Machine Tool Interoperability in Smart Manufacturing and Industry 4.0

Real-time decision making is supported by data-hungry emerging technologies such as machine learning and digital twins. Innovations in manufacturing process control utilizing these technologies are constrained by interoperability. Marketing materials, sales pitches, and academic literature portray interoperability on the factory floor as seamless and robust. However, this study demonstrates that in spite of plentiful mature standards, interoperability on the factory floor is neither seamless nor robust. To exemplify interoperability in the context of an established and widely adopted standard, this study analyzes the interoperability of machine tools produced by a premier equipment builder which has exceeded US$1 billion in sales with more than 200,000 machines currently in operation worldwide. Through demonstrating and discussing non-interoperability and influencing factors, this study aims to provide insights and actionable intelligence applicable to industry and academia for laymen, end users, systems integrators, standards organizations, equipment builders, and data scientists. By leveraging phronesis and empirical evidence to demonstrate the state of interoperability, this study provides a fresh perspective on an age-old manufacturing challenge.

Authors

Publication Details

Journal
Scholar Commons (University of South Carolina)
Published
2025-07-11
DOI
https://doi.org/10.1109/access.2025.3585766/">https://doi.org/10.1109/access.2025.3585766</a></p
Primary Topic
Digital Transformation in Industry
Type
article
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article

Machine Tool Interoperability in Smart Manufacturing and Industry 4.0

Mohammed Shafae, M. R. Mccormick, Thorsten Wuest
Scholar Commons (University of South Carolina)
Digital Transformation in Industry
article

Machine Tool Interoperability in Smart Manufacturing and Industry 4.0

Mohammed Shafae, M. R. Mccormick, Thorsten Wuest
article en

Abstract

Real-time decision making is supported by data-hungry emerging technologies such as machine learning and digital twins. Innovations in manufacturing process control utilizing these technologies are constrained by interoperability. Marketing materials, sales pitches, and academic literature portray interoperability on the factory floor as seamless and robust. However, this study demonstrates that in spite of plentiful mature standards, interoperability on the factory floor is neither seamless nor robust. To exemplify interoperability in the context of an established and widely adopted standard, this study analyzes the interoperability of machine tools produced by a premier equipment builder which has exceeded US$1 billion in sales with more than 200,000 machines currently in operation worldwide. Through demonstrating and discussing non-interoperability and influencing factors, this study aims to provide insights and actionable intelligence applicable to industry and academia for laymen, end users, systems integrators, standards organizations, equipment builders, and data scientists. By leveraging phronesis and empirical evidence to demonstrate the state of interoperability, this study provides a fresh perspective on an age-old manufacturing challenge.

Scholar Commons (University of South Carolina)
Industry, innovation and infrastructure
Openalex Percentile: Top 28%
Digital Transformation in Industry
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