Adaptive lifecycle design by applying digitalization and AI techniques to production - Adapt 2030

Status:

active

Start date:

2020-07-01

End date:

2023-02-28

Deviation occurs in all steps of a product lifecycle; e.g., production, transport and
operations. Today, many manufacturers have access to an enormous amount of data from
the whole lifecycle, which is under-utilised. Despite proven digital and AI (artificial
intelligence) techniques, and lifecycle engineering (LCE) methods, the application of
these in combination in industrial practice is scarce. Continuously reducing deviations
both reactively and proactively with a lifecycle perspective will have a significant
economic and environmental gain.
The project will develop a method and two demonstrators as “proof of concept” showing
the process and value of lifecycle digitalization, by applying AI techniques to data for
reducing deviations. Two value chains will be addressed; gas turbines and production
machines. The data related to deviation collected from the full lifecycle will be used to
derive insights for continuous improvements including design of next-generation
products.
The major expected impacts for industry will be improved cost efficiency as well as
capacity and competitiveness concerning the next level of digitalization with strategic use
of AI. Environmental performance including resource efficiency will also be increased.
Linköping University will be the coordinator and provide expertise on LCE. Mälardalen
University and the Swedish National Road and Transport Research Institute will provide
expertise on AI and transport, respectively. Two large firms will provide cases that
together cover a wide range of value chains for production: Siemens Industrial
Turbomachinery and Volvo Construction Equipment. In addition, a number of companies
will provide leading edge expertise to the demonstrators.

Peter Funk, Professor

Email: peter.funk@mdh.se
Room: U1-126
Phone: +46-21-103153