Automation in manufacturing systems is rapidly changing, shifting from rigid solutions towards the use of smart technologies that better support manufacturers in meeting market demand. The implementation of these new technologies augments the complexity of managing manufacturing systems, thus necessitating the achievement of harmony between automation and human factors. Several studies have tried to summarize the latest achievements by proposing systematic reviews in the automation domain to define the state-of-the-art. However, a quantitative examination of literature metrics using statistical tools, i.e. a bibliometric analysis, is still missing in this domain, although it can complement extant studies by augmenting knowledge regarding potential future trends and research directions. Based on this, this study proposes a bibliometric analysis to analytically document the volume, intellectual structure, and knowledge development directions in the field of adaptive and adaptable automation in the manufacturing context. As a whole, 68 journal articles published in the period 2000-2023 were selected and analyzed.
Adaptive and Adaptable Automation in manufacturing: a bibliometric review / Vigoroso, L., Caffaro, F., Tronci, M., Fargnoli, M.. - In: PROCEDIA COMPUTER SCIENCE. - ISSN 1877-0509. - (2025). (6th International Conference on Industry 4.0 and Smart Manufacturing Prague, Czech Republic ) [10.1016/j.procs.2025.01.164].
Adaptive and Adaptable Automation in manufacturing: a bibliometric review
Massimo Tronci;Mario Fargnoli
2025
Abstract
Automation in manufacturing systems is rapidly changing, shifting from rigid solutions towards the use of smart technologies that better support manufacturers in meeting market demand. The implementation of these new technologies augments the complexity of managing manufacturing systems, thus necessitating the achievement of harmony between automation and human factors. Several studies have tried to summarize the latest achievements by proposing systematic reviews in the automation domain to define the state-of-the-art. However, a quantitative examination of literature metrics using statistical tools, i.e. a bibliometric analysis, is still missing in this domain, although it can complement extant studies by augmenting knowledge regarding potential future trends and research directions. Based on this, this study proposes a bibliometric analysis to analytically document the volume, intellectual structure, and knowledge development directions in the field of adaptive and adaptable automation in the manufacturing context. As a whole, 68 journal articles published in the period 2000-2023 were selected and analyzed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
