Abstract
The digitization of industrial operations and manufacturing has transformed factories through automation and model-based approaches, driving advancements in areas like additive manufacturingAdditive manufacturing, augmented reality, and simulation. While these technologies have significantly enhanced industrial processes, artificial intelligence (AI)Artificial Intelligence (AI) has yet to be fully integrated as a central component. Emphasizing the importance of human involvement alongside technological innovation, AI applications are particularly vital in areas such as roboticsRobotics, where human-centricHuman-Centric AI approaches are key. Despite its widespread use in consumer-focused services, trust in AI remains a major concern in industrial settings. Initiatives such as the European Union’s Trustworthy AITrustworthy AI guidelines and the EU Act aim to foster trust in AI while ensuring ethical implementation and worker safety. However, many organizations remain unaware of the need for specific approaches to effectively address trust concerns in AI systems. This work explores the principles required for building trustworthy AITrustworthy AI systems for industrial operations and manufacturing and challenges of trustworthy AI.
| Original language | English |
|---|---|
| Title of host publication | Springer Series in Advanced Manufacturing |
| Pages | 179-197 |
| Number of pages | 19 |
| DOIs | |
| Publication status | Published (in print/issue) - Mar 2025 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Keywords
- AI Fairness
- Explainable AI
- Industry 5.0
- Smart Manufacturing
- Trustworthy AI