The IIoT is the harbinger of real change

August 8, 2017 Saar Yoskovitz, Augury

“We wanted flying cars, instead we got 140 characters.” Peter Thiel might have been talking about the Internet of Things (IoT) in his quote about pipe-dream technology. Despite all the hope, hype, and funding that’s poured into the IoT and its affiliated products, the only changes we’re witnessing in daily life involve home-oriented conveniences.

While IoT devices like Alexa, Nest, and the Ring doorbell are convenient, consumer-oriented technology doesn’t represent the real revolution. The biggest changes lie out of sight and behind factory walls. This is the Industrial IoT, or IIoT.

Through innovations in connectivity, big data, analytics, and machine learning, the IIoT is changing the way we do business. It promises to upend manufacturing the way the cloud changed computing, bringing on a new era of efficient, cost-effective maintenance approaches to money savings.

Manufacturing can be a symphony of machines, parts, operators, suppliers, and maintenance. It can also be a chaotic mess, if one step in the process unexpectedly breaks down. The newfound ability to connect the many complicated parts of this equation marks a giant leap toward simplifying industrial processes, increasing both efficiency and productivity on a grand scale.

For example, when a machine can monitor itself for inefficiencies or malfunctions, it can automatically notify the appropriate parties when necessary. Technicians and managers can move beyond guessing games and instead arm themselves with the critical insight necessary to make adjustments and repairs. Whether taking a machine offline for repair before it breaks, or knowing exactly when to order a special replacement part to avoid costly downtime.

The IIoT is the conductor the manufacturing orchestra has always needed. It can process information from a multifaceted operation and dictate real-time changes to accommodate shifting circumstances, including customer demands, changes in weather, equipment condition, and labor force fluctuations.

A maintenance tech's dream

A facility’s health is judged by the health of its equipment. Preventive maintenance (PM) methodology, which dictates following a schedule for equipment inspection and replacement, has long ruled as the norm. The proliferation of sensor technology in the IIoT, however, is changing this practice, replacing PM with PdM, or predictive maintenance. Instead of calendering equipment maintenance at predetermined intervals, sensors placed on machines in everything from the largest production systems to HVAC equipment, allow maintenance crews to monitor equipment health in real-time.

Previously, this practice had been reserved for only the largest and most critical machinery, as it was expensive and involved a complicated implementation. Unfortunately, even the most inexpensive parts can become critical when it breaks down and ceases all production. With recent advancements in mobile and cloud technologies, however, PdM has become both affordable and easy to roll-out, bringing this former-pipedream technology to reality, and bringing PdM to all levels of the manufacturing process.

The obvious downside to PM is that outside the maintenance cycle, parts can become misaligned, wear faster than expected, or might have not easily-detectable quality defects that lead to unexpected downtime. PdM, however, can see things that are invisible to the human eye. PdM practices include monitoring and analyzing vibrations, ultrasonic emissions, and lubricating fluids. Modern PdM incorporates Internet-age practices, capitalizing on machine learning and data algorithm technology, to pick up on the telltale signs of impending failures.

Boils down to the bottom line

Profit is a balancing act. And in any facility, all systems have to work in conjunction, or else failure means reduced productivity and inefficiencies mean wasted money. The IIoT gives vendors the ability to keep tabs on everything at once, through a new, higher level of insight and control.

In the not-too-distant future, we may see production lines that aren’t only just-in-time, but small-batch and personalized, automated from raw material to drone delivery. Repair emergencies will become less common, and the nature of insurance itself will change so that premiums are reduced based on prevention. The whole system, in other words, will be overhauled.

Saar Yoskovitz has extensive experience in machine learning, signal processing algorithms, and system architecture. Prior to founding Augury, he worked as an analog architect at Intel. Saar holds a BS in electrical engineering and a BS in physics from the Israel Institute of Technology (Technion).

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