A Cognitive Assistant for Operators: AI-Powered Knowledge Sharing on Complex Systems

被引:7
|
作者
Freire, Samuel Kernan [1 ]
Panicker, Sarath Surendranadha [2 ]
Ruiz-Arenas, Santiago [3 ]
Rusak, Zoltan [1 ]
Niforatos, Evangelos [1 ]
机构
[1] Delft Univ Technol, NL-2628 CD Delft, Netherlands
[2] Cognizant Technol Solut, NL-1096 BK Amsterdam, Netherlands
[3] Univ EAFIT, Medellin 3300, Antioquia, Colombia
基金
欧盟地平线“2020”;
关键词
Production facilities; Artificial intelligence; Training; Manufacturing; Machine components; Cameras; Best practices; TACIT KNOWLEDGE;
D O I
10.1109/MPRV.2022.3218600
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Operating a complex and dynamic system, such as an agile manufacturing line, is a knowledge-intensive task. It imposes a steep learning curve on novice operators and prompts experienced operators to continuously discover new knowledge, share it, and retain it. In practice, training novices is resource-intensive, and the knowledge discovered by experts is not shared effectively. To tackle these challenges, we developed an AI-powered pervasive system that provides cognitive augmentation to users of complex systems. We present an AI cognitive assistant that provides on-the-job training to novices while acquiring and sharing (tacit) knowledge from experts. Cognitive support is provided as dialectic recommendations for standard work instructions, decision-making, training material, and knowledge acquisition. These recommendations are adjusted to the user and context to minimize interruption and maximize relevance. In this article, we describe how we implemented the cognitive assistant, how it interacts with users, its usage scenarios, and the challenges and opportunities.
引用
收藏
页码:50 / 58
页数:9
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