EXPlainable and Learning production & logistics by Artificial INtelligence (EXPLAIN)

About the project

The overall aim of the EXPLAIN project is to increase the profitability, sustainability, and competitiveness of the Swedish manufacturing industry. The project conducts research and development to enable the next-generation of energy-efficient, connected and learning factories using a new fusion of virtual production and explainable machine learning innovations for decision-making support within the production systems lifecycle.

EXPLAIN will target cases on production planning and control with humans-in-the-loop, wherein complex multi-criteria decisions are to be made, including energy and resource efficiency. Unlike many other research efforts within virtual production.

EXPLAIN aims at delivering three unique innovations:

(1) automatic virtual model generation with real-time connections to data sources and modeling sub-modules that consider energy and resource efficiency factors via process mining and self-reconfigurable modeling methods to further reduce the hurdle and lead-time of using virtual production technologies in the industry.

(2) explainable and trustable AI algorithms and user interfaces for decision-makers, not only for informed, optimal, and confident decisions but also for increasing their knowledge and competence.

(3) knowledge management using knowledge graphs to link virtual production artifacts to enable them to be searchable, retrievable, and efficiently reusable by human users.

EXPLAIN sees an innovative combination of virtual production technologies and AI algorithms can provide a unique way to the increased access to new knowledge and skills in the production area, which is not possible with the current industrial practice of applying virtual production technologies alone.