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Digital Twins provide organizations with a new era of decision making and planning. Using data with Digital Twins enables a deeper look into their business allowing them to quickly see changes and trends while also enabling them to plan virtually and collaboratively. With Digital Twins, organizations can reach new levels of intelligence and control over their operations, leading to greater efficiency, higher productivity, lower costs and competitive edge.
The market for Digital Twins is moving fast and there are already huge opportunities for developing Digital Twins. Taking the right choice on use cases and technologies can save organizations money and is an important stepping-stone for future data-driven success.
Digital Twins are mirror images of reality – virtual images of physical objects, organizations or people. Continuous real-time updates with data from real-world create a dynamic virtual environment that can also be visualized in the metaverse. Whether it is microchips, manufacturing machines or entire factories – Digital Twins can be generated for almost anything. With high scalability, Digital Twins offer enormous optimisation potential for all industries.
In addition, Digital Twins can represent more information explicitly than the real object, as besides others they can contain important additional information, such as (production) history, future planning, balance sheet values and deadlines.
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Digital Twins bring the digital and physical worlds ever closer together. For example, Digital Twins of individual machine components can be linked together and be concatenated, creating a digital copy of the machine as a whole. Such links can also be dynamic – an interaction – which enables a Simulation of a machine based on Digital Twins.
This disruptive potential of Digital Twins for traditional business models is already being recognised by many companies in different sectors. For example, 14% of German companies are already benefiting from the advantages of Digital Twins and 20% are interested in introducing such concepts.
As a consequence, many companies have developed their own Digital Twin solutions, which are already on the market making the choice of the right Digital Twin software non-trivial. The correct choice, however, is a key aspect for successful digital transformation. A company's needs and requirements need to be precisely defined, as the right scope of information is crucial. Too much information and it will increase costs and prolong development, too less and it won’t draw the right picture to make informed decisions.
To further strengthen confidence in the integrity of data, standards concerning data management are in development. This will require well thought-out and future-oriented data management that is reflected in the organizational structure as specific knowledge is needed – both technical and from a compliance side.
The successful digital modernisation of corporate data forms the basis for trustworthy applications built on it and promotes the development of data-driven technologies, such as AI or data analytics. Thus, trustworthy data management is expected to generate average annual growth rates of up to 45% in the Digital Twins sector in Germany by 2030.
When done right and responsibly, Digital Twins offer a possibility to better understand the facts underlying the relevant data and to visually engage and interact with the information to gain further insights into your operations. Using them you can plan next steps virtually, which makes decision making cheaper, richer and quicker.
“With Digital Twins companies and organizations can start interacting with their data and better understand the facts underlying their processes. Thus, making better informed decisions and reducing risks.”
In production, a robot can be represented by a Digital Twin. This Digital Twin can be constructed of robot component Digital Twins and range up to an entire production line Digital Twin. Often Digital Twins only structure already existing data of physical objects. The benefit lies in the creation of relationships between data points. This enables complex analyses of production, e.g. identification of bottlenecks. Additionally, to analyze past events, Digital Twins allow for forecasting possible future scenarios in Simulations that can be visualized, e.g. in a metaverse. For example, production failures can be predicted and thereby downtimes and maintenance costs are reduced. This not only increases confidence in reliable production, but also enables reliable utilization planning.
Digital Twins can be created for manufactured objects too. Often, product information such as material quality, origin or batch numbers are available to manufacturers only or are complicated to get access to. Structuring this data enables better analysis of products and production. Simulations based on Digital Twins make possible a Simulation of how changes in production may affect products. In the end, structured product data increases customer confidence, as they can better comprehend the production and understand what quality assurance measures were passed.
Digital Twins can be applied not only to production but also to organizations and processes. In organizations they can map individual business processes, departments, or entire corporate structures and are highly scalable. However, the data required for Digital Twins is often available in a mass, unstructured format, which makes it less accessible and meaningful. The preparation and structuring of this data as Digital Twins enables the exploitation of its full potential, allowing for real-time analysis of business processes and quicker identification of weak points in the organization. As an example: When preparing offers it is possible to identify which sub-processes, e.g. of external service providers, are particularly inhibiting. Changes to existing business processes can be simulated and their effects predicted based on Digital Twins. The potentials show that Digital Twins are not only of interest for the manufacturing industry, but for all industries aiming to optimize their processes.
Creating Digital Twins of entire companies – including organization and production – follows the idea of creating Digital Twins from Digital Twins along a hierarchical and meaningful structure such as already existing in a company’s organigram. This hierarchical structure keeps complexity low and interpretability high. The holistic approach enables real-time analyses of any company aspect and their interdependencies, e.g. between sales and business strategy, while still holding up accessibility for users. The concatenation of Digital Twins enables Simulations and forecasts about the effects of changes and identification of economic potentials. Exemplary questions to be assessed are:
What will be the impact of outsourcing production on lead times, development costs, personnel costs, etc.?
What concrete effects will the restructuring of the company's divisions have on the company's processes?
Which processes and employees will be needed for a new location and how will these affect the existing organization?
The possibilities and advantages of Digital Twins for Simulation and creation of forecasts are manifold and extremely promising.
The use of Artificial Intelligence takes the possibilities of Simulations based on Digital Twins to the next level, as significantly more complex relationships can be identified. AI can be integrated with Digital Twins in two ways:
Many use-cases combining AI and Digital Twins can be envisioned, e.g. predictive maintenance, personalized medicine or urban planning. To further outline the potential for example on urban planning: Digital Twins can, for example, be used to gain a better understanding of the impact of construction projects on urban infrastructure. AI helps analyze large amounts of data collected from sensors and other sources to identify patterns and correlations. This for example allows urban planners to analyze project consequences at an early development stage or enables them to minimize the impact of construction projects on traffic, energy supply or the environment – for a better citizen experience and ESG purposes.
“Just like a biologist using a petri dish, with combined Digital Twins that form the landscape of your business you are able to plan future success using a mirror image of your company.”
At PwC, we firmly believe in driving business transformation and streamlining through Digital Twins. As a leading digital trust company, we prioritize that our solutions meet the highest standards of safety, security, privacy, and scalability. We understand that implementing these technologies can pose potential risks, including data accuracy, reliability, bias. Therefore, to ensure trustworthiness in the data, algorithms, and models used, we employ transparency, data governance, validation processes and controls to ensure that the decisions made are accurate, safe, secure, and ethical. Our team of technological, governance and business experts wil providing tailored support every step of the way, from planning and implementation to continuous maintenance and assistance. Let us help you drive your business to the next level. It's time to consider the power of Digital Twins and Reinforcement Learning.