As first published by Internet of Business: https://internetofbusiness.
In five years’ time, it’s quite likely that devices will run much of the world through their own private Internet of Things. There could be billions of them and they’ll all have their own virtual “mini-me.” But there’s no need to worry and here is why.
Until fairly recently, the only way to monitor production equipment was to physically monitor the results. This had many limitations. It was bad enough that it was a time-consuming, laborious task, but what was even more problematic and expensive was that it gave designers few chances to change their prototype before it became the finished product. The old system offered few opportunities to shed light on how a product was evolving.
Now, a combination of micro-sensors and software has created a system for the micro-management of manufacturing production lines creating some much-lauded efficiency dividends. They achieve this by a twin operation, where they jointly measure every tiny aspect of a physical device and, using these reports, recreate it in digital form, somewhere in the cloud. This software representation of the device is known as its “digital twin.”
Digital twins aren’t a new concept—the University of Michigan unveiled the first prototype in 2001—but recent breakthroughs in industrial connectivity and machine intelligence have boosted their impact.
Once manufacturers have a digital twin of a device, they can test it, tweak it, and tune it throughout the process of building it. By the time it is deemed ready for industrial production, it will have been honed to perform with maximum efficiency. The digital twin comes into its own by feeding back intelligence throughout the lifetime of the asset. It’s not just about cutting prototyping or construction costs, but predicting failure and cutting maintenance costs and downtime.
Digital twinning creates efficiencies across the entire production system too. For example, imagine if all the equipment in a wind farm had a digital twin. The digital twin could be used to configure each wind turbine prior to procurement and construction. Once the farm has been built, each virtual turbine could use data from its physical equivalent to optimise power production at plant level, just by small tweaks such as adjusting turbine-specific parameters like generator torque or blade speed.
The digital twin approach is easiest to apply in vertical markets where one vendor has complete omnipotence. If these disciplines could be brought to the supply chain, there could be economy-wide gains. However, the involvement of multiple vendors and new manufacturing techniques makes that more of a challenge.
The key to tackling these complexities is to help small suppliers adopt a digital approach. To this end, the US government’s Digital Manufacturing and Design Innovation Institute (DMDII) is funding an appeal for examples of digital twinning by supply-chain participants, especially small manufacturers. If all participants in the chain can commit to adopting digital-twin models with their suppliers and partners, there could be immense economic dividends for everyone.
Typically this might involve a partnership between a global vendor say, and a small local specialist. Each can provide something the other needs. Leverage on one hand, and agility on the other. Together they can test, develop, and validate digitally.
It’s precisely this need for machine-to-machine harmony that inspired TIBCO to take a lead in integrating devices made for the IoT.
The twin axes of TIBCO’s strategy here are Project Flogo and the TIBCO Graph Database. Project Flogo is ultra-lightweight integration software, which is designed to get into even the tiniest of spaces and, being open source, aims to work with anything. It is so unobtrusive that its average installed footprint can be 20 times lighter than conventional middleware like Node.js. Indeed, it’s 50 times lighter than Java!
Its minimal presence doesn’t stop it from referencing the powerful translytical Graph Database. The rationale is to give developers the broadest possible range of options when creating IoT environments. The TIBCO Graph Database creates all these possibilities through its signature specialist function, which is to make sense of a complex web of dynamic data and translate that into intelligence that can be rationalised and acted upon instantly.
With the pairing of Project Flogo and the Graph Database, TIBCO has created its own unique contribution to digital twinning. Combined, these technologies increase interconnectivity, augment the intelligence of the IoT, and expand the edge of digital business for organizations. It’s a partnership of one small, but immensely powerful, reporting tool linking with a massively powerful brain in the cloud.
Now is the time to allow the machines—and the results—to speak for themselves.