Research Article
Reviewing Manufacturing Execution System in Industry 4.0: A Global Approach
@ARTICLE{10.4108/dtip.9768, author={Teresa Dieguez and Jos\^{e} Machado}, title={Reviewing Manufacturing Execution System in Industry 4.0: A Global Approach}, journal={EAI Endorsed Transactions on Digital Transformation of Industrial Processes}, volume={1}, number={3}, publisher={EAI}, journal_a={DTIP}, year={2025}, month={8}, keywords={Manufacturing Execution Systems (MES), Industry 4.0, IoT, AI, Cyber-Physical Systems, Smart Manufacturing}, doi={10.4108/dtip.9768} }- Teresa Dieguez
José Machado
Year: 2025
Reviewing Manufacturing Execution System in Industry 4.0: A Global Approach
DTIP
EAI
DOI: 10.4108/dtip.9768
Abstract
INTRODUCTION: Manufacturing Execution Systems (MES) have evolved from basic production tracking tools into intelligent, AI-driven platforms integrated with IoT, cloud computing, and cyber-physical systems. In the context of Industry 4.0, MES play a key role in enabling real-time decision-making and operational efficiency. However, research in this field remains fragmented, with ongoing challenges related to interoperability, cybersecurity, and system integration. OBJECTIVES: This study aims to map the MES research landscape within Industry 4.0 through a systematic literature review and bibliometric analysis. It identifies core research themes, technological trends, and persistent challenges, offering insights to guide future developments in MES. METHODS: A Systematic Literature Review (SLR) was conducted using the Scopus database, applying specific search terms and strict inclusion/exclusion criteria. A total of 47 peer-reviewed articles (2010–2024) were analysed using VOSviewer to perform co-authorship, bibliographic coupling, and keyword co-occurrence mapping. RESULTS: The analysis revealed three main research clusters: MES core technologies, MES integration with Industry 4.0, and comparisons with ERP and SCADA systems. Key trends include the integration of AI, digital twins, and blockchain. Barriers such as interoperability, cybersecurity risks, and adoption costs—especially for SMEs—remain prevalent. CONCLUSION: MES research is advancing toward intelligent, scalable, and interconnected systems. Future work should prioritise standardisation, secure data exchange, and cost-effective models to support broader Industry 4.0 adoption. Cross-disciplinary collaboration will be essential to achieve sustainable and resilient MES implementations.
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