Holistic understanding is one of the major benefits brought by digital twins, as stated in the Digital Twin Consortium’s definition. What precisely are the types of holistic understanding brought by digital twins, and what added value can be expected by industry? Ultimately, what is the recommended implementation of digital twins to support holistic value creation? To start with, let us consider the different levels of understanding brought by digital twins.
Digital twins can bring three levels of understanding – understanding what exists and what is happening, understanding the future, and understanding how to act and control performances.
By combining these levels, digital twins help the industry in its ability to move from reaction to anticipation and then to greater control, with some automation, of its performance.
These levels can be deployed from a single asset or process to the entire system or organization represented by the digital twin. The more the digital twin enables understanding and control of decision making (horizontal axis) in a systemic way, by considering all the diversity and heterogeneity of the reality under consideration (vertical axis), the greater the holistic understanding and value that is delivered to industry.
Understanding what exists and what is happening. Digital twins enable companies to accurately report on what exists, how it was built and commissioned, and monitor operational performance in real time from a single asset or process up to the level of the whole organization including all assets, processes, human capital as well as any environment factors to which they are connected.
Three technological approaches allow better awareness:
From a single asset or process to an entire system, digital twins can offer at this stage, through the descriptive modeling of components as well as the interconnections of environments, a holistic representation of what is built as wells as the monitoring of performance of the company at the present moment, connected to its environment, and explaining the current situation with historical design and operational data.
Understanding what will happen. Building from the first level of insight generated by system monitoring, additional value can be provided to organizations by predicting how the system will evolve, and what is likely to happen in the future. Here digital twins offer two major possibilities for organizations:
This level extends holistic understanding into the future and assesses the gap between what has been planned and how it will evolve. In both cases, predictions can be performed in real-time and provide insights to decision-makers ahead of any critical point.
Understanding how to act and control performance. Once an organization has the capacity to understand the current and future state of their system via their digital twin, they can begin to assess the robustness of their plans to uncertainty, test alternative plans via simulation scenarios, and optimize their performance. The digital twin represents the virtual environment for such experimentation by combining monitoring and predictive capacity with scenario testing, sensitivity analysis, robustness testing, and optimization technologies.
Uncertainties can be included in the model and the most influential variables can be identified to optimize alternative scenarios for planning resilience, and ultimately, automatically identify the most robust strategy or operational response.
Digital twins offer the capacity to virtually test levers that might be impossible to test in the field. Strategies and scenarios can be simulated to discover their impact on the organization before choosing which to implement, risk can be measured, safety levels optimized, and the impact of major transitions (decarbonization) or disruptions (pandemic disease impacts) assessed.
This holistic understanding, and the resulting value creation, therefore, impact the industry in a variety of ways.
At a micro level, for example, an organization can understand how a bottleneck in a production plant impacts other processes in the plant, learn why that bottleneck occurs, and identify the right lever to avoid it altogether. An organization might gain insights on how a shift from one strategic supplier to another impacts their delivery times or service levels, or how maintenance on a certain class of assets impacts the global manufacturing output of a single factory or group of factories.
At a macro level, the holistic understanding that a digital twin delivers can help in the strategic allocation of resources and the deployment of teams across an organization. Decision-makers can leverage the power of their holistic digital twin to generate robust and resilient plans that are truly systemic and not just global. What is more, they can safely automate processes and systems by training their automation algorithms to react to all possible situations and not only those that have occurred in the past.
Digital twins have the capacity to deliver this holistic understanding for organizations, but they rely on those organizations deploying five key components and powering those components in turn with three key enablers.
The five key components required to achieve holistic value with a digital twin are:
In addition, there are three key enablers that contribute to delivering this holistic value, namely:
A holistic understanding of a complex industrial system is important for making the best business choices. Digital twins provide this holistic understanding in real-time by offering a view of the whole system, the capacity to predict its future state, and ensuring its control and optimization.
This new type of real-time information and projection into the future in the short and long term transforms the decision-making process in three ways
This article was originally published in Digital Reflections, the online magazine of the Digital Twin Consortium in January 2021.
