Digital Twin: Virtually Understanding Asset Performance

Digital twins give businesses an unprecedented view into how their assets perform. A digital twin can help identify potential faults, troubleshoot from afar, and ultimately improve customer satisfaction. It also helps with product differentiation, product quality, and add-on services too.

If you can see how customers are using your product after buying it, you can gain a wealth of insights. That means you can use the data to (if warranted) safely eliminate unwanted products, functionality, or components, saving time and money.

Unprecedented control over visualization, from afar

There are other advantages to a digital twin, too. One of the major ones is that digital twins afford engineers and operators a detailed, intricate view of a physical asset that might be far away. There’s no need for engineers and assets to be in the same room with the twin or even the same country.

Imagine, for example, a mechanical engineer in Seattle using a digital twin to diagnose a jet engine sitting in the hanger of O’Hare airport. Or engineers visualizing the entire length of the Channel Tunnel from Calais. Thousands of sensors in a dozen modalities, like sight, sound, vibration, altitude, and so forth, mean an engineer can ‘twin’ a physical thing from almost anywhere in the world. That means unprecedented clarity and control over visualization.

IBM Maximo and digital twin technology

IBM has been doing a lot of work with digital twin technologies. And the applications keep growing across different industries, bringing Augmented Reality (AR) into asset management. The IBM Maximo lab services ‘turns on’ many visual and voice (Natural Language Processing) features for your workforce. You can see your assets in a new dimension and get instant access to critical data. You can then feed those insights back to others using an AR helmet with voice/video in the visor. This makes ‘interacting’ the next evolution of working.

The future of the cognitive digital twin

Digital twins are already helping organizations stay ahead of digital disruption by understanding changing customer preferences, customizations, and experiences. This knowledge means businesses can deliver products more rapidly, with higher quality, from the components to the code. Yet, the promise of digital twin can still go further.

The use of cognitive computing increases the abilities and scientific disciplines in the digital twin. Technologies and techniques such as Natural Language Processing (NLP), machine learning, object/visual recognition, acoustic analytics, and signal processing are just a few features augmenting traditional engineering skills. For example, using cognitive to improve testing a digital twin can determine which product tests should be run more frequently. It can also help decide which should be retired. Cognitive digital twins can take us beyond human intuition to design and refine future machines—no more “one-size-fits-all” model. Instead, machines are individually customized. That’s because cognitive digital twin is not just about what we are building, but for whom.

Part One: What is a Digital Twin? Here’s a Basic Definition

Initially published by Maggie Mae Armstrong

Ms. Armstrong is the Director of Marketing at IBM. She oversees public relations and marketing efforts to a broad range of complex audiences.