Physical Twins Provide Data over Time that Allows Digital Version to Simulate and Optimize Peformance, Among Other Benefits

If you been at all following the news (and to some extent hype) around digitization in manufacturing generally, you may have come across the concept of a "digital twin" for a company’s products and/or assets.

What is a digital twin? According to GE, which is making a major push into providing digital manufacturing solutions, a digital twin is "a dynamic digital representation of an industrial asset that enables companies to better understand and predict the performance of their machines and find new revenue streams, and change the way their business operates."

Supply Chain Digest Says... Gartner says "Seek simplicity: avoid building a digital twin if business objectives can be met with basic indicators from sensors on critical performance issues." What do you say? Click here to send us your comments Click here to see reader feedback

Those assets at minimum can be either a company’s own production equipment or the products it sells to market.

According to Network World magazine, a digital twin "is a digital replica of a physical asset, process, or system that can be used for a variety of purposes. The digital representation of an object provides both the elements and the dynamics of how the object operates throughout its life cycle."

Both definitions get us started, but we could probably agree are not exactly crystal clear.

The analysts at Gartner maybe get it a little better: "A digital twin is a digital representation of a physical object. It includes the model of the physical object, data from the object, a unique one-to-one correspondence to the object and the ability to monitor the object.

So it seems safe to say a digital twins is an electronic model of an asset or product that can be used to simulate the behavior of its physical twin - and in some cases maintain the history of that asset/product in the field over time.

The more highly instrumented a device is - meaning how many sensors and data inputs the physical twin is equipped with - the more accurately its digital twin will represent its actual historical performance, leading to better analysis and simulation of its future performance.

Gartner says that digital twins add value to traditional analytical approaches by improving situational awareness, and enabling better responses to changing conditions, particularly for asset optimization and preventive maintenance. The twins can lower operating expenses and potentially capital expenses too by extending the life of the object they represent and optimizing the performance of the asset as it runs.

So there is certainly a heavy touch of Internet of Things to the digital twin concept, with the physical object providing the connectivity and data, which is then stored and processed by the digital twin.

Source: GE

The focus today seems to be primarily on production assets and major types of industrial equipment, from turbines to aircraft engines, but the concept may see eventual adoption for more consumer type products as well.

Network World says digital twins can have a major impact in three areas:

1. Driving improvements in the manufacturing process: Companies can use digital twins throughout the manufacturing phases - from initial design to completed product - to make sure the observed performance of the manufactured product conforms to the design goals. Manufacturing operations can also be optimized by efficiently predicting production line failures and fixing them before they effect target production goals.

2. Providing efficient predictive maintenance for existing products in the field: Digital twins can provide both historical and real-time data that technicians and increasingly smart maintenance systems can leverage. Predictive algorithms increasingly provide insight into potential failures before they occur. Technicians can use also use the digital twin to make remote preventative adjustments, without having to go into the field to fix the physical product.

3. Developing new products based on real world usage of existing products: For example, digital twins can capture and analyze data on how products are being used by customers and what changes could or should be made in new product design and manufacturing to improve market penetration and customer satisfaction. That is at the product level as a whole. In other cases, the twin can provide insight into how a given customer is using a specific piece of equipment - effectively or not - as Caterpillar is already doing with its construction machines across the globe.

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How to get started with digital twinning? Gartner offers the following recommendations:

• Focus on objectives: Understand the key business benefits from digital twins before investing to build them.

• Assess readiness towards adoption: A parallel element to this is understanding the readiness of the enterprise to adopt IoT initiatives that will leverage digital twins.

• Seek simplicity: Avoid building a digital twin if business objectives can be met with basic indicators from sensors on critical performance issues.

• Include checks and balances: Develop leading indicators with metrics that can be used to measure the progress of digital twin initiatives, which may require a few years to realize financial objectives.

Among the interesting changes to business models that Gartner foresees is the potential development of companies charging for their products based on performance data, a sort of digital form of gainsharing.

Do you have insight on digital twins? What can you add? Let us know your thoughts at the Feedback section below.

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