Creative Destruction and Technological Paradigms in Manufacturing: A Large-Scale Review and Framework for Technology Portfolio Assessment

Manufacturing digitalization and automation research has expanded rapidly over the past decades. However, the current literature often presents fragmented views, lacking a comprehensive understanding of its evolution. Due to the vast number of publications, traditional literature reviews are impractical for broad fields like manufacturing digitalization and automation. This study leverages recent advancements in Artificial Intelligence (AI), Large Language Models (LLMs), and Natural Language Processing (NLP) to analyze 31,914 scientific papers from 1970 to 2023, providing a knowledge structure of the field. Moreover, we provide a roadmap of the field's evolution using Dynamic Topic Modeling (DTM). We note emerging trends in energy efficiency (since 2004), composite materials (2006), cybersecurity (2008), robotics (2014), and AI (2016), while simulation, scheduling, and process planning maintain steady and consistent research interests. Additionally, we observe a decay in certain research areas such as manufacturing automation protocol, a once-prominent area in the 1980s introduced by General Motors. We introduce a technology portfolio assessment framework categorizing technologies into Emerging, Established, Experimental, and Decaying quadrants. The proposed framework is based on the findings of this study, technology life cycle, creative destruction, and technological paradigms theories. The findings also offer insights into thematic shifts across the literature, consistent with creative destruction and technological paradigm theories. These findings hold implications for academia, industry, and policymakers, supporting more strategic innovation and resource allocation in the manufacturing sector.