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Research project(s): s-X-AIPI

Keywords

Cognitive Manufacturing System; Artificial Intelligence (AI); Human in the Loop (HITL); Autonomic Computing; Electric Arc Furnace (EAF); Process Industry; Data-driven Systems; Circular Economy; Green Transformation

Abstract

The introduction of Self-X capabilities into industrial control offers a tremendous potential in the development of resilient, adaptive production systems that enable circular economy. The Self-X capabilities, powered by Artificial Intelligence (AI), can monitor the production performance and enable timely reactions to problems or suboptimal operation. This paper presents a concept and prototype for Self-X AI in process industry, particularly electric steelmaking with the EAF (Electric Arc Furnace). Due to complexity, EAF operation should be optimized with computational models, but these suffer from the fluctuating composition of the input materials, i.e., steel scrap. The fluctuation can be encountered with the Self-X method that monitors the performance, detecting anomalies and suggesting the re-training and re-initialization of models. These suggestions support the Human-in-the-Loop (HITL) in managing the AI models and in operating the productions processes. The included Self-X capabilities are self-detection, self-evaluation and self-repair. The prototype proves the concept, showing how the optimizing AI pipeline receives alarms from the external AI services if the performance degrades. The results of this work are encouraging and can be generalized especially to processes that encounter drift related to the conditions, such as input materials for circular economy.