Implementing and using smart maintenance technologies: Introducing challenges and enablers related to human, organizational and technological perspectives
2025 (English) In: Procedia Comput. Sci., Elsevier BV , 2025, p. 932-941Conference paper, Published paper (Refereed)
Abstract [en]
Research within smart maintenance has become a popular research topic largely focused on how the nine technologies of Industry 4.0, such as Industrial Internet of Things (IIoT) and Augmented Reality (AR), as well as Artificial Intelligence (AI) and Cyber Physical System (CPS), can be used for, e.g., condition monitoring of equipment, remote services, modelling wear of components, calculating Remaining Useful Life (RUL) and prediction of failure. Due to the new generation of maintenance, new skills are required regarding the interaction between humans and technologies. Human-technology interaction in smart maintenance research is not highlighted in a structured way and according to any type of socio-technical system. The aim of the paper is to study the challenges and their associated theoretically grounded enablers regarding the implementation of and use of smart maintenance technologies, through the interplay between humans, technologies and organizations. The paper is based on empirical data from seven large manufacturing companies in Sweden as well as a literature review.
Place, publisher, year, edition, pages Elsevier BV , 2025. p. 932-941
Series
Procedia Computer Science, ISSN 18770509
Keywords [en]
Industry 4.0, Maintenance 4.0, Smart maintenance, Socio-technical systems, Transformation system, Condition based maintenance, Corrective maintenance, Scheduled maintenance, Cyber-physical systems, Human perspectives, Maintenance technologies, Organizational perspectives, Research topics, Sociotechnical systems, Technological perspective, Transformation systems, Smart manufacturing
National Category
Mechanical Engineering
Identifiers URN: urn:nbn:se:mdh:diva-70738 DOI: 10.1016/j.procs.2025.01.155 Scopus ID: 2-s2.0-105000509704 ISBN: 9781510849914 (print) OAI: oai:DiVA.org:mdh-70738 DiVA, id: diva2:1949252
Conference Procedia Computer Science
2025-04-022025-04-022026-04-29 Bibliographically approved