. As the digitization triggers real-time data capturing, the introduction of efficient Predictive Maintenance (PdM) schemes in Maintenance Management (MM) becomes feasible, improving operational efficiency. The challenging problem is to correctly identify the factors that will influence the successful implementation of digitization of Maintenance Management System in SMEs. This research focuses on enlisting, evaluating and identifying the most influential factors for implementing digitization in MM system of SMEs. In this work, a Q-methodology based solution methodology is proposed to find the critical factors for the implementation. The Q Set is developed through a well-designed interview process, and an on-line survey software is employed to rank and sort the Q statements both qualitatively and quantitatively, followed by a structured statistical analysis. Out of the five factors that evolved in the process, two factors were identified as influential for the implementation. The proposed methodology is applied to a few SMEs with similarities, and the results obtained exhibit consistency in validating the proposed methodology's accuracy. The proposed methodology is compared with that of similar Q based methodologies reported in the literature, and the proposed methodology is found to be more efficient.

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