Cloud Computing, Industrial Autonomy, and Corporate Sustainability
Quick hits:
- According to the Environmental Protection Agency, data centers now account for 1.5% of all electricity consumption in the U.S.
- By training machine learning models on larger quantities of data than any one company has access too, a cloud server can provide optimizations that would not be possible should local, on-site resources alone be used.
- When asked “what level of impact are you expecting industrial autonomy will have on the following applications in your plant in the next three years?” 45% of respondents to a Yokogawa survey stated that autonomy would have a significant impact on environmental sustainability.
Hello and welcome to Take Five with Automation World. I’m David Miller, Senior Technical Writer for Automation World. Today, I’m going to be talking about cloud computing, industrial autonomy, and how they can further corporate sustainability initiatives. So, first it’s important to define our terms. I think cloud is easy enough – When we say that we’re taking about using a large, centralized server that streams to many locations simultaneously, as opposed to many smaller, local servers. But the term industrial autonomy perhaps requires a bit more explication.
So, whereas industrial automation typically refers to machines with the ability to perform highly-structured, pre-programmed tasks in lieu of human labor, the term industrial autonomy describes systems that are capable of adapting independently to diverse challenges with minimal human intervention. In this case, we’d be talking about things like AI or machine learning, which might do something like allowing a robot or machine vision system to train itself on new items and objects rather than requiring a human operator to do so for it.
Now, finally, we come to sustainability. Again, simple: Waste reduction, emissions reduction, and energy management. We’re talking about doing more, or the same amount with less waste, less energy consumption, and fewer emissions.
But how do the Cloud and Industrial autonomy further sustainability goals? Well, first of all, when it comes to the cloud its noteworthy that, according to the Environmental Protection Agency, data centers now account for 1.5% of all electricity consumption in the U.S., which is obviously going to have sizeable impact on overall emissions, since energy production, generally, is going to have a carbon footprint. So, by eliminating these local servers, you’re using less electricity, energy consumption is slashed, and so emissions are slashed.
Now, that’s fairly straightforward, but the other way the cloud enables sustainability is simply by enabling industrial autonomy, which has its own, separate sustainability benefits.
So, the cloud enables industrial autonomy by greatly expanding the pool of data that AI and machine learning algorithms can be trained on. Basically, by training these models on larger quantities of data than any one company has access too, a cloud server can provide optimizations that would not be possible should local, on-site resources alone be used. And what are these optimizations doing? They’re providing more intelligence – the sort that can enable industrial autonomy, which can make production vastly more efficient. So when an operation becomes more efficient, it’s not only becoming more profitable because it’s using fewer inputs in order to yield the same amount of output, but it becomes more environmentally friendly too, because it’s using less energy, fewer materials, and so on.
And it turns out that many in industry actually agree. Recently, Yokogawa conducted a survey to gauge the use of industrial autonomy among respondents. What they found was that sustainability was one of the areas where industrial autonomy was expected to have the biggest impact.
So, when asked “what level of impact are you expecting industrial autonomy will have on the following applications in your plant in the next three years?” 45% of respondents stated that autonomy would have a significant impact on environmental sustainability, including dynamic energy optimization, water management, and emissions reduction, making it the most selected category, above robotic surveillance and inspection, AI-enhanced process optimization, and supply chain optimization.
More specifically, autonomy was most expected most of all to aid in waste reduction, with 38% of respondents anticipating it would have a high impact. After that, 35% of respondents anticipated autonomy having a high impact on greenhouse gas reduction, and 34% on energy management.
So, if you’re interested in sustainability and some of the emerging technology trends that enable it, this is something to keep your eye on, and you can find more information in the links below this video.