Digital Twin

A digital twin is the virtual representation of a physical product or system of assets that reflects the real-time configuration. Additionally, it can be used to navigate, via a Digital Thread, all relevant product information from design, manufacturing, operations and maintenance that have occurred to that unique, physical configuration throughout its life.

The history of digital twin technology

The digital twin was initially envisioned as the foundation of product lifecycle management (PLM). The idea of the digital twin first appeared in the 1991 book Mirror Worlds by David Gelernter. However, the first practical use was part of a NASA attempt to improve spacecraft simulation in 2010.

How does a digital twin work

There are unlimited use cases for using a digital twin to improve business outcomes. As a manufacturer, you must ensure your “as-built” configuration is as accurate and detailed as possible. This creates the first opportunity to develop an exact, unique representation of each product manufactured by capturing all serialized electrical, electronic, mechanical, and software components and linking them to engineering parts and their related history, thereby linking the product to all related Digital Thread information. CAD models, simulations, requirements, change orders, and so on are considered based on the value they can provide in supporting your required use cases. You can also create unique Digital Twin configurations in operations and maintenance. This begins by keeping accurate records and tracking what a product’s configuration is and managing how it changes over time. The goal is for product manufacturers to have a Digital Twin configuration from when the product is built and to continue manage that configuration and it changes over time – until that individual physical product is retired and recycled.

Types of digital twins

Although there are myriad usage types for the digital twin, the four most common types of digital twin are:

• Component digital twin…Sometimes called the “parts twin,” the component digital twin replicates small system elements, like a sensor or switch. This allows users to monitor the performance and simulation testing of these devices.
• Product or Asset digital twin…Implementing asset or product digital twins gives engineers a framework for monitoring performance, detecting issues that require improvement, and increasing productivity. It also opens a new avenue for engineers to glean insights and isolate potential areas of improvement.
• System digital twin…Also called “unit twins,” system digital twins duplicate system-level assets. A system digital twin covers the specific set of assets in a particular product, with real-time monitoring and simulation providing valuable data to inform strategic decision-making through process visibility.
• Process digital twins…Process digital twins connect system twins into a single entity to explore collaboration between different systems. It provides the most expansive view of plant processes and workflows, allowing more profound and more nuanced data analysis.

Digital twin advantages and benefits:

• Maintenance organizations can use the Digital Twin to support advanced strategies. With Aras, they have a view into each unique Digital Twin Configuration for assets being managed. They can drill into any asset’s operational status to identify upcoming maintenance requirements before possible unplanned downtime occurs.
• The Digital Twin provides better collaboration across the product lifecycle, helping companies quickly pivot to strategic new markets.
• Using applications, such as Aras Digital Twin Core, organizations can digitally manage the pace of configuration changes in physical assets and add characteristics to specific parts to define when maintenance should occur based on any operational event. This allows organizations to adopt product-as-service strategies for complex assets to craft maintenance plans to meet regulatory requirements or guarantee uptime based on service-level agreements.
• Building and managing Digital Twin configurations provide access to their own critical information–every time the physical asset changes.
• Building a Digital Twin creates foundational traceability― changes can be recorded with the new serialized component information to keep the Digital Twin configuration up to date and show the old component as part of its Digital Thread traceability.
• You can use the Digital Twin to predict the future. Based on the individual configuration of a particular asset and the use of simulations, you can predict what will happen if we replace a part or update software.

A Digital Twin is Possible for Any Asset in Any Industry…

The Digital Twin provides significant benefits to manufacturers and others in asset-intensive industries. Digital Twin enables the modeling, adapting, and extending of configurations for any asset or system of assets in any industry. This eliminates the inaccuracies and associated costs by creating the context of every unique physical asset in the field so that organizations can support complex scenarios such as predictive maintenance, performance optimization, and even over-the-air software updates. Although there are unlimited possibilities on how to utilize Digital Twins to improve business outcomes, here are a few examples:

