However, the measurable benefits, such as time savings and cost reductions, are often anecdotal or limited to specific projects, lacking systematic quantification. Furthermore, the development of digital twins heavily depends on expert knowledge, resulting in bespoke models that are difficult to standardize and reuse. The interoperability between various simulation and automation tools also poses a significant barrier to broader adoption [18]. Recent review studies emphasize the pivotal role of DT technology in the context of Industry 4.0, particularly in automation, supervision systems, and predictive maintenance. A comprehensive review by [PERSON] et al. explores the integration of existing and disruptive technologies in automation and supervision, highlighting how Industry 4.0 relies on digitalization and IIoT-enabled solutions for seamless industrial operations [19]. Another review study by [PERSON] et al. focuses on the standardization of predictive maintenance automation through DTs, addressing challenges such as explainability, data efficiency, and scalability and proposing a requirement-based roadmap for DT-driven predictive maintenance [19]. Furthermore, a broader review by [PERSON] et al. outlines the key applications of DT in Industry 4.0, emphasizing its role in real-time process monitoring, efficiency optimization, and data-driven decision-making [20]. These studies reinforce the significance of DTs as a transformative technology, supporting their practical implementation in industrial automation and manufacturing environments. This research is motivated by the potential of digital twins and virtual commissioning to bridge the gap between simulation and real-world validation in cyber-physical systems. The primary objective of this study is to explore the development of functional digital twin models that meet the requirements for both simulation and validation purposes. These models must effectively identify design flaws in CAD-based systems, verify the functionality of automation components such as the PLC control code, and support interoperability across diverse software platforms. By addressing these aspects, this research seeks to provide practical insights into the application of digital twins and virtual commissioning, offering solutions to overcome current limitations. To achieve these goals, this study focuses on a case study involving a specific cyber-physical system. The objectives of this case study are to evaluate the ability of digital twins to identify and address deficiencies in CAD designs, such as inefficient motion trajectories and collision risks. Additionally, this study aims to verify the functionality of automationsystems, including the PLC control code, within a virtual environment. Furthermore, it proposes a methodology for creating robust and reusable digital twin models that are universally applicable and compatible with various simulation and automation tools. Finally, this study highlights limitations in existing practices and offers recommendations for improvement. This article is organized as follows. The Introduction provides an overview of the problem, the benefits and challenges of digital twin technology, and the motivation and objectives of this study. The Related Work Section reviews existing research on digital twins, virtual commissioning, and their applications in cyber-physical systems. The Preliminary Methodology Section details the proposed approach for developing DT models, emphasizing their application for simulation and validation. The case study demonstrates the practical application of the methodology of virtual commissioning to a specific cyber-physical system as Digital Twin and Control System Design Section. The Discussion Section analyzes the findings, addressing the benefits, limitations, and practical insights of the approach. Finally, the Conclusion summarizes the contributions of this study and suggests directions for future research.