# Digital Twins: Enabling Interoperability in Smart Manufacturing Networks
## 5 A Digital Twin Framework for Interoperability  
Digital twins are unique because no two businesses will have the same digital twin architecture as their assets; processes and facilities will differ. The beauty of a digital twin is that it is a mirror of the physical workspace. As the business grows and changes, so too will the digital counterpart. Understanding systems, their architecture, behaviours, and how they interact with other systems depends on conceptual models. Such models must be codified and standardised in a way that is reusable for various use cases encountered in the field in a world where millions and billions of interconnections are implemented daily in dynamic ways. By modelling information, professionals can develop standardised models depicting the fundamental components of systems and intelligent machines, resulting in better modularity and reuse. A digital twin system's primary goal is to speed the holistic understanding of the real world for the best decision-making. The \"world\" can be a structure, utility, community, nation, or another environment. Not simply the isolated connection between two subsystems, but all information transmitted across connected systems must assist the digital twin's overall goal: the development of a common interoperability mechanism, in which each system contributes to the collective intelligence of the whole and where one system may easily consume and respond to information from another system [31]. Below in Figure 7 is a diagram that captures the concept of an interoperable system as outlined. Figure 7: Conceptual digital twin framework towards a system of systems. According to the 2017 EU report, European Interoperability Framework, \"The focus is on releasing machine readable data for use by others to stimulate transparency, fair competition, innovation and a data-driven economy\" [32]. Manufacturing businesses with legacy production systems and functional PLC code must find a method to integrate a verified manufacturing approach into their current processes if they are to tackle the demands of Industry 4.0. By bridging the gap between the factory floor and the company, industrial IoT improves visualisation, data analysis, and holistic insights, enabling operators to maximise the effectiveness of crucial operations. Data synergy, or the integration of data from various sources to produce value, is a crucial part of the industrial IoT. The aforementioned deployment methodology can be applied to both modern and antiquated production facilities, with little disturbance to ongoing installations. This architecture offers a real-time enabled framework for vertical and horizontal integration, making it easier for various sensors and systems to communicate with one another. For manufacturing, the transition towards interoperability can improve policies and standard practices through the following:  
1. Improved supply chain management, resulting in reduced costs, increased efficiency, and faster delivery times [33]. 2. Enhanced quality control processes, leading to improved product quality, reduced waste, and increased customer satisfaction [34]. 3. Increased regulatory compliance, through standardized data collection, sharing, and analysis, reducing costs and improving transparency [35]. 4. Informed decision-making through better data analytics, providing insights into operations, products, and customers [36]. 5. Greater innovation and collaboration, enabling the development of new products, services, and business models that meet evolving market needs [37]. Interoperability can foster greater innovation and collaboration, enabling the development of new products, services, and business models that meet evolving market needs. By collaborating with different partners and stakeholders, manufacturers can gain new perspectives, share best practices, and leverage technology to create innovative solutions that drive business growth.