Shifting to autonomous industrial operation is about relieving people from ‘dangerous, dull and dirty’ and opening up more interesting roles for them. The evolution of the control room is fascinating, and we’ve already gone from individual control rooms to consolidated centralized control rooms and integrated remote operations centers. Technology for remote operations has been available for some time, however many companies just never adopted and prepared for it. COVID expedited that. Those companies who didn’t implement remote capabilities were at a disadvantage compared to their competitors. Having people in the office required a much bigger spend, as well as risk, to ensure their facilities were compliant with the health regulations.
We provide technology that lets customers run, monitor, optimize their operations and work truly remotely, from thousands of kilometers away, negating the need to travel to remote areas. It’s first about safety, but also better decision support systems, leveraging AI and ML to operate plants with predictive analysis based on years of data. This technology can make decisions in the place of human operators, getting us to the autonomous state. But it isn’t about taking jobs away, it’s evolving them. When we evolve roles to autonomy, the invaluable human knowledge gets embedded into the AI/ML models so that data and insights empower every role to excel.
We will always need people to continuously evolve those models, and we need to support them in developing their skills to work with autonomous technology. It will result in increased productivity that will make jobs more secure and more valuable. You need years to understand how industrial processes work, especially for a specific site. It’s much easier to learn the newer technology than how a process works – the process part is more valuable and highly sought after.”
It’s also important that we address industry’s knowledge retention issue. In the past, people stayed in the same job, with the same company for decades, and they knew the processes inside and out. The current generation does not stick around in one process area or even one company – they are mobile. Understanding some of these processes can take years, so how do we address that and transfer 10-20 years of knowledge to an incoming operator or engineer in less than 2 years. That’s why going autonomous and equipping human operators with these decision support systems is really not a matter of choice: you must do it.
Data rationalization and integration is essential for digital transformation, and companies must not put off addressing it for a minute longer. In order to build autonomous operations and harness the power of AI and ML, your data has to be fit for purpose. New companies start out knowing they need to set up a common data lake, but older companies have such a range of data in different locations and consolidating it is very difficult. We have experienced customers realizing they have different systems from region to region or site to site including some that require custom connectors.. Add to that the speed at which we’re collecting data today, which means there’s often too much data. Companies must invest the time and resources to rationalize and integrate their data. It’s vital that they are choosing the right platform to structure it and allow collaboration. That will enable different vendors to interact with the data, and even when data is in different locations, it can be integrated seamlessly. Honestly, it’s a huge challenge, but it’s urgent.