Periodic Reporting for period 2 - knowlEdge (Towards AI powered manufacturing services, processes, and products in an edge-to-cloud-knowlEdge continuum for humans [in-the-loop])
Okres sprawozdawczy: 2022-07-01 do 2024-03-31
knowlEdge tackles challenges in AI integration for manufacturing, addressing complexity, skill shortages, and market dynamics. It aims to enhance business sustainability and operational efficiency by overcoming barriers to AI adoption.
Addressing AI barriers is vital for societal and economic transformation. AI is pivotal in the fourth industrial revolution, revolutionizing manufacturing, optimizing resources, and spurring innovation. The knowlEdge project aims to overcome these obstacles, empowering industries for competitiveness, market adaptation, and sustainable growth.
The knowlEdge project aims to develop AI methods and infrastructure for manufacturing. It simplifies AI integration, ensures secure data management, and facilitates model exchange. Ultimately, it empowers industries to harness AI's potential for innovation and competitiveness.
The knowlEdge project successfully developed innovative AI solutions for manufacturing and process industries. It achieved major innovations in AI-centric software, deployment models, knowledge marketplaces, and secure communication infrastructure. The project simplified AI integration, making it accessible to industries with varying expertise levels. Efficient communication and data management infrastructure enabled effective utilization of data assets. User-friendly applications demonstrated feasibility in real-world scenarios. Effective communication ensured stakeholders were informed about project outcomes and potential industry impact.
Addressing AI barriers is vital for societal and economic transformation. AI is pivotal in the fourth industrial revolution, revolutionizing manufacturing, optimizing resources, and spurring innovation. The knowlEdge project aims to overcome these obstacles, empowering industries for competitiveness, market adaptation, and sustainable growth.
The knowlEdge project aims to develop AI methods and infrastructure for manufacturing. It simplifies AI integration, ensures secure data management, and facilitates model exchange. Ultimately, it empowers industries to harness AI's potential for innovation and competitiveness.
The knowlEdge project successfully developed innovative AI solutions for manufacturing and process industries. It achieved major innovations in AI-centric software, deployment models, knowledge marketplaces, and secure communication infrastructure. The project simplified AI integration, making it accessible to industries with varying expertise levels. Efficient communication and data management infrastructure enabled effective utilization of data assets. User-friendly applications demonstrated feasibility in real-world scenarios. Effective communication ensured stakeholders were informed about project outcomes and potential industry impact.
The knowlEdge project aimed to address challenges in integrating AI technologies in manufacturing. Work performed focused on user-centric design, evolutionary requirement engineering, and analysis to inform platform development. Key milestones included delivering the knowlEdge platform architecture and integrating features like knowledge discovery and edge AI orchestration. The project developed tools for semi-automatic data preparation, automatic AI model generation, and human-AI collaboration to streamline processes and enhance decision-making. A prototype knowledge discovery engine improved data quality and reduced costs, while the knowlEdge Marketplace revolutionized AI model accessibility and security in manufacturing.
Significant work focused on data management, integration, and governance, developing frameworks for data collection and ensuring robust security mechanisms. Edge data management services efficiently handled historical and live data. The project finalized digital twin methodology, developed digital twins for pilot processes, and enhanced security measures. Success indicators included improved operator satisfaction, enhanced production planning, and decision-making support. Parmalat, Kautex-Textron, and Bonfiglioli optimized processes and reduced false product rates, showcasing AI's potential in advancing manufacturing.
Dissemination efforts included publishing scientific articles, conducting workshops, and developing business models for industry partners. Exploitation strategies and IPR management were finalized for post-project sustainability. Collaborative efforts with ICT-38 projects enhanced synergy, facilitating knowledge sharing in AI for manufacturing.
The project introduced innovations such as agile software architecture, data collection spanning edge-fog-cloud continuum, and AI-driven Decision Support System. Commercial exploitation potential was explored, with business plans developed for commercially exploitable key results. These efforts promise significant advancements in AI for manufacturing, bridging the gap between technological innovation and industrial application.
Significant work focused on data management, integration, and governance, developing frameworks for data collection and ensuring robust security mechanisms. Edge data management services efficiently handled historical and live data. The project finalized digital twin methodology, developed digital twins for pilot processes, and enhanced security measures. Success indicators included improved operator satisfaction, enhanced production planning, and decision-making support. Parmalat, Kautex-Textron, and Bonfiglioli optimized processes and reduced false product rates, showcasing AI's potential in advancing manufacturing.
Dissemination efforts included publishing scientific articles, conducting workshops, and developing business models for industry partners. Exploitation strategies and IPR management were finalized for post-project sustainability. Collaborative efforts with ICT-38 projects enhanced synergy, facilitating knowledge sharing in AI for manufacturing.
The project introduced innovations such as agile software architecture, data collection spanning edge-fog-cloud continuum, and AI-driven Decision Support System. Commercial exploitation potential was explored, with business plans developed for commercially exploitable key results. These efforts promise significant advancements in AI for manufacturing, bridging the gap between technological innovation and industrial application.
