Trustworthy Artificial Intelligence for Industrial Operations and Manufacturing: Principles and Challenges

Md Alamgir Kabir, M. M. Manjurul Islam

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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 languageEnglish
Title of host publicationSpringer Series in Advanced Manufacturing
Pages179-197
Number of pages19
DOIs
Publication statusPublished (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

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