Digital industrial transformation is about more than just…well, digital. At the heart of any smart, connected system–be it a collection of assets in a plant, a smart factory, or a fully-interconnected digital supply network–is data. Knowledge. The illumination of previously unknown information about the inner workings of physical production and digital operations systems, about people and assets. And the ability to take that information and use it to know more, make better business decisions, improve performance, and better anticipate the future. In short, turning insight into informed action.
I was privileged to present alongside my colleague, Mark Cotteleer, at Minds + Machines 2017 earlier this fall in San Francisco.
While I was excited to talk about the rise of Industry 4.0 and the evolution of the smart, connected, data-driven factory, I came away with much more. It’s always exciting to hear what others think, see some of the newest developments in technology, and listen as some industry leaders share their knowledge. For me, it highlighted the incredible reach and breadth of digital industrial transformation: its impact not only on a multitude of industries and sectors, but on the very fabric of day-to-day business, innovation, manufacturing, and society.
In our talk, we focused on the spectrum of possibilities made possible by Industry 4.0, from predictive maintenance to the digital thread, from the digital twin to the smart factory. While each is a step forward in complexity from the one before it, one thing they all share in common is the use of data to drive decisions, learn, self-adapt, and predict future scenarios. In short, to build a more flexible, agile manufacturing network that is more receptive to change. With this broad array of choices, the most difficult task can simply be getting started.
Walking though the Tech Hall to see the various demos seemed to bring many of these abstract concepts to life. The ability to interact with various technologies, touch assets, and experience various simulations helped crystallize some of those choices and suggest what they might look like in real-life applications. What’s more, other specialists talked about specific uses of predictive maintenance, the digital thread, and the digital twin in oil and gas, aviation, and industrial settings–providing concrete examples of the journeys companies can follow as they seek their own digital industrial transformation.
The biggest thing I came away with after Minds + Machines, was the confirmation that the technology to support digital industrial transformation is, in many cases, here now. There is a broad spectrum of opportunities to use those technologies–so many that it can be difficult to choose. And the myriad of choices can lead to paralysis, making it easier to remain frozen in place for fear of making the wrong choice or taking a risk. But doing nothing can pose the biggest risk of all. For all the choices out there, the best choice may be to simply get started.