Industry 4.0 – Everything is Digitising, Bit Byte Bit
Published on : Monday 30-11--0001
I was at the DistribuTech conference last month – my first time – and got a firsthand view of Industry 4.0. I saw what GE’s Jeff Immelt meant when he said that “every industrial company may have gone to sleep an industrial company but will need to get up as a software and analytics company”.
You wouldn’t be blamed for thinking that you had stumbled into a software and sensors conference. Almost every keynote or conference talk included the words, “connectivity, IoT, sensors”. (All except an entertaining keynote by Michael Webber, who talked about Water and humanity's top 10 challenges).
Every major exhibitor had a software and networking strategy for their sensors, i.e., Industrial IoT. They showcased boxes for edge computing and edge-to-cloud and edge-to-enterprise secure connectivity with every connectivity mode possible; and software platforms for seamless integration and API development. I heard a lot of AI and Machine Learning as well, although mostly at a conceptual level.
Digital Twin
GE has developed a concept called the digital twin, which is essentially a real-time sensing, simulating, computing and analysing digital copy of deployed assets.
This is IoT on steroids.
In the future, a software technician sitting in Austin, TX could monitor real-time diagnostics of a turbine (the deployed asset) in Iowa, and can order parts or a new service before any failure mechanism sets in. Extending this futurism; this technician, upon detecting a hardware fault, commissions an onsite robot to relocate to the fault location and fix it while she watches it on a live video feed. Further, if necessary, she fixes it with her “own hands” by mapping her fingers onto the robot’s. In order to get a real feel of the situation, she has special gloves that provide haptic feedback and uses VR goggles to immerse herself in the true environment.
Sensors, Data, Networking
There were the other known concepts on smart grid, smart buildings, smart lighting; all of them about how you can obtain bits (data) from the atoms (the sensors) and eventually use newly generated bits to ensure the smooth flow of electrons (power) while ensuring that spurious bits from unknown sources don’t interfere with your bits, atoms and electrons.
Obviously, these are economies of massive scale, and for several reasons the deployments are going to be the preserve of large companies. Even the customers are going to be mostly large entities, for example utilities. That said, tremendous software and hardware opportunities exist for smaller vendors in the Industrial IoT food chain: Sense @ node -> compute/analyse @ node -> transmit to edge -> assimilate, compute/analyse more; store -> transmit back to node and/or transmit to cloud -> compute and analyse in cloud. Throw in the gobs of data generated and you have made a case of data science, AI and machine learning.
Wireless power play
I can't not write about this.
How do you power the millions of sensors and thousands of Automated Guided Vehicles (AGVs)/robots? Running wires can be complex and nearly impossible in some cases. Therefore, power will be a mix of wired, wireless (RF, magnetic induction, capacitive, other), and battery-driven. For example, the high-power robots and AGVs are higher energy devices and will be recharged either via wired connections, or magnetic induction if induction can justify the costs (e.g., long-term energy), for the benefit (e.g., safety, convenience, aesthetics). Low power remote sensors will be powered either by batteries that last for a few years, energy harvesting or RF power.
Caveats & Conclusion
The industry is still poking at the IoT beast.
While I didn’t meet any naysayers at the conference, there was a wide range of “when”. The Industrial IoT industry is at a point where the wrist wearable industry was a year ago and where the VR/AR industry is at currently. There are a lot of cool sensors and technologies that can provide us with good information and stellar analytics and visualisation, but the "so-what" of it is still being answered. Some technological barriers still need to be crossed and desired outcomes still need to be proven.
All said, infrastructural changes always are slow moving and the question of "if" is no longer being asked.
For better or worse, most massive deployments are not decided by the average consumer (but often paid for by them). Instead the decision is made by utility companies, several of whom have already embarked upon IoT-isation of their grid (see case studies1) and even opening up grid data to external agencies (e.g., NYPA) for new applications.
Did you know?
Thanks to Netflix, the UK national grid is less reliant on France for power.
Before Netflix, the UK grid would experience a 3 GW power surge for 3-5 minutes after a popular TV show ended. This was due to 1.75 million households powering up their kettles at roughly the same time. To handle this surge, UK would "borrow” power from France. With Netflix and DVR schemes, the time at which the kettles are switched on has skewed, thereby ending the power surges. Merci mais, non merci.
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- Klaus Schwab, The Fourth Industrial Revolution
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