An analytical review of data integration for decision support in smart manufacturing
Farah Balaha, Hamad Albinali, Haneen Alrabiah, Mohamed Ali, Zied Bahroun
Abstract
The increasingly complex and globalized business environment demands effective data integration and management to support decision-making. Enterprise Resource Planning (ERP) systems play a pivotal role in managing and integrating information in modern organizations, particularly within the evolving landscape of Industry 4.0. This paper presents a systematic review, conducted using PRISMA guidelines, of peer-reviewed journal articles published between 2019 and 2024. A comprehensive search in the Scopus database retrieved 439 publications, of which 69 were selected after assessing relevance. These studies were categorized into five key themes: Resource Allocation and Planning, Information Management, Supply Chain Improvement, Automation and Process Optimization, and Exploratory and Explanatory Studies, with further subthemes providing deeper insights. The review reveals that while ERP-Industry 4.0 integration offers significant potential for enhancing operational efficiency, supply chain resilience, real-time data visibility, and automation capabilities, it also presents challenges related to system complexity, data security, interoperability, and workforce readiness. The analysis further uncovers a tendency for case-specific or sector-specific studies, highlighting the need for comprehensive frameworks and cross-sectoral research. A bibliometric analysis using VOSviewer visualized co-authorship networks, research trends, prominent keywords, and the most integrated Industry 4.0 technologies. Notably, IoT, Big Data Analytics, and Cloud Computing emerged as the most prevalent technologies associated with ERP integration. This paper synthesizes the current state of research, identifies significant gaps, and offers actionable recommendations to guide future research. These include: developing scalable integration architectures, addressing cybersecurity and data governance challenges, and fostering cross-functional collaboration to support data-driven decision-making and enhance ERP integration in dynamic Industry 4.0 manufacturing environments. • Examine recent studies on decision analytics in smart manufacturing environments. • Map how integrated systems support real-time data and predictive insights. • Identify major decision challenges in planning, automation, and operations. • Reveal barriers to adoption, including security, complexity, and workforce readiness. • Recommend data-driven frameworks for scalable decision support across sectors.