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NIF's product is the physics data derived from the experiments performed at the facility. Our goal is to maximize NIF's availability to do experiments and consequently its data output by predicting and preventing equipment failures before they occur. We want to be in control of the equipment, not let the equipment be in control of us.

NIF focuses 192 of the world's highest energy lasers on peppercorn-sized targets to create unprecedented conditions of temperature and pressure for a wide variety of cutting-edge scientific experiments. We use reliability centered maintenance (RCM) and other industry best practices processes and tools to keep NIF running at an ever increasing pace. NIF completed 31 target experiments in February at a rate of more than 7.5 shots a week while also saving millions of dollars in avoided downtime and unnecessary maintenance. Since 2011, RCM and a companion program called condition-based maintenance (CBM) have saved more than $2 million. They are projected to save nearly $3.5 million by 2017. The programs use non-intrusive techniques, such as vibration analysis, oil analysis, ultrasonic lubrication and the elimination of ineffective preventive maintenance tasks.

The RCM program is a decision process to determine what needs to be done based on the function of the equipment. In other words, our decisions are function-based, not equipment-based. We look at the failure modes and effects of each asset and the criticality of the function it performs to determine the best maintenance path to follow.

We have determined that using a template process based on equipment type alone leads to wasted time and effort. For example, we now have a completely different preventive maintenance (PM) procedure for two identical pumps because one has a primary function and the other serves as a backup pump. While we maintain the primary pump with all essential PMs, we perform a different set of PMs to assure the backup pump is in a ready state.

A key asset condition management tool used by our facility operations and maintenance (FOM) group is vibration analysis. We use it to assess the health of critical pumps and motors to mitigate failures and plan for repairs with as much early notice as possible. Vibration analysis has allowed us to predict what's failing and how it's failing. We also keep historical records of this analysis and plan to potentially determine how much longer we have before a failure may occur.

We also use our vibration analyzer and precision laser alignment tool to perform alignment and balancing whenever we replace motors or fans. The vibration analyzer provides information about our critical rotating machinery, measuring the condition of bearings, co-alignment of motors and pumps, adequacy of equipment mounting and proper balancing, all of which affect the reliability of our rotating equipment.

When we install new equipment, we get a baseline of the vibration signature, make the necessary adjustments and take the baseline again until we're satisfied that we've installed the equipment properly. Then, we go out every quarter or so and take another vibration signature. Based on how the vibration spectrum is changing, we can tell whether a bearing is failing, if the motor has some imbalances and so forth.

Technicians performing alignment

Figure 1: Facility operations and maintenance technicians perform precision alignment on the NIF central plant motor and pump set.

The RCM program paid big dividends toward the end of last year when a routine monthly vibration analysis detected incipient failures on one of the motors in the laser amplifier cooling system. The motor was placed on a watch list and scheduled for weekly vibration analysis. Subsequent tests revealed a significant rise in low frequency vibrations, indicating further bearing deterioration and looseness. At that point, the FOM team received management approval to replace the motor before it failed.

Vibration analysis told us that the motor bearing was beginning to wear out and it wasn’t worth the risk to extend the operation of the motor any longer. If it failed at an inopportune moment, it could impact facility costs a lot more than the cost of replacing the motor.

Vibration analysis allowed sufficient time to have a well planned replacement strategy using NIF’s “Formula 1” operational approach based on the quick teamwork of Formula 1 race car pit crews. NIF’s FOM and transport and handling (T&H) teams used pre-coordinated plans to replace and commission the motor in an available four-hour window between shots, taking less than three hours to complete the task. Prior to Formula 1 evaluation, the process in a reactive mode could have required a full eight-hour shift.

Electrician installing an acceleratometer

Figure 2: FOM electrician installs an accelerometer on a NIF power amplifier circulating fan motor.

This proactive approach prevented at least eight hours of shot delays had the motor failed while we were preparing for a shot. The Formula 1 process avoided at least two hours of shot delays, for a onetime savings of about $80,000.

We think of ACM in the same way a doctor thinks about using lab results prior to treating a patient. Our CBM differs from time-based preventive maintenance by taking into account the condition of the equipment in determining the need for additional maintenance. We use oil analysis to monitor the health of our rotating equipment and as a way to confirm any diagnoses from our vibration analysis data. For example, if vibration analysis indicates that we are seeing some bearing deterioration, we should be able to confirm this with an increase in the metallic contents of the oil. With these types of confirmations, we can then make informed decisions on performing the appropriate maintenance.

Lubrication for motors is another example. We use precision ultrasonic lubrication for all our motor bearing lubrication. This technology alone has doubled the life of our laser amplifier cooling motors. Based on the manufacturer's recommendations, we used to pump in three to six pumps of grease per bearing every quarter. It turned out that was much more than was needed for this operation. Now, we use ultrasonic oil analysis to determine if lubrication is needed.

The ultrasonic device is attached to a Zerk fitting and allows the technician to listen to the bearing while applying the lubricant. By doing this, the technician can determine how much lubricant to add and when to stop adding it. In the past, we used to find the windings full of grease during post-failure analysis. Now, we are no longer filling our motor windings with grease and eliminating that issue has extended the life of our motors.

We also started using a paperless process, utilizing tablet computers to streamline our checklists and track our work orders. One hundred PM work orders are now being performed using the mobile platform and this number is increasing each week. Environmental stewardship is one of our goals and going mobile not only saves trees, but has saved time as well. Data from the field is seamlessly stored in our enterprise asset management (EAM) database and we get automatic alerts when inspections find parameters that are out of spec.

The FOM team performs about 6,000 PM work orders a year at an estimated average of four hours per work order. About 25 percent of all maintenance tasks have gone through a rigorous RCM analysis to evaluate cost-effectiveness and value, resulting in the elimination of hundreds of hours of ineffective preventive maintenance. In addition, the team has reduced the time spent doing reactive maintenance by 50 percent. RCM evaluations for the remaining maintenance tasks are in progress, but the reviews already are saving several hundred thousand dollars a year. Expansion of NIF's RCM and CBM efforts are planned for 2015 and the years to follow.

Nick Jize

Nick Jize, CRL, is the co-founder of JMS Software, a company that produces RCM software solutions. Nick has a background in RCM and predictive maintenance leadership with over 30 years of experience helping customers improve their reliability programs. He has a master’s degree in Engineering.

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