Discrete-Event Simulation for Smart Manufacturing: Assessing Software, Industry Adoption, and Future Research Challenges

Abstract The Discrete-event simulation (DES) has become a critical tool in modern manufacturing, enabling process optimization, resource allocation, and strategic decision-making. This study systematically evaluates 4 leading DES software solutions, assessing their capabilities, industrial adoption, and integration with emerging technologies. Key aspects include their modelling approaches, automation capabilities, scripting environments, digital twin integration, and support for risk-based planning and scheduling (RBS). A structured literature review was conducted using peer-reviewed sources published in the last ten years, focusing on manufacturing, healthcare, and supply chain applications. The findings reveal that while DES software enhances efficiency and scalability, challenges remain in computational complexity, interoperability, and real-time analytics. Moreover, gaps persist in autonomous decision-making and the standardization of DES models. This review provides a comprehensive overview of DES trends and research challenges, offering insights into future advancements in smart manufacturing. The study contributes to both academia and industry by identifying key areas for further development.