Data Driven Maintenance: A Promising Way of Action for Future Industrial Services Management
Paper i 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.

Simulation tool

Service-related business models

Maintenance planning

Data driven maintenance

Författare

Mirka Kans

Linnéuniversitetet

Anders Ingwald

Linnéuniversitetet

Ann-Brith Strömberg

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Michael Patriksson

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

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, ,

Ämneskategorier

Produktionsteknik, arbetsvetenskap och ergonomi

Annan maskinteknik

Tillförlitlighets- och kvalitetsteknik

Styrkeområden

Produktion

DOI

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

Mer information

Senast uppdaterat

2022-03-17