We are pleased to announce the newsletter for the first year of the EU project knowlEdge.
Looking back on the last year, the knowlEdge project, whose aim is to develop a new generation of AI methods, systems, and data management infrastructure, has successfully launched with 12 partners from across 7 EU countries. Due to the pandemic situation, the project’s kick-off meeting was conducted in a digital manner with participation of all consortium partners.
The kick-off meeting was successfully conducted in a way that the project’s main vision and objective, which is to boost industries towards agile and flexible strategies, able to respond to the fast-changing customers’ needs, and at the same time to optimize their processes and quality control mechanisms, has been discussed extensively along the individual work packages and in addition to other administrative and organizational aspects.
Followed by several project internal workshops, the individual requirements and user needs has been discussed together with the different industrial pilot partners. As a results, we have envisioned six fundamental types of AI-based enhancements, that will be followed throughout the knowlEdge project:
Product Quality: Predictive quality control and continuous AI-based inspection/analysis in collaboration with humans
Process Quality: Digital Twin, i.e. simulation of physical world with integrated AI, as well as continuous and intelligent process optimization with AI models
Process Planning & Scheduling: Dynamic and real-time process Planning using AI-based multi-criteria optimization techniques and Adaptive Scheduling
Flexibility of manufacturing industries towards a rapidly changing market: Employing agile processes, fostering reusability of knowledge and AI models, and transparent sharing of proven models via interoperable standards.
Human – Machine interaction: Explainable AI enabling non-experts to use AI tools, and dynamic task allocations between AI tools & humans.
Data & Intelligent technologies: Smart and frugal AI algorithms, distributed computing model, and deployment of AI models alongside the Cloud-Edge continuum.
In addition to this internal workshop series, the knowledge project participated in different external workshops and seminars. Prof. Christian Beecks gave a talk about AI powered manufacturing services, processes, and products in the knowlEdge project at the international workshop on Explainable Artificial Intelligence in Manufacturing. This online workshop took place in the AI-MAN cluster. In addition, Stefan Walter gave a presentation on AI driven manufacturing processes in the knowlEdge project: relations to supply chains at the ALICE seminar on Artificial Intelligence in planning, simulation and forecasting. He also acted as an invited expert on a manufacturing exploitation workshop organized by the EU project IntellIOT.
Another highlight of was the visiting of the Kautex demonstrator. Due to the ongoing Covid19 situation across Europe, it was not possible to invite the technical project partners to the Kautex manufacturing plant in Belgium. Instead, the Kautex team prepared and conducted a virtual tour supported by a HoloLens, presenting and explaining the production line. This way the technical partners could get an impression of the physical dimensions of the blow molding machines, which reach up to 12x12x8m, as well as the single steps needed in the production process and its overall complexity.
From a scientific perspective, the knowledge has achieved several scientific publications, which can be found online on the project website. One major aim was to create a joint paper summarizing the concept, methodology and innovations of the knowlEgde project. This joint paper has been accepted to the IEEE International Conference on Industrial Informatics (INDIN 2021) and can be found online here. Other relevant papers have also been published at top-tier conferences including IEEE International Conference on Data Mining (ICDM 2021), International Conference on Scientific and Statistical Database Management (SSDBM 2021), as well as IEEE International Conference on Big Data (Big Data 2021).
We look forward to sharing future highlights and project outcomes with you and we value any feedback you might have.