Track: Modeling and Simulation

Abstract

This review paper delves into the evolving landscape of project monitoring and control tools within the manufacturing sector, driven by the increasing complexity of modern production processes and the rapid adoption of Industry 4.0 technologies. We provide a comprehensive analysis of a spectrum of tools, ranging from traditional methods like Gantt charts and Critical Path Method (CPM) to sophisticated solutions such as Enterprise Resource Planning (ERP) systems, Manufacturing Execution Systems (MES), and advanced analytics platforms powered by artificial intelligence (AI) and the Internet of Things (IoT).

This review highlights a significant shift from static, reactive monitoring approaches toward integrated, data-driven systems that provide real-time visibility, facilitate predictive modeling, and empower proactive decision-making.  We discuss key factors influencing tool selection, including industry context, desired outcomes (e.g., cost reduction, risk management, efficiency improvement), and the level of technological readiness within organizations.

Our findings underscore the imperative for manufacturing companies to embrace a data-centric, future-oriented approach to project oversight. By leveraging the capabilities of advanced monitoring and control tools, manufacturers can effectively navigate the complexities of modern production, optimize operational performance, and maintain a competitive edge in the rapidly evolving industrial landscape.