Organisational Constraints in Data-driven Maintenance: a case study in the automotive industry

Paper in proceeding, 2020

Technological development and innovations has been the focus of research in the field of smart maintenance, whereas there is less research regarding how maintenance organisations adapt the development. This case study focuses to understand what constraints maintenance organisations in the transition into applying more data-driven decisions in maintenance. This paper aims to emphasize the organisational challenges in data-driven maintenance, such as trustworthiness of data-driven decisions, data quality, management and competences. Through a case study at a global company in the automotive industry these challenges are highlighted and discussed through a questionnaire survey participated by 72 people and interviews with 7 people from the maintenance organisation.