Vision-enhanced robots that can halt their movement on a factory line if they sense an obstruction. Smarter real-time condition monitoring systems that can alert you that a fleet vehicle is going to need service soon because it’s been slogging through lousy weather. Sensors and drone-enabled digital photography that combine to create a rich facility data history that can help a utility company, for example, spot an emerging structural problem at a substation before it can turn into a catastrophe.
It’s not science fiction, and it’s not a vision of the manufacturing and materials movement environment 20 years from now. It’s what context-aware technology – tech that detects and records details about the environment in which an asset is operating – looks like today. And it’s what industry giants like Caterpillar and Boeing are investing in heavily in their efforts to slash inefficiencies and remain as competitive as possible.
“The technology is there,” says Rick Veague, CTO at IFS North America. “This isn’t stuff that people are dreaming up right now. It exists; it’s real; it’s usable.”
And yet for a large swath of discrete manufacturing organizations, context-aware technologies aren’t in use – yet. That’s a problem, says Veague, because an asset “doesn’t exist in a vacuum; it exists in some context.”
Being able to correlate different types of data – including details of an asset’s operating and maintenance history and the precise conditions in which it’s operating now – can help manufacturers make smarter, just-in-time maintenance and production decisions, say context-aware tech’s biggest proponents. In fact, context-aware technologies are an essential part of asset management’s transformation into a predictive rather than reactive enterprise, they assert.
More-widespread adoption of context-aware tools should follow from falling costs for sensors and new automation technologies, but it also will hinge on a clear understanding of what the technology can do and why it’s worthwhile.
Let’s take a look at five top questions about context-aware technology.
Part 1: What does it look like, and what's it worth to my company?
Part 2: Who's leading the charge?
Part 3: What are the hurdles to adoption, and what's next?