Proposal ID: 957296
ICCS project ID: 63114700
Role: Partner
Acronym: COALA
Topic: ICT-38-2020
Type of action: RIA
Call identifier: H2020-ICT-2018-20

COALA: COgnitive Assisted agile manufacturing for a LAbor force supported by trustworthy Artificial Intelligence

Duration in months: 36
Fixed keyword 1: Artificial intelligence, intelligent systems, multi agent systems
Fixed keyword 2: Artificial Intelligence & Decision support
Fixed keyword 3: Ergonomic and Human factors
Free keywords: Digital Voice Assistants, Augmented Analytics, AI Ethics, Explainable AI

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.

Lab URL: http://imu.ntua.gr/wp
Project URL: https://www.coala-h2020.eu