It is a well-known anecdote that Thomas Edison conducted many trials before inventing the light bulb. Imagine if Thomas Edison had access to a tool that could predict the outcome of his experiments without the need to complete each one physically. This is not a science fiction tale, but a reality made possible today through the concept of digital twins. Instead of navigating through a vast sea of trials and errors, Edison could have employed a digital twin of his invention. This virtual counterpart would have allowed him to simulate various materials, configurations, and process parameters to predict the most promising design for the light bulb, significantly saving time, effort, and resources.
Understanding Digital Twins Concept
A digital twin is a virtual representation of a physical entity developed using data, simulation models, and advanced analytics. It mirrors the life cycle of its physical counterpart, allowing for analysis, experimentation, and decision-making in a risk-free virtual environment. From the minor components, like a bolt in a wind turbine, to complex systems like an entire city, digital twins serve as a bridge between the tangible and digital worlds, offering a revolutionary approach to design, optimization, and maintenance.
The implications for innovation, efficiency, and sustainability are profound, affecting industries ranging from manufacturing and healthcare to urban planning and aerospace.
System Thinking in the Context of Digital Twins
But how do you start translating real-life objects to their virtual reflection? Here, System Thinking comes into play. Systems Thinking is a holistic approach that focuses on how system components are correlated and how systems work over time and within the context of larger systems. In the realm of digital twins, Systems Thinking enables practitioners to understand and describe the complexities of real-world entities in a virtual environment. It’s crucial for capturing the dynamic and often non-linear interactions between different system components being modelled.
Let us take a city as an example. From the System Thinking perspective, a city can be considered a complex system composed of various subsystems such as transportation, utilities, public services, and the environment. When creating a digital twin of a city, systems thinking helps integrate these diverse subsystems into a cohesive model. For instance, a digital twin of a city could simulate the impact of traffic flow changes on air quality, public transport usage, and emergency services response times. By considering these interdependencies, city planners can make informed decisions on urban development projects, traffic management, and environmental protection measures, leading to more sustainable and efficient urban environments.
An application of System Thinking is System Engineering. Systems Engineering is an interdisciplinary engineering and engineering management field focusing on designing and managing complex systems over their life cycles. Integrating various components (hardware, software, data, people, processes) ensures a system meets requirements. Systems Engineering is essential for ensuring that the virtual model accurately represents the physical counterpart and behaves as expected under various conditions in the context of digital twins.
The synergy between Systems Thinking and Systems Engineering makes digital twins powerful tools. Systems thinking provides the framework for understanding the complex interactions within the system, while Systems Engineering offers the methodologies and practices needed to build and manage these intricate models. Together with in-depth domain knowledge, they enable the creation of digital twins that not only replicate physical entities but also provide insights into their operations, predict future performance, and identify potential improvements.
Applications of the Digital Twin Concept
In the complex yet fast-paced technology world, digital twins play a pivotal role in accelerating innovation and reducing the time-to-market of new products. Researchers and engineers can conduct extensive testing, optimization, and scenario analysis by simulating virtual prototypes without needing physical prototypes. Key technologies making this possible include sensor fusion, the Internet of Things (IoT), cloud computing, and Artificial Intelligence (AI).
Faster Automotive Development
The digital twin approach in automotive development creates a virtual model of a vehicle or its components. This digital replica runs simulations using real-world data to predict performance, diagnose issues, and enhance vehicle design. By mirroring the physical vehicle in a digital space, engineers can test and optimize features under various conditions without the risk and cost of physical prototypes.
New drug discovery
Another fascinating application of the digital twin approach is accelerating drug discoveries. By building virtual replicas of human cells, rapid testing of drug combinations and understanding their mechanisms of action is now possible. This, in turn, improves the speed and quality of drug development, reducing traditional costs and timelines significantly.
Transforming Production Processes
In production environments, digital twins enable predictive maintenance, dynamic resource allocation and many more. By creating a digital replica of manufacturing assets and processes, operators can monitor real-time performance, identify inefficiencies, and proactively address issues before they escalate.
Next-Generation Logistics
Digital twins in logistics enhance operational efficiency, resilience, and sustainability. The key benefits are: optimizing supply chain relationships and mitigation of disruptions, predictive maintenance and repair of the assets, improving sustainability by reducing the environmental impact
Virtual Power Plants
Digital twins serve not only as virtual versions of physical systems. They can also create new entities, which previously weren’t possible. A representative example is a virtual power plant (VPP). VPP is a network of decentralized, power-generating units such as wind farms, solar parks, combined heat and power (CHP) units, and batteries. Such a system of collective energy sources can act like an actual power plant, but is more effective and sustainability-oriented.
Challenges and Limitations
While digital twins offer numerous benefits, they also pose challenges. Data security, possible privacy concerns, and integration with existing systems are just a few hurdles that must be overcome. Additionally, creating an accurate Digital Twin requires a profound understanding of the modelled system, which can be complex, time-consuming, and require extensive domain knowledge.
Despite these challenges, the future of Digital Twins is certain. As technology advances, we expect more sophisticated digital twins incorporating cloud computing, AI and other technologies like blockchain. These advancements will enable even greater insights and predictive capabilities.
Conclusion
The journey from Thomas Edison’s extensive physical experimental endeavours to today’s cutting-edge digital twins reflects a remarkable evolution in how we approach innovation, design, and problem-solving. Digital twins, underpinned by Systems Thinking and Systems Engineering principles, are not just technological marvels. They represent a fundamental shift in our ability to understand, predict, and optimize the complex systems that shape our world.
By harnessing the power of digital twins, we stand on the verge of a technology transition where the boundaries between the physical and digital blur, enabling us to solve challenges with unprecedented efficiency and creativity. From accelerating the development of sustainable cities and advancing healthcare to transforming manufacturing and logistics, the potential applications are as boundless as our imagination.
In conclusion, the concept of digital twins, enriched by Systems Thinking and Systems Engineering, offers more than a bridge between the physical and digital realms—it provides a roadmap for transformative change. As we continue to explore and expand the possibilities, let us do so with a commitment to the principles of integration, sustainability, and shared progress, ensuring that the legacy of today’s innovations creates a brighter, more informed future for future generations.
Are you considering applying the digital twin concept for your products, or considering applying a systems thinking and systems engineering approach with a trusted partner?
Systerion‘s team of professionals offers expertise in systems development, selected industrial domains. We will support you in analysing your case and propose an optimal course of action.
