EXPlainable and Learning production & logistics by Artificial INtelligence (EXPLAIN)
| Reference number | |
| Coordinator | Uppsala universitet - Uppsala universitet Institutionen för materialvetenskap |
| Funding from Vinnova | SEK 6 000 000 |
| Project duration | April 2021 - April 2024 |
| Status | Ongoing |
| Venture | The strategic innovation programme for Production2030 |
| Call | SIP Produktion2030, call 13 |
Purpose and goal
The aim of the EXPLAIN is to increase the profitability, sustainability, and competitiveness of the Swedish manufacturing industry. The project conducts research & development of a new generation of interactive and innovative fusion of virtual production modeling methods and machine learning algorithms for decision-making support and increasing knowledge within the production systems lifecycle. It will target cases on production planning and control with humans-in-the-loop, wherein complex multi-criteria decisions are to be made, including energy & resource efficiency.
Expected results and effects
The EXPLAIN project brings into a paradigm that emphasizes the human-machine co-learning through transferability of preferences/values and knowledge between human and machine within a multi-objective (productivity and sustainability) optimization context and hence will provide a unique, long-term contribution to knowledge-driven industry in Sweden. Fully in-line with other worldwide Learning Factories efforts, the human-machine symbiosis framework proposed can in the long-term increase the sustainability and competitiveness of the Swedish manufacturing industry.
Planned approach and implementation
The main implementation approach adopted by EXPLAIN is application case studies connected to a total of 6 work packages, led by the two universities, MainlyAI and RISE, wherein the four industrial partners from four different sectors will have the lead in choosing the focus of each study to secure industrial relevance within the different WPs. The learning model will be according to double-loop learning, i.e., internal development at each partner is going on, and progress is being assessed against input from other partners, thus providing new energy into each development process.