Factors Influencing the Implementation of Digital Technologies for Predictive Maintenance: An Automated Production Case
2025 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Student thesis
Abstract [en]
The competitiveness today amongst companies is greater than ever before and it is driven by digitalisation. As a result of this, organisations may strive to extend and ultimately undergo considerable changes, to develop predictive maintenance in automated production. However, the complexity of succeeding with their extension related to the implementation of predictive maintenance is often underestimated. The reality is different and preparing the organisation for these changes is vital. Otherwise, problems might arise such as delays, increased costs, and undesirable project outcomes.
The study was inspired by a case study approach with the purpose of getting an in-depth understanding to support identifying enabling, and hindering factors when implementing digital maintenance technologies, observing the phenomenon in its natural environment. The data for this study was gathered through interviews and a questionnaire.
Given the results of this study, the empirical evidence gathered suggests there are a multitude of factors that are influencing for the success of the implementation of digital maintenance technologies. The most important influencing factors were found to be Preparation and Compatibility, as well as Top management commitment. However, it was also found that it is important to consider all the factors unveiled by this study to enable the implementation of digital maintenance technologies.
This study helped shed light on the importance for organisations to rigorously plan and take serious action in relation to their maturity regarding digitalisation. There are numerous challenges that need to be considered especially when the knowledge in the area of digitalisation is limited. Ultimately, this study highlights the vital importance of preparing for an implementation to expedite the transition from reactive to predictive maintenance.
Place, publisher, year, edition, pages
2025.
Keywords [en]
Digital maintenance technologies, Industry 4.0, Predictive maintenance, Change management, Social-technical systems
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hj:diva-67370OAI: oai:DiVA.org:hj-67370DiVA, id: diva2:1940811
External cooperation
Troax AB
Supervisors
Examiners
2025-03-122025-02-262025-10-13Bibliographically approved