How Predictive Maintenance Programs Fail When Teams Misuse Technology

A good mechanic knows that you need the right tool for the job, but a common problem with predictive maintenance (PdM) programs is that sometimes teams acquire a tool before fully understanding what problem needs to be fixed. When you have a hammer, all your problems look like nails, and what follows from this mistaken view is a whole list of reasons why PdM programs fail. Only when you really understand the problem does the solution become obvious.

One major reason PdM programs fail is because the goals of the program are not well defined or well understood. A company purchases a tool like a vibration analysis system or infrared camera and trains staff to use it, but they receive no guidance on what to use it for. What organizations often fail to do is change processes and procedures in the plant to take advantage of the information this new tool provides. In other words, you buy a screwdriver, you learn how to loosen and tighten screws but you somehow fail to see how this does or doesn’t relate to the plant’s overall operation. 

So, what are the goals of a successful program? Depending on your background, experience or role in your organization, you may have differing ideas about this. But how you view success will have a large impact on how you employ technology and what sorts of benefits you’ll receive. It will also ultimately dictate your opinion on which tool is best for the job. 

The failure of many PdM programs can be traced back directly to confusion or disagreement on this core question: what is the goal of the program? Why are we purchasing this tool (or service), how will we use it and how will we measure our success? In many cases, companies purchase tools before answering these questions — if they ever answer them. In other cases, the benefits teams hope to reap are not in line with how they actually employ the technology.

The Importance of Setting Goals

Let’s consider two common viewpoints regarding the goals of a vibration analysis program. One typical view is that vibration analysis is one of the best non-destructive technologies available to detect and diagnose mechanical faults and degradation in rotating machinery. The goal of using the technology is to detect and diagnose faults in rotating machinery, and that’s it.

Another common view is that because vibration analysis can be used to detect wear in rotating machines, teams can utilize this machinery condition information to better plan maintenance actions. This leads to an increase in uptime, quality, and plant performance and a decrease in unplanned maintenance, catastrophic failures, and accidents. These benefits, loosely defined as overall equipment effectiveness (OEE), lead to higher profitability. In this view, the lofty goal of the vibration analysis program is higher plant profitability. 

This is the crux of many failed programs. 

Perhaps a manager agrees to purchase a vibration monitoring system or a monitoring service. They instantly imagine a 30:1 return on investment (ROI). Maybe they didn’t completely think the decision through, but higher profitability seems like a good goal to have. The manager has read plenty of articles about condition monitoring and profitability and is sold on the idea. 

Now that a product is purchased, some technicians and engineers are given some training, but they understand the goal differently. They use the equipment to detect problems in their rotating machinery; perhaps they even become quite skilled at it. But beyond this, no organizational changes have been implemented to schedule maintenance based on vibration test results. Nor have metrics been introduced to calculate and measure the impact of the technology on uptime and spare parts and, ultimately, its impact on the bottom line. 

From the point of view of the engineers and technicians using the system, it appears successful. They are able to troubleshoot machines and diagnose problems but imagine what happens when a recession hits and upper management goes around looking for programs to cut. How will these technicians make the case that their vibration program should be preserved? Where is the 30:1 ROI? 

This is one major cause of terminated PdM programs. The original idea was to impact the bottom line, but the technology was actually used in a more limited fashion. The maintenance team did not implement necessary organizational and procedural changes required to utilize machine condition information to meet the goal of higher profitability. 

Another issue is the tool itself; the actual equipment or service that a team purchases. The equipment you purchase, and how you use the equipment, will vary based on your goals. Remember, most people purchase the equipment first and never fully reconcile the goal. 

Goal #1: Troubleshooting and Diagnosis

Here is a common scenario that describes a plant using vibration analysis to troubleshoot machines and determine what is wrong with them. That goal — troubleshooting and diagnosis — defines what kind of equipment the team needs, what they don’t need, and who should do the job. 

The plant either has a vibration expert on-site or uses an outside consultant. Typically, someone hears a weird noise coming from a machine or they feel that the machine is vibrating too much. Maybe the machine keeps failing unexpectedly or seems to have more problems than a similar unit. Whatever it is, someone in the maintenance department believes there is a problem, and so they call a professional to troubleshoot it. 

