Computer Vision in Manufacturing: A Bibliometric Analysis and future research propositions

Abstract

Abstract Computer vision simulates human capabilities and automates the tasks. Its application within the manufacturing context has garnered ample attention and interest from both academics and practitioners. Due to its large-scale applicability and adoption potential, extensive research has been conducted to understand and appreciate it’s working. However, extant research in this domain is rather disjointed, thereby delimiting the otherwise vast scope and knowledge boundaries. Therefore, this study utilizes bibliometric analysis to synthesize extant literature within this field to address this lacuna. This research analyzed 897 articles from Scopus, entailing contributions from 309 journals, 108 countries, 2138 authors and 1334 organizations from 1981 to 2022. Additionally, citation and co-authorship networks are also analyzed to acknowledge prominent authors, organizations, and countries within this domain. The thematic classification of extant literature through bibliographic coupling identified five major thematic areas: automated visual inspection, object tracking and process controlling, real-time monitoring, roughness inspection and profile projection. Importantly, the study uses both knowledge and insights from our findings and scope for future research.