The manufacturing industry is undergoing a profound transformation driven by increasing demands for efficiency, customization, and sustainability. Although Additive Manufacturing (AM) offers significant advantages, its industrial adoption remains constrained by limitations in precision, productivity, and repeatability. Hybrid Additive Manufacturing (HAM), which integrates additive and conventional manufacturing processes, has emerged as a promising pathway to overcome these limitations. This study goes beyond descriptive literature mapping by combining bibliometric science mapping with Technology Life Cycle (TLC) modelling to analyse the evolution, technological maturity, and industrial positioning of HAM. Using a Scopus dataset and the Gompertz growth model, the study interprets publication and citation dynamics. The results indicate that HAM is currently in an early growth phase, with differentiated maturity trajectories across process families and a projected inflection point around 2030. By linking bibliometric clusters to technological maturity, the study reveals mismatches between scientific activity and industrial deployment, as well as the role of international collaboration in shaping impact and specialization. Based on this integrated analysis, the paper derives actionable research priorities and industrial implications, addressing process reliability, hybrid process planning, material–process co-optimization, and certification challenges. Rather than providing a purely descriptive overview, this study offers an analytical framework that supports strategic decision-making for researchers, industry stakeholders, and policymakers, contributing to the advancement of hybrid manufacturing technologies.
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João P.G. Magrinho
Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento
The International Journal of Advanced Manufacturing Technology
Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento
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João P.G. Magrinho (Thu,) studied this question.
synapsesocial.com/papers/69c7724e8bbfbc51511e2b5f — DOI: https://doi.org/10.1007/s00170-026-17886-0
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