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.

Smart Maintenance

Maintenance Management

Data-driven Decisions

Decision Support

Data Quality

Organisational Factors


P. Savolainen

Student at Chalmers

J. Magnusson

Student at Chalmers

Maheshwaran Gopalakrishnan

Chalmers, Industrial and Materials Science, Production Systems

Ebru Turanoglu Bekar

Chalmers, Industrial and Materials Science, Production Systems

Anders Skoogh

Chalmers, Industrial and Materials Science, Production Systems


2405-8963 (ISSN) 24058963 (eISSN)

Vol. 53 3 95-100

4th International-Federation-of-Automatic-Control (IFAC) Workshop on Advanced Maintenance Engineering, Services and Technologies (AMEST)
Cambridge, United Kingdom,

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Reliability and Maintenance

Business Administration

Areas of Advance




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