Challenges in the Maintenance and Diagnostic Segment of Digital Asset Management in the Swedish Railway Industry

Abstract: Just like the rest of society, the use of digital technology has throughout the years become a more crucial part for train companies to improve performance, meet customer demands, improve operation and maintenance processes to increase efficiency and reliability. These solutions have through time developed to become part of a cluster named Digital Asset Management (DAM). A highly relevant segment of DAM is the maintenance and diagnostic segment (M&D) involving solutions such as diagnostic systems, and predictive maintenance. The purpose of this thesis was to investigate what the market of M&D looks like in Sweden given its complex market structure with approximately 40 private train owners. A multi-case study was conducted in which data was collected through eight semi-structured interviews with employees from different key companies in the Swedish railway industry. Based on the interviews, there are several challenges within the digitalization process in the maintenance and diagnostic segment of DAM. These are related to the following: data availability, data analysis and modelling, investments in knowledge and skills, ecosystem perspective and lastly, maintenance optimization. The role of legislation and its impact on the digitalization was studied. The transition to working with a full condition-based strategy is difficult due to the existing challenges. Instead, it is deemed optimal to implement a hybrid strategy consisting both of conventional/time-based maintenance and condition-based maintenance for applicable components given the current state of the industry.