Wireless Remote Monitoring

Killing Five Birds with One Stone

Wireless remote monitoring: a game-changer that reduces maintenance costs, capital expenditures, labor and unplanned downtime while improving safety.

Rarely in the field of industrial maintenance does a game-changer come along, and even when it does the resistance to change often defies logic. (Where else do you find businesses that still pay $40,000 for a tablet computer?)

Let's face it, most opinion leaders in maintenance organizations across the U.S. are planning for retirement and have no desire to rock the boat, and that may leave their organizations vulnerable, and their supervisors uninformed and ill-equipped to anticipate the coming change.

The pervasive mistake, committed by legions of businesses a decade ago, is to underestimate the potential for online maintenance strategies to move the economic needle of the enterprise.

Like it or not, a game-changer is here, and it's in the form of remote wireless monitoring.

Why is the future coming so fast?

Because the so-called "internet of things" changes the equation, just as the internet has altered everything else.

Wireless remote monitoring will have effects far beyond the maintenance organization and even beyond the plant. It has implications for how the senior-most officers of major industrial enterprises will be judged by regulatory bodies and capital markets alike, and for the competitive strategies of the OEMs and industrial service suppliers that supply these enterprises.

Starting on the plant floor and working our way into the boardroom, let's see how.

How it Works

The routine data collection with which many maintenance personnel are tasked is mind-numbing.

If they won't tell you themselves, check the logs, or better yet, study the turnover in positions assigned to the task.

Compliance with data collection regimens is abysmal because the task is boring and sometimes dangerous.

It's easy (and often self-serving) to question the value of the data. The vast majority of it is not actionable; that is, the data says the machine is healthy, or maybe healthy enough.

But once a year, or maybe twice, the data heads off a catastrophic failure and saves a bundle, from hundreds of thousands to perhaps millions of dollars depending on how the enterprise measures costs, from unplanned maintenance costs to unplanned capital expenditures, spoilage, and opportunity cost. And a dozen times a year, or maybe more, the data sees a failure coming that can be addressed during a scheduled shutdown.

But you have to be taking the data to see the incidents coming or you're turning a blind eye – quite literally choosing to turn a "knowable unknown" into an "unknown unknown," in Rumsfeld's famous parlance, and that's a mistake because the value of rigorous data collection is incontrovertible.

Unplanned maintenance activity and all its attendant costs can be reduced as much as 95%, and unplanned shutdowns and capital spending can be eliminated.

These missed opportunities become errors of commission as soon as the organization neglects to take data, and the dollars and cents add up fast, so you have to take the data, right? Maybe not.

Sensing Solutions

The convergence of remote sensing and wireless technologies has produced robust and dependable commercial remote wireless sensing solutions. These consist of wireless communication-enabled sensing devices such as accelerometers permanently mounted in strategic locations on machinery throughout the plant.

The communications modules can be battery or line powered and programmed to take data as frequently as desired, from several times a day to once a month.

Automated data collection with a wireless remote monitoring solution solves the pervasive compliance issue, reduces the burden on labor, which can be put to more productive uses, and keeps personnel away from dangerous machines.

More data more consistently collected means more avoided failures, fewer unplanned shutdowns, less unplanned maintenance activity and a safer work environment, and those are just the plant level benefits.

Once the data is on the network it has far broader implications for the enterprise and its suppliers.

In particular, large multisite enterprises can aggregate the data in powerful ways:

  • It can be used to "see" risk, track spending, and benchmark uptime within and across production operations.
  • It can also be organized by asset type and vendor to supply feedback, identify persistent problems, lodge warranty claims or negotiate purchase and support contracts.

Information that used to be hidden in the bowels of the industrial site and limited to break-fix applications can be strategic when it is:

  1. consistently collected
  2. aggregated at massive scale
  3. used to understand ebbs and flows of heretofore inscrutable plant level spending.

Capturing data automatically and using it analytically has implications for managing large industrial enterprises that are just now coming to light.

The big wins in online (maintenance) strategies for industry will go to the early adopters. The first movers will be defined by seeing the potential in data and connectivity for step changes in operating and financial performance.

The analogs are already out there: Google, Apple, Amazon. Who remembers the fate of the Encyclopedia Britannica, IBM laptops or Borders Books?

The industrial world's first movers will lift market share from right beneath the noses of long-standing incumbents who ignore how data and connectivity have changed the consumer world, and will soon be changing industry.

And the advantages will be secured so quickly that it may be very hard for second-mover strategies to prevail.


Burt Hurlock is CEO and a member of the Azima DLI Board where he is responsible for the company's strategic growth initiatives and overseeing the its day-to-day operations. Burt has spent over 20 years as an entrepreneur and investor. He has founded, advised, built, operated, and/or sold almost a dozen venture-backed operating companies, and completed more than 40 acquisitions. Burt holds a Bachelor’s Degree from Princeton University and a MBA from Harvard Business School.

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