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The term digital twin became a “thing” about a dozen years ago, thanks to the pioneering efforts of industrial companies like Dassault Systems, General Electric, IBM, Schneider Electric and others. Over time, digital twins replaced 3D modeling. The primary advantage of digital twin technology over 3D modeling was that digital twins bridge the gap between the virtual and physical world, enabling a new breed of diagnostics, maintenance and troubleshooting that extends the life of physical products.
In January, electronics distributor Avnet Inc. identified digital twins as one of three industrial IoT trends manufacturers should be thinking about now. According to Avnet, the concept behind digital twins is already established, but the support needed to make it widespread is only just now being rolled out. This includes a common language to describe the built world in a way that is easy to model.
Digital twins allow companies to conduct virtual “what if” experiments of their production environments without causing disruption. For example, data captured from the equipment on a factory floor can predict why and how the equipment may fail. Likewise, data captured by sensors and IoT devices in a warehouse can help a supply chain team manage future inventory costs.
By modeling end-to-end supply chain digital twins, suppliers, distributors and OEMs can quickly see the consequences of unplanned disruptions in the supply chain and make timely contingency plans. A supply chain digital twin is a virtual simulation model of a real supply chain used to analyze supply chain dynamics. Digital twin models use real-time data from IoT devices, logistics and transportation databases, vendors and suppliers, and user experience to optimize inventory.
“We work with a number of large enterprise companies, especially with our Softweb Manufacturing 360 offerings. Through that work we are seeing opportunities especially within shop-floor solutions, and production schedules integrated with warehouse management systems and order management systems [WMS and OMS],” said Prasad Bhojak, business development manager for Avnet’s Softweb Solutions unit. “Digital twin technology helps implement ‘what if scenarios for these large-scale applications within the enterprise. These applications are built on top of the existing technology to allow for better decision-making.”
In one use case, the head of procurement at a company that manufactures in Asia and Latin America for markets in the U.S. and South America received an offer from an Asia-based supplier that wanted to increase business with the company and offered an attractive discount. Using a digital twin of its supply chain, the company was able to show how the lower price stacked up against other options. Price was a factor, but so was lead time, how far the product must travel, and how the change might impact the need to hold more finished goods inventory.
Source: kvbresearch
The customer used a digital twin of its global network to evaluate the merits of the scenario and was able to determine the impact with a high degree of confidence in just two hours. Before, it would have taken two weeks, and they would have had much less confidence in the evaluation.
Today, digital twins are primarily built to manage product design and manufacturing. Sensors and IoT devices are the primary tools for processing massive amounts of data from real-world products and systems such as appliances, cars, planes, and manufacturing equipment. Digital twins use AI and ML to predict failures and unplanned shortages so action can be taken preemptively to fix the problem in the physical world. Bottom line: digital twins reduce accidents, unplanned downtime, and maintenance costs in real-world systems.
The number of companies stepping up to engage with digital twins has continued to grow steadily. For example, over 100 companies have joined the Digital Twin Consortium in the last couple of years. Kvbresearch projects the global value of the digital twin market will reach more than $63 billion by 2027, dominated by business optimization and predictive maintenance applications.
It’s early days in the application of digital twins to manage supply chain operations. But there’s evidence that the benefits and cost savings could be significant.
