Adapt past the disruptors to realize benefits from industrial data analytics.
Vice President of Business Development, Laurie Cavanaugh, shared her insight and experience with Control Engineering for a webcast last spring in this partial transcript from the April 21, 2022, RCEP PDH webcast.
Emerging Trends in Industrial Data Analysis
Industrial data analysis is evolving rapidly, driven by advances in connectivity, AI, and machine learning. Modern manufacturing facilities are increasingly relying on real-time insights to optimize production, reduce waste, and improve production quality. That means that understanding analytics trends can help companies stay ahead of competitors and achieve measurable operational gains.
The Source of Key Disruptors Shaping Industrial Analytics
Several factors are fundamentally changing how manufacturers approach data analysis:
- Edge computing
- Integrating OT and IT data
- AI and predictive analytics
- Cloud and hybrid solutions
Just as each of these creates new opportunities for manufacturers, it also introduces disruptors that can prevent progress. That doesn’t mean we should avoid progress — but it does shape what adapting to new technologies looks like.
Disruptors Can Slow Industrial Data Analysis Adoption
The industrial data analytics course title says “Just Enough,” but what is enough? Sometimes, enough isn’t good enough because of some of the disruptors to industrial automation. Back in the late ‘90s and the early aughts, it was difficult for those trying to sell computers into the industrial automation space.
The user adoption just wasn’t there. People were afraid of technology. They didn’t have a computer in their home at that point, or were just getting into that. Fear of the unknown prevented full forward movement of the industrial automation space.
There were generational barriers, but in just a 10-year timespan from the late aughts until mid-2010s, what really disrupted that? What started changing the minds of end users in the industrial space? It was what they were doing outside of work. All of a sudden, users are starting to become a little bit bold, a little bit more creative, and a little bit more demanding.
Now, industrial users want the tech in every hand. They say, “I don’t understand why can’t I just go up to my human-machine interface (HMI) computer or my computer on my desk at work and key in a search and get 18 billion responses in less than one second.”
Why Isn’t Machine History Available?
The online shopping experience back in those days started a little bit slow, but then when people said, “Wow, I can really buy something online? Sure. I’ll give you my credit card information. I’ll tell you all sorts of things about my buying habits.” They come into the industrial workspace and say, “Why can’t I get a log of what just happened on this machine? The maintenance history or background. Online retail knows my whole buying experience.”
With social media, everybody becomes connected. There’s a passion for using technology. There’s a reason to use it. If I can’t even get a picture of the latest version of the panel that’s running this device, there’s a huge disconnect.
The other thing that social media started to do was make everybody become an expert; everybody has an opinion, has a thought, an idea they want to share, and they want to collaborate. In the industrial workplace, the same kind of collaboration space was developing in tandem.
Then, cyber threats started to grow. It started as hackers playing around until they decided that they needed to disrupt things because there are organizations or companies that they can extort money from, or just cause disruption for disruption’s sake. Cyber threats continued to become a bigger risk over that 10-year timespan. To properly protect industrial control systems, we needed to understand what’s going on inside those machines.
The Real Meaning of “Just Enough” Data Analytics
When we talk about just enough data analytics, it means that a heightened sense of demand exists, and the pendulum has swung. Now, the industry needs to hurry to provide the context, quantity, and quality of data that industrial users – whether it’s the top floor CEO down to the shop floor operations, plant management, or safety – are trying to get, by accessing information in the context they need.
Users can be anywhere, anytime, and need to be able to access appropriate information. That’s the user expectation. We went from online shopping and doing a transaction to microphones listening to some of my apps. (I would advise looking at which apps have the microphone enabled.)
Interestingly enough, I was talking about [a particular brand of] motors all day and, in my Facebook feed, there was an advertisement for those motors. Artificial intelligence (AI) and machine learning (ML) are being applied to push notifications. These are the day-to-day experiences outside of the workplace. Cyber threats have a shopping experience of their own called the dark web.
Cryptocurrency has added the ability to extort people or companies, and we might not be able to be tracked or traced. The global pandemic has affected everyone in a variety of ways, many good, some not so good, but the challenge from an industrial perspective is to find just-right industrial data analytics available commercially.
The lesson is that a wide and deep data source is needed, because the context of information required for industrial application is unknown.
Supply Chain Problems are Still Plaguing the Automation Industry
The technology chip shortage has been a huge disruptor, but given what the pandemic did to unemployment in certain sectors, car manufacturers couldn’t just shut down manufacturing and production of cars. They started parking cars across a variety of open vacant lots. There was a huge push to create wireless mesh networks to find all the VINs of those manufactured cars when the chips became available. There’s been this compounding need for the right kind of data and the right kind of analytics.
E Tech Group: Undisrupted by Industrial Data Analytics Disruptors
The industrial automation sector is complex – filled with these kinds of obstacles, dilemmas, and pitfalls. However, each disruptor is an opportunity for innovation, and this is the theoretical framework E Tech Group, a leading control system integrator, works under.
We design, build, implement, and support turnkey factory automation systems that keep your facility secure, with user-friendly control panels, complete system integration, and room to adapt, expand, and scale. With the right approach and the top automation partners like Rockwell and AVEVA, E Tech Group helps manufacturers stay competitive and poised to grow.
The original version of this article was published in Control Engineering.