The Next Level
Initially, IoT capabilities and machine learning involved a huge investment in complex software and deep expertise. However, as with most new technologies, implementation has become more cost effective as cloud technology and streaming analytics have evolved and become more widely adopted. “As soon as you say Big Data, everyone thinks that means big money,” Masson noted. “I think that’s changed. You don’t have to have massive investments in server farms and specialists in big data to build that infrastructure. We’ve driven cost down to the point where even the smallest manufacturer can hook up equipment and start to experiment.”
Beyond cost, manufacturers worry that more connectivity will open a door to cyber threats. “People want to connect everything to the Internet, but it’s just like connecting your PC to the Internet,” says Bryan Tantzen, senior director of Cisco’s manufacturing IoT business. “You better have a firewall, anti-virus software and security plan. We hear about baby monitors being hacked, televisions being hacked. When connecting a plant to the Internet, security is something you really have to think about.” From theft of intellectual property or sabotage to cyber mischief that could interrupt operations, CEOs pointed to a number of potential security risks raised by the IoT. “There are several levels,” said William Brindley, technology manager at Pratt & Whitney. “There’s a tragedy level—shutting off two engines on a two-engine aircraft. Another is an interruption in our manufacturing capability that shuts down a line or shuts us down entirely.
And then there’s classified information because we’re a defense contractor and we’ve experienced incidents of our vendors being hacked. So we are very connected inside of our four walls, in our intranet, but we don’t connect our manufacturing capability outside those walls.”
Strong security protocols, however, can overcome such resistance, noted Dyck. “When we were working with an automotive supplier, initially he said, ‘Heck no, you will never put my data into the cloud,’” Dyck recounted. “But when we dug deeper into his $18 million maintenance budget and showed him we could prevent downtime on big hydroforming presses, all of a sudden the story changed to, ‘If you can convince my IT people this data will be secure, we’ll have that conversation. And we did, and we are.”
ThyssenKrupp: Lifting Productivity
Over the course of a lifetime, the average urban office worker spends literally years waiting for or stuck in elevators, according to a recent building-efficiency study. Clearly, keeping elevators running smoothly can have a significant impact on worker productivity—and, in turn, offer a competitive edge to the elevator company able to deliver what matters most to its customers in buildings all over the world: reliable service.
That’s why ThyssenKrupp Elevator decided to look for ways to move from preventative maintenance to pre-emptive maintenance by harnessing the Internet of Things. The company worked with Microsoft and CGI to collect data from sensors and systems and draw it into a central, cloud-based dashboard for a real-time view of key performance indicators. By feeding data about things like motor temperature, shaft alignment, cab speed and door functioning into dynamic, predictive models, the company was able to anticipate repairs—to know which cabs would need repairs before they even went down. Its technicians can access information about the 1.1 million elevators ThyssenKrupp maintains worldwide in real-time from PC dashboards or mobile device.
The result? “We have the ability to use live data to bring elevator reliability to new heights, reducing costs for ourselves and for our customers,” says Executive Chairman Andreas Schierenbeck.