Leveraging GenAI for Enhanced Plant Performance: An OEE Case Study, TAPPICon25

Generative Artificial Intelligence (GenAI) is rapidly emerging as transformative technology in industrial digitalization, providing intuitive interfaces for accessing and analyzing plant performance data. This paper presents a case study showcasing the implementation of GenAI designed to walk users through Overall Equipment Effectiveness (OEE) metrics and provide actionable insights into plant operations. By simplifying data access and fostering engagement, the chatbot accelerates the adoption and impact of digital initiatives.

The GenAI integrates seamlessly with existing plant systems, offering real-time updates on critical OEE components: availability, performance, and quality. Through natural language processing (NLP), it allows operators, engineers, and managers to ask questions and receive instant, contextualized answers, such as identifying downtime causes, highlighting underperforming equipment, or tracking production trends.

This paper explores how GenAI enhance digital project results by bridging the gap between complex analytics and end-user accessibility. Key benefits include faster decision-making, improved data literacy among plant personnel, and increased engagement with digital tools. The interactive nature of chatbots also fosters a culture of curiosity and continuous improvement, enabling users to explore data more effectively.

The case study demonstrates how GenAI streamlined workflows, reduced troubleshooting time, and facilitated cross-functional collaboration, ultimately improving OEE and overall plant efficiency. This paper concludes with insights on best practices for GenAI implementation in industrial settings, emphasizing user-centric design and iterative development to ensure long-term success.

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