Exploring the Synergistic Potential of Simulation-Based Decision-Making Tools in Enhancing Manufacturing Efficiency

Abstract

The manufacturing sector relies on simulation based decision making tools to optimize processes, improve efficiency and maintain competitiveness in a turbulent global marketplace. This narrative review investigates the synergistic potential of various tools, including digital twins, discrete event simulations, Monte Carlo methods, and agent based modeling. By enhancing key efficiency metrics, such as productivity, waste reduction, lead time, and cost savings, these tools have been made better and their integration with new technologies such as artificial intelligence, Internet of Things (IoT), and Industry 4.0 frameworks makes them more transformative. However, along with the benefits also come a number of challenges, including high computational demands, resistance to adoption, skill gaps and scalability. Moreover, gaps remain in their applicability to under researched industries and continuous manufacturing processes. The primary insight from this review is the importance of investing in emerging technologies like quantum computing, 5G, edge computing and their interdisciplinary collaboration to push these technologies to further minimize these barriers to unlock the full potential of simulation tools. The results demonstrate how simulation tools enable firms to transform the dynamics of manufacturing efficiency and provide directions for future research and practical implementation.

Keywords- Synergistic Potential, Simulation-Based Decision, Making Tools, Manufacturing Efficiency