Cognitive Advisor Service
Assistance for on-the-job-training of factory workers
Cognitive Advisor Service aims to support operators in troubleshooting, facilitate on-the-job training for novices, and provide production analytics to production managers. This service allows easy access to relevant training material, knowledge, and insights through the mobile app’s text, voice, and graphical user interface.
The Cognitive Advisor can acquire knowledge from expert users to facilitate the update of the training material. These cognitive capabilities are made possible by the Cognitive Advisor’s context awareness in combination with its mapping of human-understandable concepts in its knowledge representation.
The Cognitive Advisor offers four main features:
AI-Powered Cognitive Advisor for Knowledge Discovery and Transfer
Tacit knowledge discovery and storage in a knowledge base
On-the-job training for novice operators
Context-aware cognitive assistance
The COALA Digital Intelligent Assistant functions connect with the cognitive advisor service that accesses shop-floor data (e.g., machinery location, production rates, production issues) and adapts the learning progress to the user. For example, a novice worker can interact with the COALA cognitive assistant in natural language and request solutions to problems based on knowledge collected from the experienced workers. This will enable machine operators and production-line managers to become effective faster, which will speed up changes in manufacturing (e.g., agile manufacturing).
Complementary to the technology, we are also developing an education and training concept that focuses on building blue-collar worker competencies in human-AI collaboration. Ultimately, the COALA solution will transform how workers perform their jobs while enabling companies to maintain, or even increase, the quality of their production processes and their products.
Kernan Freire, S., Surendranadha Panicker, S., Ruiz-Arenas, S., Rusak Z., & Niforatos, E. (2022). A Cognitive Assistant for Operators: AI-Powered Knowledge Sharing about Complex Systems. Submitted to IEEE Pervasive, Special Issue on Human-Centred.
Kernan Freire, S., Niforatos, E., Rusak, Z., Aschenbrenner, D., & Bozzon, A. (2022). A Conversational User Interface for Maintenance Reports: A Wizard of Oz Study. Submitted to the 4th International Conference on Conversational User Interfaces (CUI 2022), ACM.
Foosherian, M., Kernan Freire, S., Niforatos, E., A. Hribernik, K., & Thoben, K. (2022). Whose Job is it? Handling the Learning Burden of Divergent Phrasing to Minimize Conversational Breakdowns when Interacting with Conversational Agents. Submitted to the 4th International Conference on Conversational User Interfaces (CUI 2022), ACM.