• Manufacturing: Technology is available to link product data as it is created in the design, engineering, and manufacturing stages and to capture it as it changes. We call this the Digital Thread. Many manufacturers realize the importance of creating digital threads between departments. Everything must be connected to the final product at the final stage of product manufacturing. This Digital Twin Configuration links all product data history, decisions, who made them, and why, including the CAD models, simulations, and requirements.
• Nuclear: Aras Innovator provides the foundation for the single data source implemented by the first nuclear power plant designed and managed with PLM as the backbone. This will enable them to provide an as-built Digital Twin configuration of the reactors at the time of delivery with traceability to all product data created during the engineering and manufacturing of the product.
• Oil and Gas: Power industries: PLM is important in developing improved engineering processes and delivers an as-built Digital Twin configuration that enables more sophisticated field support and predictive maintenance. For example, in Oil & Gas or power generation, changes are frequent, products are many, and there are relationships between products—creating systems of systems. These companies need their configurations to be more automated to keep up with the pace of change.
• Aircraft Design and Maintenance: Building a Digital Twin configuration creates an opportunity to bring modeling and simulation techniques to the operations phase of an asset. These capabilities can be used to compare operational data and simulate the behavior of the asset now, as well as the future state of the asset if the behaviors continue. This allows organizations to improve the accuracy of operations and maintenance decisions to optimize their aircraft fleets and can be used by OEMs to support future product improvements in next-generation aircraft.

Additional Digital Twin Use Cases

Beyond industry-based use cases for Digital Twins, it is also possible to configure them based on unique requirements across the product lifecycle. For example:

• Customer Requirement Digital Twins: Depending on the customer, when they receive your product or system of products, they may expand or collapse the fidelity they want to see based on how they intend to maintain the product over time.
• Business Model Digital Twins: This concept allows flexibility in how the configuration of the Digital Twin is set up, linked to the Service Level Agreements provided to support the final product in the field. This could mean the entire configuration can be accessed to support the sales of upgrades (see in product capability purchase). If the manufacturer offers “Product as a Service,” the view could be based on what needs to be managed based on guaranteed uptime.
• Supply Chain Digital Twins: Depending on which supply chain is being managed for the same product, a different configuration view of the Digital Twin may be required. OEMs may have an extensively detailed view of the component level of the supply chain. In contrast, the Owner/Operator may require a different view based on how they operate and maintain with their vendors to support reorder components during maintenance.
• Target Scenario Digital Twins: Depending on what the business tries to achieve financially or operationally, the Digital Twin configuration can vary and adapt to align with objectives. For example, a higher fidelity view would be required if your organization is moving from preventative to predictive maintenance. In contrast, if you have a software-defined product operating in the field, you may want to see only the software-related configurations of each asset to determine which assets and when Over the Air (OTA) updates may be required.

The future of digital twin technology

• As opportunities arise to manage complex products in the field, organizations realize that existing technology needs to be improved, making it challenging to keep up with the pace of change. You can use the Digital Twin to predict the future. Based on the individual configuration of a particular asset and the use of simulations, you can predict what will happen if we replace a part or update software. Failing to excel affects brands, profitability, and business sustainability – this creates the opportunity to transform with the Digital Twin:
• The Digital Twin provides a view into each unique Digital Twin for managed assets. They can drill into any asset’s operational status to identify upcoming maintenance requirements before possible unplanned downtime occurs. This is what is known as prescriptive maintenance. Ultimately, it allows manufacturers to decide on when to address potential failures before they happen.
• Digital Twin technology allows innovation across the product lifecycle, helping companies quickly pivot to address new market opportunities by understanding unique applications of their products as customers operate them, understand quality issues, or new features commonly requested.
• PLM assists engineers in designing future complex products instead of just “tracking” what was intended. Exposing design intent in PLM has many benefits throughout a product’s lifecycle, and many involve the ability to generate a Digital Twin in context instead of having to go to the asset in the field physically. It can be used to analyze the impact of a proposed product update, leverage IoT data in preventive maintenance, or wirelessly enable/disable services in specific product variants and others. Artificial Intelligence (AI) can help by allowing more intelligent searches, generating task-specific reports from complex data, or translating requirements and regulations between languages without losing the context.
• Digital Twins and sustainability: Digital Twins may help companies meet the challenges of Environmental, Social, Governance (ESG) compliance by surfacing opportunities for more sustainable products and practices. In Addition, manufacturers of products, and customers themselves can use the Digital Thread data linked to the Digital Twins to support reporting and regulatory requirements.

Other resources:

• Digital Twin Core
• The Digital Twin: Everything, Everywhere, All at Once
• The Digital Twin in Maintenance and Service
• What Makes Digital Twins So Compelling?