Adapt 2030
| Reference number | |
| Coordinator | Linköpings universitet - Linköpings tekniska högskola Inst f fysik kemi & biologi IFM |
| Funding from Vinnova | SEK 9 248 108 |
| Project duration | March 2020 - August 2023 |
| Status | Completed |
| Venture | The strategic innovation programme for Production2030 |
Purpose and goal
The project aimed to develop a vision, a proof of concept, a method, and concrete use cases showing the process and value of AI (artificial intelligence) application for environmental sustainability (on the context of lifecycle engineering), especially in applying AI techniques to data for reducing deviations in product development and production. The cases provided by industry partners from the Swedish manufacturing industry were used to demonstrate the AI applications (e.g., natural language processing and ontology).
Expected effects and result
The vision, knowledge gaps, state of the art, method, and use case that this project provided were peer reviewed by relevant scientific communities and published on academic journals / conferences. These results were disseminated via a white paper, videos, and online meetings to industry. The major expected impacts for industry are improved cost efficiency as well as capacity, network, and competitiveness concerning the next level of digitalization with strategic use of AI. Environmental performance including resource efficiency will also be increased.
Planned approach and implementation
The project adapted to partners’ situations and adjusted activities to a minor extent during the execution. The case with deviation in product design contributed to develop the proof of concept that was validated with the use case from production. The environmental assessment task helped industry partners with a widely applicable template instead of quantitative case work requiring extensive data collection. Overall, despite the corona crisis, the project was carried out to produce the results as a whole on the expected level, including spontaneous deliverables.