## 3 Integrating DT in CPS
### Smart Manufacturing  
The smart manufacturing system, as a general concept, is the integration of traditional manufacturing systems and processes with information communication technologies to enable advanced intelligence and process optimization and automation. The demands of current manufacturing systems can be complex in nature, due to the challenges of scalability, efficiency, delivery, or design requirements [79]. The smart manufacturing system is the utilization of emerging technologies to massively optimize production in terms of throughput, efficiency, precision, loss, resource consumption, scale, and value [7]. Traditional manufacturing systems are comprised of shop floor hardware that works as a unit to streamline the production of a deliverable product. In contrast, the smart manufacturing system integrates communication and computing technologies to utilize information generated from traditional manufacturing systems to make a more complete representation of a product life cycle. The application of IoT to industrial systems, or Industry 4.0, relies on technologies such as sensing, control, communication, computing, and data science to support information flows between different components of the manufacturing system, allowing for better system interoperability and use. One major limitation in manufacturing systems is the ability to automate and mass produce in a manner that is efficient and cost-effective. With the shifting paradigm in manufacturing of custom user deliverables, there is an increased challenge to provide custom solutions in a method that can be massively produced by manufacturing systems. A common issue in manufacturing is the ability to generate a deliverable that is flexible to the user's needs while still maintaining automated systems that can quickly and efficiently create products. At scale, it is often difficult to analyze how changing requirements in the product design or supply chain will impact variables such as cost and production timelines while retaining quality and efficiency. Additionally, adoption rates are going to be a challenge for manufacturing environments that are looking to incorporate smart manufacturing systems in their product life-cycle. A core technology for enabling smart manufacturing is the availability of information from the physical objects (i.e., shop floor equipment) through IoT sensors connected to IoT networking infrastructure. Implementation of DT in the smart manufacturing system can help evaluate the effectiveness of large-scale production environments by utilizing models for analyzing production efficiency and design factors. The link between the virtual and physical representation of a manufacturing system (i.e., in the way of DT) can determine whether a design is going to be cost-effective by integrating with decision support systems such as supply chain management and timeline forecasts. The integration of smart supply chain technologies involves a real-time link between the production environment and the suppliers and distribution centers to determine the deliverable dates [80]. Determining the availability of materials required for manufacturing production will allow the system to generate a cost model and timeline for delivering a final product. Monitoring the physical production environment with DT systems can allow for the real-time analysis of system health on physical things (i.e., equipment, tools, and hardware) and prevent delays based on environmental factors. In the event of an anomaly detection on a manufacturing system, the DT model can determine whether the work load should be rerouted to another system in the manufacturing line to avoid delays in production [81]. IoT sensors in manufacturing equipment allow for real-time monitoring, enabling the detection of events that could cause breakdowns in the manufacturing system and providing alternative scenarios for maintaining system efficiency to prevent delays in production timelines [82].