An AI-Driven User-Centric Framework reinforced by Autonomic Computing: A case study in the Aluminium sector

Abstract

The integration and deployment of AI in the industry faces several challenges, involving not only the need for robust and accurate AI models, but also their seamless integration with existing systems, while ensuring an intuitive user experience for workers. Furthermore, it is critical for AI solutions to be continuosly managed for data governance, performance optimization, and the mitigation of risks, among other factors. This paper presents a service-oriented application that explores the integration of Machine Learning algorithms by adopting Human-in-the-Loop (HITL) strategies to enhance user-technology interactions in an Aluminium industrial environment. The proposed application exploits the use of data-driven Autonomic Computing techniques in AI Data Pipelines to promote the development of self-managed, adaptive systems that support dynamic interactions between technology and workers. Through the implementation of a web interface, workers are provided with seamsless access to real-time data analysis and intelligent solutions within the user-empowered application.

Keywords: Artificial Intelligence, Autonomic Computing, AI Data Pipeline, Human-Centric Design, Human-In-The-Loop (HITL)

DOI: 10.54941/ahfe1005478