European industry has recognized the importance of Artificial Intelligence (AI) tools within the context of CPES (Cyber Physical embedded Systems) since they are the keys to provide excellent services, enriched customer knowledge and also exploit new business opportunities. Cognitive production aids to achieve objectives associated with these issues concurrently providing high quality, high energy efficiency, high system availability, performance and cost effectiveness. Cognitive production is enabled by AI techniques that extract value from information related to the on-line status of assets and deploy a decision-based self-learning platform able to react dynamically. COGNINTEL application experiment aims to deploy AI-based decision making and control platform tailored to the machine tools industry to optimize their operations by enabling an holistic and intelligent Quality, Energy and Maintenance Management (QEM) approach. It provides users and plant managers with the right tools to implement cognitive production by ensuring high production efficiency, high quality, minimising the use of resources while optimising maintenance strategies, avoiding safety related failures and minimizing process downtime.
This application experiment relies on strong commitment of partners to provide innovative solutions and services to recover COVID-19 crisis within manufacturing sector. The two industrial partners are complementary to each other: SCORTA, through COGNINTEL tool, expects to deliver better products (thread cutting tools and specialised taps) and also better after-sale services, while ERREDUE (the engineering services provider) will deliver AI models for advanced diagnostics and prognostics for machine tool industry. Finally, an effective connection with relevant stakeholders as well as with DIH4CPS members is ensured by the DIH CIIRC CTU through proper communication and networking activities aimed at facilitating access to new technologies and services. CIIRC CTU will also support partners in demonstration trials to prove replicability of results towards other field of applications.