IoT-driven Decision Support Systems for Smart Manufacturing: A Review of Implementation Strategies

Abstract

This paper explores the integration of Internet of Things (IoT) technologies with decision support systems (DSS) in the context of smart manufacturing, offering a comprehensive review of current implementation strategies. With the advent of Industry 4.0, the potential for IoT to revolutionize manufacturing processes through enhanced data-driven decision-making is immense. However, the effective deployment of IoT-driven DSS presents a myriad of challenges, including data management, system integration, security concerns, and the need for robust analytical tools. Through a meticulous literature review and analysis of various case studies, this study identifies and discusses key strategies employed to overcome these challenges, thereby facilitating the successful adoption of IoT-driven DSS in smart manufacturing environments. Additionally, this paper highlights the architectural considerations, data analytics techniques, and integration methods that are pivotal to the optimization of manufacturing processes. By examining the implications of these strategies on the efficiency, productivity, and sustainability of manufacturing operations, the paper provides valuable insights into the future direction of smart manufacturing. The findings underscore the critical role of interdisciplinary approaches and the need for continuous innovation in technology and management practices to harness the full potential of IoT-driven DSS in smart manufacturing.