The knowlEdge project has made substantial progress in advancing beyond the state of the art. Employing a diverse range of pilot cases across various industries, the project addresses different manufacturing processes, reflecting a comprehensive analysis of user needs and requirements. The platform's open architecture and marketplace exchange capability facilitate enhanced agility in production processes, offering tailored AI/ML models for Industry 4.0/5.0 applications like time series forecasting and computer vision.
This agile approach is reinforced by user need analysis and iterative requirement engineering, ensuring adaptability to evolving industry demands. Core functionalities for knowledge capturing and analytics enable swift decision-making and process optimization. Tasks such as "Knowledge Discovery for AI Model Generation" and "Edge AI Learning Pipeline Orchestration" enable rapid deployment of AI models, empowering manufacturers to adapt swiftly to market dynamics.
Adopting a human-centered design methodology, the project emphasizes human-AI collaboration and domain knowledge fusion, enhancing data understanding and evaluation of the entire AI pipeline. Technology components like the Decision Support System utilize historical pilot data and AI/ML models to support decision-making, actively involving end-users in the process.
The platform architecture enables seamless collaboration between humans and AI, fostering the adoption of AI and facilitating adaptation to evolving organizational structures. Efforts are made to enhance human-AI collaboration through XAI services, ensuring visibility of AI outcomes to humans.
The knowlEdge project enhances partners' absorptive capacity, fostering technological insights, cross-collaboration, and continuous learning. Market understanding is expanded through AI application exploration and market trend tracking, ensuring partners remain responsive.
Strategic initiatives maximize exploitation, managing intellectual property rights and mapping value roadmaps. Tailored exploitation strategies cater to commercial, scientific, and internal pathways, driving innovation and long-term sustainability.
Emphasizing post-project utilization, the project prioritizes building user trust through GDPR-compliant and transparent solutions. Security measures, including Blockchain technology, ensure trust in transactions and data security.
Throughout its duration, knowlEdge has effectively addressed industrial challenges, resulting in streamlined workflows, improved product quality, and optimized operations. Tangible benefits include increased competitiveness and enhanced productivity across sectors.
The project drives significant economic impacts by introducing advanced AI technologies, enhancing automation, and fostering innovation. It empowers European firms to maintain leadership positions globally, contributing to the EU's economic prosperity.
Pioneering AI in manufacturing, knowlEdge integrates human expertise through a novel AI pipeline, aiding human-AI collaboration and promoting transparency and ethics. Validation across various sectors demonstrates adaptability, with future steps focusing on compatibility and refinement for widespread adoption.
Furthermore, the project minimizes environmental impacts by optimizing processes and reducing waste generation, aligning with EU Twin Transition goals. Lastly, knowlEdge significantly impacts employment, fostering job creation, reskilling, and entrepreneurship opportunities, supporting sustainable development goals.
This agile approach is reinforced by user need analysis and iterative requirement engineering, ensuring adaptability to evolving industry demands. Core functionalities for knowledge capturing and analytics enable swift decision-making and process optimization. Tasks such as "Knowledge Discovery for AI Model Generation" and "Edge AI Learning Pipeline Orchestration" enable rapid deployment of AI models, empowering manufacturers to adapt swiftly to market dynamics.
Adopting a human-centered design methodology, the project emphasizes human-AI collaboration and domain knowledge fusion, enhancing data understanding and evaluation of the entire AI pipeline. Technology components like the Decision Support System utilize historical pilot data and AI/ML models to support decision-making, actively involving end-users in the process.
The platform architecture enables seamless collaboration between humans and AI, fostering the adoption of AI and facilitating adaptation to evolving organizational structures. Efforts are made to enhance human-AI collaboration through XAI services, ensuring visibility of AI outcomes to humans.
The knowlEdge project enhances partners' absorptive capacity, fostering technological insights, cross-collaboration, and continuous learning. Market understanding is expanded through AI application exploration and market trend tracking, ensuring partners remain responsive.
Strategic initiatives maximize exploitation, managing intellectual property rights and mapping value roadmaps. Tailored exploitation strategies cater to commercial, scientific, and internal pathways, driving innovation and long-term sustainability.
Emphasizing post-project utilization, the project prioritizes building user trust through GDPR-compliant and transparent solutions. Security measures, including Blockchain technology, ensure trust in transactions and data security.
Throughout its duration, knowlEdge has effectively addressed industrial challenges, resulting in streamlined workflows, improved product quality, and optimized operations. Tangible benefits include increased competitiveness and enhanced productivity across sectors.
The project drives significant economic impacts by introducing advanced AI technologies, enhancing automation, and fostering innovation. It empowers European firms to maintain leadership positions globally, contributing to the EU's economic prosperity.
Pioneering AI in manufacturing, knowlEdge integrates human expertise through a novel AI pipeline, aiding human-AI collaboration and promoting transparency and ethics. Validation across various sectors demonstrates adaptability, with future steps focusing on compatibility and refinement for widespread adoption.
Furthermore, the project minimizes environmental impacts by optimizing processes and reducing waste generation, aligning with EU Twin Transition goals. Lastly, knowlEdge significantly impacts employment, fostering job creation, reskilling, and entrepreneurship opportunities, supporting sustainable development goals.