Project description
A cutting-edge intelligent assistant for training in manufacturing
Europe is currently experiencing a shortage of skilled workers in sectors like textile manufacturing. The solution is effective training to upgrade the skills of new workers. However, for many companies, the costs of such training sessions are prohibitive. The EU-funded COALA project will design and develop a cutting-edge Digital Intelligent Assistant for the manufacturing sector. At its core is the privacy-focused, open-source voice assistant, Mycroft. COALA will integrate, for instance, augmented quality analytics, an experimental mechanism for explainable AI, and features for the assistance of on-the-job training. An AI-focused change management process and guidelines for professional worker education will complement the technical work. The project will significantly decrease the costs of failures in manufacturing and will reduce training time for workers.
Objective
Humans are at the center of knowledge-intensive manufacturing processes. They must be skilled and flexible to meet the requirements of their work environment. The training of new workers in these processes is time consuming and costly for companies. Industries, such as the Italian textile sector suffer from the shortage of skilled workers caused, e.g. by the demographic change. A second challenge for the manufacturing sector is the continuous competition through high quality products. COALA will address both challenges through the innovative design and development of a voice-first Digital Intelligent Assistant for the manufacturing sector. The COALA solution will base on the privacy-focused open assistant Mycroft. It integrates prescriptive quality analytics, AI system to support on-the-job training of new workers, and a novel explanation engine - the WHY engine. COALA will address AI ethics during design, deployment, and use of the new solution. Critical components for the adoption of the solution are a new didactic concept to reach workers about opportunities, challenges, and risks in human-AI collaboration, and a concurrent change management process. Three use cases (textile, white goods, liquid packaging) will evaluate the results in common manufacturing processes with significant economic relevance. COALA will contribute its results to the European AI community, e.g. via the AI4EU platform, and it will involve Digital Innovation Hubs to replicate its demonstrators for Europes first trustworthy digital assistant for the manufacturing industry. We expect to reduce the failure cost in manufacturing by 30-60% with the prescriptive quality analytics feature and the assisted worker training. For the change over time we expect a reduction of 15% to 30% by shortening the worker training time.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencesartificial intelligence
- engineering and technologymechanical engineeringmanufacturing engineering
- social scienceseconomics and businessbusiness and managementinnovation management
- social sciencessociologydemography
- engineering and technologymaterials engineeringtextiles
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
28359 Bremen
Germany