Smart Factories: The Future and the Present of Digital Twins
We are in a new world for the manufacturing industry; an industry which was already experiencing an enormous amount of disruption and change a year ago has been completely reinvented by COVID-19. Almost overnight, supply chains were undone, demand dried up for some products and ballooned for others, employees were forced to distance or couldn’t come to work at all.
One outcome of these challenges has been a greater demand for digitally agile processes to help manufacturers meet current demands and better prepare for the uncertain future. One solution they have been turning to has been the introduction of cognitive and intelligent processes. These open the possibility of a wide range of enhancements which will permanently transform the manufacturing sector.
This progress is not without its challenges. With increased automation, companies must also learn how to leverage the potential of advancements such as the Internet of Things (IoT), cloud computing and machine learning. One method that will be invaluable in facing these challenges, both in the present and the future, is the concept of the Digital Twin.
A Digital Twin is a near-real-time representation of the physical attributes of a factory, product, or process. Through connecting objects generating real-time data, a digital footprint of a product, from design to production can be developed. Data can be processed and aggregated based on a range of criteria and presented in various forms depending on specific use-cases. Over time, an evolving digital profile based on historical and current behaviour emerges, leading to the development of richer models and realistic measurements of a system’s inherent unpredictability.
In the past, it was not feasible, both technically and economically, to handle the volume of data required to generate realistic digital copies of an object. However, the costs of computing, storage and bandwidth have now dropped dramatically, enabling the rapid collection, aggregation and analysis of data, generated by connected, smart technologies.
A well-constructed Digital Twin can facilitate the simulation of possible scenarios and predict possible outcomes, allowing companies to try new strategies out digitally before rolling them out in the real world. Not only does this save valuable time, but it can also help to identify possible flaws with a strategy before it is deployed and can cause issues.
A Digital Twin is not only useful at the start of the production process but all the way through. By analysing the performance of machines and the quality of a product at each stage of production, processes can be optimised to make better products at lower costs. In addition, Predictive Maintenance can alert staff to potential breakdowns, allowing for issues to be averted before they happen through the near-real-time tracking of components.
As part of this process, factory machines can also receive updates to their software and configuration wirelessly, eliminating the need for some levels of on-site support, and allowing for a centralized team to perform service tasks at multiple sites simultaneously, even in remote locations. Something which is increasingly important with frequent national lockdowns around the world.
We are already seeing Digital Twins being applied in many manufacturing sectors. For example, Reply is already working in the automotive industry with Digital Twins designed to help proactively monitor the logistics function. Digital Twins can be used for a variety of car models, generations and configurations to model the number and type of microcontrollers, sensors and actuators as well as installed software components. Reply can track production activities through a network of RFID antennas that log information on each new component box. Manufacturers can use a digital twin to harmonise the various data models and automate the process of data collection. This allows scientists to access data points (such as vehicle speed) without having to know the technical details of the specific platform.
Digital twins can also be used as a monitoring system for a fleet of assets in a factory. Thanks to individual signal sensors, alarm logs and complex state machines, manufacturers can now track a number of KPI’s including the overall equipment effectiveness (OEE). The OEE describes how well a machine is utilized relative to its capacity. If it scores a poor value on this metric signal, it indicates that machine maintenance or process optimization is needed. Additionally, alarm logs can help users understand technical problems with individual machines and utilise alarm patterns to improve performance.
By connecting different systems and processes, a product can be tracked and monitored through its entire production lifecycle. This opens the window to process optimizations, higher quality goods and reduced costs. With processes growing ever more complex, the Digital Twin offers a unique opportunity to gain control of an entire system.
Digital Twins have the potential to fully transform the manufacturing industry and solve many of its greatest challenges to maintaining productivity. This is equally true in the wake of a major world event like the current pandemic or for something as routine as introducing a new supplier or process change. Manufacturing is an early adopter of this new technology, but we will likely see this advancement spread to other industries as sectors look to survive and prosper during turbulent times. Ultimately, Digital Twins are here to stay, and early adopters will lead the way for a new digital world that mirrors and enhances the physical.
SAP Whitepaper: Advantages of Intelligent Assets
A core pillar in SAP’s Industry 4.0 strategy, Intelligent Assets equip organisations to reduce downtime, empower employees and increase efficiencies across industrial equipment and manufacturing units.
In a whitepaper produced in partnership between SAP and BizClik Media Group, Rachel Romanoski, Solutions Manager, Digital Assets, SAP, dispels some of the myths surrounding asset intelligent, and shares insight into how even small investment in asset intelligence can pay dividends in minimising cost leakage and realising an asset’s potential.
As with all innovations, the ceiling for Intelligent Assets is as high as an organisation can dream, afford and implement. But Romanoski says that just a little intelligence can go a long way: “Oftentimes people think Intelligent Assets need to be the latest and greatest cutting-edge technology. They can be super advanced, such as leveraging physics-based engineering simulations to forecast potential failures, and help mitigate them. But it could be as simple as a temperature reading. You can pull a lot of simple information from most equipment, and by enhancing that data through ancillary solutions and digital capabilities, you can create that Intelligent Asset.”
One of the most immediate benefits is reducing or, in some cases, eliminating unplanned downtime. Equipment failure is one of the most common causes of disruption and can cause chaos throughout the supply chain.
“The true power of the Intelligent Asset is in changing the basic, reactive emergency work or time-based, planned maintenance and being more prescriptive and tailored to that specific asset and use case,” Romanoski says. “Ultimately, you can reduce the unplanned events that often carry a big price tag.”
"Oftentimes people think Intelligent Assets need to be the latest and greatest cutting-edge technology... But it could be as simple as a temperature reading"
Other financial benefits include stemming cost leakage and “sweating assets” to the full potential. “Maybe you can consider the lifecycle of the asset and understand whether you can push it a little bit further,” Romanoski explains. “It might be that the best course of action for a low-cost item is to run it to failure. Having this information that we collect over time empowers those people to make those better decisions, but also has a trickle down effect to building resiliency and efficiency into the entire supply chain.”
To read the full report, including insight from Intelligent Assets, Intelligent Factories, Empowered People, and exclusive insight from Dominik Metzger, the lead on SAP’s Industry 4.0 programme, CLICK HERE.