Abstract
Despite the widespread adoption of Industry 4.0 (I4.0) technologies, the fragmentation of existing research limits our understanding of their technological interdependencies, industrial applications, and implementation challenges. This study presents a systematic literature review (SLR), conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 framework to critically examine the principal enabling technologies underpinning intelligent manufacturing. Literature searches were conducted in Scopus, Web of Science (WoS), and CrossRef up to September 2025, complemented by metadata verification through Dimensions.ai. Following screening, eligibility assessment, and methodological quality evaluation, 193 publications were retained for qualitative synthesis. The findings identify two interconnected technological domains: information and communication technologies, encompassing the Internet of Things (IoT), Big Data Analytics (BDA), Artificial Intelligence (AI), and cloud–edge computing; and manufacturing-oriented technologies, including robotics, automation, additive manufacturing (AM), and cyber–physical production systems. Their integration supports predictive maintenance, intelligent quality assurance, adaptive production, and supply-chain optimisation, although interoperability limitations, cybersecurity vulnerabilities, legacy-system integration, and workforce skills shortages continue to constrain industrial deployment. The review further identifies IoT-centric, edge–cloud, and AI-augmented architectures as key patterns of technological convergence. These findings provide an integrated perspective on I4.0 implementation and its emerging implications for the human-centricity, sustainability, and resilience objectives of Industry 5.0 (I5.0).