Machine Reliability Moves to the C-Suite

Sept. 8, 2010
Programs sometimes fail over confusion about how to use the technology.

Condition monitoring and predictive maintenance are accepted practice in many industries today, but many companies still fail to realize the 20:1 or 30:1 ROIs they should realize from predictive maintenance programs and proactive maintenance strategies.

We have observed that programs sometimes fail over confusion about how to use the technology. For instance, using technology to troubleshoot a known problem, which is reactive, differs markedly from using technology to monitor equipment over time, which is proactive.

This article explores a philosophical shift that is gaining traction among leading manufacturers across American industry, namely, the realignment of accountability for reliability (and condition monitoring) from maintenance to operations, and from operators to condition monitoring domain experts.

Operators work around their equipment on a daily basis whereas maintenance deploys sporadically to a wider range of locations to make discrete repairs. In a truly predictive maintenance environment monitoring technologies should be used to detect equipment entering a failure mode so it can be repaired at the most opportune time and by the least costly method to avoid a costly failure.

We have found that monitoring technologies aren't always used that way. In fact monitoring technologies may be applied more frequently after there's a known problem to analyze and diagnose. In this capacity the technology is reduced to a troubleshooting tool rather than for monitoring, which means the user denies themselves the benefit of understanding plant-wide reliability and machine health. While this mode of use is entirely consistent with the role of plant maintenance, it also explains why many predictive maintenance programs never realize their advertized promise -- without systematic monitoring opportunities to catch small problems that can be address at minimal cost and before they become big problems are missed.

If we accept that a systematic approach yields better outcomes than episodic interventions, then it's fair to ask who is best positioned to administer the monitoring programs at the heart of all successful predictive maintenance programs.

Let's consider car maintenance, a subject about which we all have more and less well informed opinions. Who spends the most time in the driver's seat? Who is most familiar with the car's grunts, sputters and groans? Most of us check our tires for obvious signs of wear, monitor the dash board for warning lights, and check the oil and clean the windshield when we stop for gas. Most importantly, we know how the car should sound and feel. We're the first to notice a new rattle or a wobble, a pulling wheel, difficulty starting on cold mornings, or a loss of power going up hills. Consciously or unconsciously, experts or not, we constantly monitor our cars.

How do we react when we detect a change in how our cars are running? We note the change, try to identify related conditions (hills, cold mornings), attempt to determine if there's a trend and if the condition is getting worse. The moment we believe the car is at risk, off to the mechanic we go where we describe the symptoms, related conditions and trending. The mechanic combines this information with knowledge of other cars, administers some additional tests, and carries out the repair. Within minutes of driving the car away our intimate knowledge of the car under normal operating conditions establishes whether the repair was successful.

Traditionally, plant maintenance has been tasked with visiting the car every month or so to take readings and inform us of problems. Does that really make sense? Doesn't it make more sense for individuals with the greatest machine familiarity to supervise the monitoring?

Who is the Biggest Stakeholder?

At the risk of pushing our car analogy too far, let's ask who has the most at stake, the driver or the mechanic? Let's assume all mechanics have good intentions and do a good job. Does your mechanic go at risk for driving your car after it's repaired? Mine doesn't. Our dependence on the reliability of our cars creates a powerful incentive for being attuned to the characteristics of how it runs.

More than Just Monitoring Technology

Not only do operators have the right incentives to assume responsibility for monitoring the condition of equipment, they may be more effective at it. Although we have an arsenal of monitoring technologies at our disposal including vibration, IR thermography, and performance analysis among others, these technologies often complement and confirm suspicions first raised by our own senses. Sight, smell, sound and instinct frequently serve as the first line of defense. Add an operator's intimate knowledge of equipment and processes, and the technology simply translates uncertainty into defined risks and actionable information. In the condition monitoring world we far too often ask the mechanic to inspect and test the car when what we should be doing is relying on operators to assess risk, and using that assessment to deliver actionable information.

Should Operators be Condition Monitoring Experts?

Operators should assume condition monitoring responsibilities because they are 1) with the equipment on a daily basis, 2) more attuned to its normal operating characteristics and 3) most at risk in the event of machine failure. Does that mean they need to become vibration analysts or experts at interpreting IR images? Not necessarily. We should not confuse accountability with expertise, especially in highly evolved, complex organizations where the viability of the enterprise depends on coordinating specialized knowledge and experience.

Few of us who drive cars need to be trained mechanics to know the car has a problem, especially today with advanced onboard diagnostics including warning bells, alarms and lights that deliver high level information describing the nature of the problem. These systems may also be remotely monitored by diagnostic experts in the relevant technology with deeper knowledge of the alarming systems and machine condition than the driver and mechanic (operations and maintenance) combined.

With so much budget pressure to do more with less, and to eliminate or outsource all non-core functions, perhaps it's unfair to expect either operations or maintenance to shoulder the burden of staying current on evolving condition monitoring technologies and capabilities. Perhaps that expertise is better sought outside either group from vendors that concentrate and specialize in such services.


The growing trend towards automating and outsourcing condition monitoring is raising a strategic question that is making its way ever more frequently to the executive suite, and that is, who should see the "check engine" light -- maintenance, operations? Who should say "I think there is something going on, can you take another test?" Whose responsibility should it be to detect and report deviations from the norm, and how rapidly should that information be escalated in the organization? Should logistics know if a production run is at risk? Should a financial comptroller be aware that a batch of raw materials will be lost, or that a large piece of capital equipment will need replacing?

As manufacturers have squeezed supply chains to minimize working capital investment, they have begun to equate reliability with capital efficiency and time-to-market. There is growing appreciation for knowledge, accurate diagnoses, fast and effective interventions, and uninterrupted production processes. As reliable, lean production takes its rightful place among the strategic competitive advantages being cultivated by leading American manufacturers, reliability will fall to those most capable of managing it.

Burt Hurlock is CEO of Azima DLI (, which is a provider of predictive machine condition monitoring and analysis services.

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