IoT (“Internet of Things”) has now been a buzz word for several years. It refers to the network of physical devices that operate using internet connectivity, and it’s in-demand among hobbyists and professional programmers alike.
However, some remain skeptical of the idea that every appliance or device should have an internet connection. It may be convenient for your refrigerator to let you know it needs service, but won’t we take care of these needs “manually” on our own? Is all this connection really helpful?
In industry, things are a bit different. If a single component fails, so does the machine, potentially halting an assembly line for hours and costing the company huge sums in lost production. With that in mind, the extra cost and complication of adding sensors to a device becomes much more practical. In fact, this concept has even been able to justify its own buzz-term: IIoT, the Industrial Internet of Things.
Reactive < Preventive < Predictive Maintenance
Visit a manufacturing facility today, and you’ll notice that they operate in one of three ways:
1. Reactive mode: Engineers fix problems when they occur. This means that machines speak up when a problem arises, which can lead to unscheduled work stoppages and missed deadlines.
2. Preventive mode: Some facilities schedule maintenance either by date or when a machine produces a certain number of parts. With advanced notice, supervisors can adjust production schedules and workloads accordingly. On the flip side, preventive maintenance also means downtime and replaced parts just because “it’s time.” Engineers design preventive schedules based on experience with the equipment, but all too often those professionals swap out used parts because there’s an opportunity, not because those parts show signs of age or damage. Preventive maintenance modes can still cost facilities time and money.
3. Predictive mode: With this system in place, sensors and computers continuously observe the machinery for indications of imminent failure.
To employ an effective predictive maintenance program, it’s critical to have the proper sensors and machine learning configuration. Engineers and technicians can observe and interpret signs of wear but can’t continuously analyze the way a machine can. For that matter, IIoT sensors can see things that humans cannot without specialized equipment.
A predictive system can combine many sensors and the production data they compile into one amalgamated plant snapshot. We’ve identified several companies and technologies that help record and use machine data, striving toward the goal of true predictive maintenance and no unscheduled downtime.
Petasense – Compact WiFi Vibration Monitoring
Image Credit: Petasense
An advanced predictive maintenance system sounds like a great idea, but setting one of these systems up involves a lot of work. Engineers might also worry that sensors wouldn’t work with older equipment. Here are some products Petasense has developed for use:
Vibration Monitor. Petasense sells a small sensor unit that mounts onto your vibrating equipment with a stud or epoxy, then transmits vibration and temperature data to your plant network via WiFi. If you have access to WiFi in your facility, you can have your unit up and running in a few minutes.
WiFi Transmitter Module. Vibration tracking and temperature monitoring is useful in many situations— since energy and power generation form the bulk of Petasense’s customer base— but these sensors aren’t appropriate for all situations. Petasense recently introduced a WiFi transmitter module, which is able to take in data from a variety of sensors. Setup is more complicated than simply attaching a sensor to a motor, but this module allows engineers and technicians to monitor more types of machinery.
Cloud Services. Along with the physical sensors, Petasense features an Asset Reliability and Optimization (ARO) cloud service to monitor and optimize maintenance planning. ARO takes advantage of the Google Cloud platform, allowing practically limitless scalability, along with access via the web or mobile devices. The system can also be implemented on your own private cloud.
Civionics – Your Sensors to the Cloud
Image Credit: Civionics
Civionics’ IIoT sensor modules are known as Percēv Nodes.
Here are some quick facts about these modules:
1. They’re Powerful. Each sensor takes in data from an internal temperature sensor and accelerometer, as well as up to 20 external wired sensor units.
2. They Use the Cloud. Civionics designed these Nodes to link to a central “CloudGate” hub using a ZigBee compliant protocol. This protocol can communicate via WiFi, wired Ethernet, or even a cellular for ultimate versatility.
3. They’re Battery Powered. Each node is battery powered with a targeted lifespan of at least 18 months between changes, though three years is common, and some even last up to ten years. CloudGates are generally wall powered (though can utilize a battery in some situations) compensating for increased power demands, especially in a cellular configuration.
With these versatile sensing and communication capabilities, engineers have put Civionics’ sensor to use in widely varied fields, such as:
- manufacturing
- energy production
- infrastructural applications like tracking data for bridges and pipelines
One success story occurred at a Chrysler stamping plant that implemented Civionics’ sensing package to monitor equipment including presses and robots. After just two years, the system has reportedly saved over two million dollars in unexpected downtime.
Civionics’ cloud platform is known as the Percēv Decision Workshop, a suite of software for data visualization and analysis. Customers can use their external cloud for this software, or Civionics can set it up at a customer’s facility and customize it as needed. Notably, in April 2018, Civionics was acquired by Grace Engineered Products, a Rockwell Automation Encompass Partner. This kind of consolidation may hint at the advance of predictive technology systems in the future.
Other IIoT Options
Petasense and Civionics are only two of the players in this emerging field. Companies like 3DSignals are active in this space with sound-based monitoring solutions, while ABB offers vibration monitors in a similar configuration to those made by Petasense. Other well-established companies such as Allen Bradley, Siemens, and Fluke also feature their own IIoT offerings, and we’re sure to see this lineup expand soon.
Manufacturing can be a stressful environment—no one enjoys the dreaded 4:30 PM call that will take hours to resolve— but predictive maintenance may help eliminate these emergencies in the future. Predictive monitoring allows engineers to go home on time, avoids sending other employees home early, and can increase a company’s bottom line. Add to that a simple installation, and IIoT innovations become a win-win for all involved.