There are a few common themes running through this year's tradeshows, user groups and other gatherings. Chief among these are the Internet of Things (IoT), Industry 4.0, smart manufacturing, intelligent devices, Big Data and the Cloud. All of these concepts are supposedly bringing earth-shattering changes to process control and automation in particular and to manufacturing and business in general.
Certainly, significant changes are continuing to come from multiplying Internet connections, but this trend has been steadily unfolding for 20 years. Sure, more machines and other equipment now have web pages and can broadcast their data, but this is really just more of the same Internet. IoT just sounds more dramatic.
Similarly, all the added information these devices are generating simply means more of the same data from more places, but Big Data just sounds more exciting. Again, the Cloud sounds more profound and powerful than just adding more rack-mounted servers to the same bunch of servers in a closet somewhere, either onsite or at an offsite service.
Finally, I know that smart phones, tablet PCs and other devices with onboard data processing are allowing wider access to operating performance and other key indicators, but isn't this an added degree of availability rather than a profound leap in intelligence, awareness or critical thinking skills? When sources tell me they're getting into smart manufacturing or the interconnectedness of Industry 4.0, I ask, what were they doing before? Weren't they supposed to be manufacturing as intelligently as possible all along? I'm not trying to be unkind. I just need specifics to put together useful stories.
So how can you separate the few useful truths from the vast cacophony of hype and baloney? Well, you can cut through the fog of buzzwords and vague statements about IoT and the rest by focusing on any specific gains users achieve in actual production processes, learning what tools and best practices they use, and then adapting them to your own applications. These efforts are aided by the fact that most Ethernet-based, Internet-enabled and other industrial networking components are much easier to configure, secure, deploy, monitor and manage than they were just a few years ago.
For instance, at GE's IoT World Forum on Oct. 13-14 in Chicago, John McGagh, head of innovation at Rio Tinto, reported his company's huge mining cranes and trucks generate lots of data that can help improve operations and maintain equipment, but that much of this information wasn't collected and organized to enable better decisions until recently. With 32 engine sensors and 120 drive sensors on each vehicle, Rio Tinto's 900 trucks produce about 4.9 terabytes of data daily.
"We have about 300 sensors at our Kennecott copper mine in Utah, but we were only pulling about 5% of their available data, and we needed a lot more," says McGagh.
To capture and use more of this information, McGagh reports that Rio Tinto worked with the University of Sydney to develop its three-part Mine Automation System (MAS), which pulls in and organizes data from all its mines worldwide, then uses a visualization engine to paint a detailed picture of operations at each facility that users can act on in real time. MAS includes a compilation system that collects all sensor data and creates a mining model, while its planning system schedules jobs and its control system sends instructions to often autonomous transportation and drilling equipment.
"Now, at mines like West Angelas in western Australia, we can talk to the three machines drilling 12-meter holes for blasting," explains McGagh. "These machines are sensor platforms, and their information combined with other sources lets us interact much more closely with the mine's geology, and that's extremely valuable to us. We can also use Big Data to look at the history of blocks mined, and this helps us make even better decisions."