DAIMP - Data Analytics in Maintenance Planning
Research Project, 2016
– 2019
This project aims to increase the use of big data analytic in maintenance planning. The current availability in Swedish industry is too low for implementing digital production concepts such as Industrie 4.0.
The purpose of the project is to increase productivity, robustness, and resource efficiency through reduction of failures and disturbances, especially in critical equipment.
The DAIMP project connects data structures on a machine level to analyses needed on a systems level. Expected results are for example: data and information structures for improved internal and external collaboration, algorithms for predictive and prescriptive analytics, and data–driven criticality analysis to support differentiated maintenance planning.
In addition to research-oriented work packages, the project will also work with evaluation and demonstration cases. One of them focuses on the role of data-driven maintenance planning when introducing new car models and production lines at Volvo Cars.
Project leader: Anders Skoogh, Chalmers University of Technology
anders.skoogh@chalmers.se
Participants
Anders Skoogh (contact)
Chalmers, Industrial and Materials Science, Production Systems
Maheshwaran Gopalakrishnan
Chalmers, Industrial and Materials Science, Production Systems
Omkar Salunkhe
Chalmers, Industrial and Materials Science, Production Systems
Mukund Subramaniyan
Chalmers, Industrial and Materials Science, Production Systems
Torbjörn Ylipää
Chalmers, Industrial and Materials Science, Production Systems
Collaborations
AXXOS Industrial Systems
Jönköping, Sweden
IFS world
Göteborg, Sweden
Mälardalens högskola
Västerås, Sweden
Royal Institute of Technology (KTH)
Stockholm, Sweden
Scania CV AB
Södertälje, Sweden
VBG GroupTruck Equipment AB
Vänersborg, Sweden
Volvo Cars
Göteborg, Sweden
Volvo Group
Gothenburg, Sweden
Volvo Group
Gothenburg, Sweden
Funding
VINNOVA
Project ID: 2015-06887
Funding Chalmers participation during 2016–2019
Related Areas of Advance and Infrastructure
Sustainable development
Driving Forces
Production
Areas of Advance