Data Driven Maintenance: A Promising Way of Action for Future Industrial Services Management
Paper in proceeding, 2022

Maintenance and services of products as well as processes are pivotal for achieving high availability and avoiding catastrophic and costly failures. At the same time, maintenance is routinely performed more frequently than necessary, replacing possibly functional components, which has negative economic impact on the maintenance. New processes and products need to fulfil increased environmental demands, while customers put increasing demands on customization and coordination. Hence, improved maintenance processes possess very high potentials, economically as well as environmentally. The shifting demands on product development and production processes have led to the emergency of new digital solutions as well as new business models, such as integrated product-service offerings. Still, the general maintenance problem of how to perform the right service at the right time, taking available information and given limitations is valid. The project Future Industrial Services Management (FUSE) project was a step in a long-term effort for catalysing the evolution of maintenance and production in the current digital era. In this paper, several aspects of the general maintenance problem are discussed from a data driven perspective, spanning from technology solutions and organizational requirements to new business opportunities and how to create optimal maintenance plans. One of the main results of the project, in the form of a simulation tool for strategy selection, is also described.

Service-related business models

Maintenance planning

Simulation tool

Data driven maintenance

Author

Mirka Kans

Linnaeus University

Anders Ingwald

Linnaeus University

Ann-Brith Strömberg

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Michael Patriksson

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Jan Ekman

RISE Research Institutes of Sweden

Anders Holst

RISE Research Institutes of Sweden

Åsa Rudström

RISE Research Institutes of Sweden

Lecture Notes in Mechanical Engineering

21954356 (ISSN) 21954364 (eISSN)

212-223
9783030936389 (ISBN)

International Congress and Workshop on Industrial AI, IAI 2021
Virtual, Online, ,

Future Industrial Services Management

VINNOVA (2014-00814), 2014-06-01 -- 2016-08-25.

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Other Mechanical Engineering

Reliability and Maintenance

Areas of Advance

Production

DOI

10.1007/978-3-030-93639-6_18

More information

Latest update

3/7/2023 1