The on-site expert or consultant will require customizable high-tech equipment that allows them to set up a variety of special tests to troubleshoot the machine. The data collection equipment may have a big screen because the analyst will do a lot of analysis on the plant floor. The equipment may also have many channels and it will likely be complex and difficult to use. Because there is no historical data, the focus will not be on trending or looking for changes over time. Therefore, the expert’s equipment will not require any advanced alarming or trending capabilities. It would not be uncommon to expect them to spend multiple hours or even multiple days diagnosing the problem and submitting a report. This would most likely be a costly but, hopefully, infrequent expense.

Summary: Scenario #1 

Data collector needs:
• Big screen
• Many test types
• Customizable, multi-channel, magnet-mounted sensors
• Intelligence in the analyzer 

Does not need:
• Alarming
• Trending
• Reporting
• Intelligent software 

Analyst:
• Highly trained
• Highly paid
• Experienced

Program manager:
• Not much program management required

Now let’s consider that the goal of the PdM program is to use the technology to better plan maintenance, ultimately leading to a measurable impact on plant profitability. What type of equipment will be best suited to meet this goal?

Goal #2: Tracking Data Trends for Decision-Making

In this next scenario, there’s an emphasis on tracking machine data trends because the goal is to look for changes in machine condition and then base maintenance decisions on this information. The maintenance team spends time upfront defining standard test conditions and organizing the program. 

This scenario calls for a low-cost, efficient worker to collect data in exactly the same way, day in and day out, year after year on the same equipment. The data collection equipment would be “idiot proof” with limited or controlled options for the user. Test points on the machine would be screw type sensor pads or installed targets for magnet mounts to ensure repeatability. Initiation of a standard test should take no more than a button press. 

Because the data collection tasks are defined to ensure repeatable, relevant, and historical data collection, there is no reason for the person collecting the data to look at or analyze this information on the plant floor. This eliminates the need for the data collector to have a big screen.

The software will have to be great at looking at trend data in an efficient way because this scenario also calls for testing most of the plant’s machines frequently, not only machines with known problems. Therefore, the analysis software will require more sophistication than the data collector. There won’t be time (or need) for an analyst to spend multiple hours looking at data from each machine; a couple of minutes will be enough to see if and how the condition has changed and to update the status and add recommendations in the software. Additionally, because trends based on good data should provide enough information to meet the goals of this scenario, the data collector will not require the capability to perform advanced customized tests, nor will the technician collecting the data require much training.

Lastly, since this scenario’s main goal is to improve maintenance decisions and relate them to the bottom line, the software should be part of a larger computerized maintenance management system (CMMS) package like eMaint or a plant asset management program. Linking results to business goals such as improvements in uptime, quality, and plant performance allow maintenance managers to accurately quantify their impact on profitability.

Summary: Scenario #2

Data collector:
• Easy to use
• Human error proof
• Simple, standard tests or online system

Data collector doesn’t need:
• Big screen
• Complex customized tests

Sensor:
• Triaxial sensor and stud mount

Software:
• Intelligent software
• Good alarming
• Trending and reporting features
• Links to CMMS and asset management software
• Metrics calculated from maintenance decisions up to plant profitability

User:
• Data collection technician
• Low skill
• Low wage

Program manager:
• High skill
• High wage

Strengthening PdM With the Right Goals

As you can see, the way you define program goals has a big impact on the type of equipment you should purchase and how it’s used. People often buy the equipment with the most bells and whistles first, paying little to no attention to the software they’ll use and no idea how the monitoring program will be organized. This is to say they buy the equipment defined in the first scenario detailed above with a vague idea that they will receive the rewards of using it as described in the second scenario.

Now let’s return to the original question: Why do PdM programs fail? The most common stumbling blocks are in understanding what the business goals are, and employing the right tools, people, and processes to meet those goals. It’s also important to establish metrics to show how effective the program is in reaching each goal. 

Oftentimes plants employ highly trained individuals to use complex equipment solely to troubleshoot machines that are already known to be problematic. This may be a valid use of the technology, but it is not PdM and does not bring the same rewards or ROI. If you begin with the stated goal of increasing profitability and work down the ladder from there, equipment purchases and the way these tools are employed will be very different. Overall, the profitability goal will be better realized. 

Predictive maintenance works best with the right tools—explore Azima’s solutions.

Author bio: Alan Friedman is a senior technical advisor for Azima DLI. With more than 18 years of engineering experience, Friedman has worked with hundreds of industrial facilities worldwide and developed proven best practices for sustainable condition monitoring and predictive maintenance programs. He has produced and taught global CAT II and CAT III equivalent vibration analysis courses.