Sensors to implement new maintenance strategies

Sensors to implement new maintenance strategies

Monitoring vibration on a constant basis can provide significant benefits in cost efficiency, productivity, and product quality

By MAX LIBERMANAnalog DevicesWilmington, MAhttp://www.analog.com

As manufacturers become increasingly aware of the skyrocketing cost of delayed maintenance, they wish to rapidly adopt new predictive maintenance programs. Monitoring technologies such as vibration analysis offer a promising answer to stemming rising costs due to damaged motors, pumps, gear boxes, fans, compressors and other equipment.

But those monitoring technologies are only viable if they can be implemented effectively and affordably. By leveraging a proven MEMS process, a new breed of sensors offers the combination of performance, size, cost and reliability needed to make real-time continuous equipment monitoring widely available.

Shop floor strategies

On the manufacturing floor, the ability to identify potential maintenance problems clearly pays multiple dividends. Bad bearings, worn gears, loose fittings, and misaligned equipment can have profound impacts on plant downtime, productivity, and employee safety.

Yet manufacturers have struggled to develop simple, effective, and affordable maintenance strategies. Historically, they have employed a combination of reactive and preventative strategies to maintain equipment.

Reactive strategies, best characterized by the saying, “if it isn’t broke, don’t fix it,” imply waiting for a failure to occur before acting. This approach is highly costly. Preventive strategies such as periodically tuning machinery, greasing bearings, changing belts and rebuilding machinery are more effective. They do help, but they are relatively inefficient because they do not rely on collected data to determine if such strategies are warranted.

The key to limiting the cost of equipment maintenance is to identify potential issues early. For example, the cost to repair a bearing after it fails and damages other parts of a system can be 10 times more costly than simply replacing the bearing itself. And a catastrophic equipment failure can cost a manufacturer hundreds of thousands of dollars in lost productivity.

To achieve that cost-limiting goal, many of today’s plant managers are opting instead for a predictive maintenance approach. With this strategy, data on machinery performance and operating characteristics is collected and analyzed on an on-going basis. By measuring parameters such as vibration, temperature, and leaks, engineers can more accurately predict when maintenance is needed, thus averting hard equipment failures. It is the most cost-effective way to apply limited resources.

A predictive maintenance plan not only helps manufacturers avoid costly unexpected equipment breakdowns, but also improves efficiency by keeping machinery optimally tuned. Its predictability also gives manufacturers the freedom to conveniently schedule downtime and accurately budget money for equipment maintenance. Lindsay Engineering, a Camarillo, CA-based provider of predictive maintenance products and services, finds such programs can cut maintenance costs as much as 25%.

Vibration analysis

Manufacturers use a variety of technologies to monitor the condition of equipment. Popular options include infrared thermography, ultrasound, and motor current. Far and away the most efficient technique, however, is vibration analysis. By some estimates the ROI for vibration analysis outpaces other technologies by a factor of at least 3:1 (see Fig. 1 ).

Fig. 1. Of the various technologies that can be employed in predictive-maintenance programs, vibration analysis provides the greatest ROI. (Source: Lindsay Engineering)

By tracking slight variations in vibration, manufacturers can get an early indication of potentially serious problems in rotating machinery. Such problems could include worn or damaged bearings or gears, misaligned equipment, lubrication issues or a loose fitting.

The data can then be used to identify and resolve the potential maintenance problem before it causes catastrophic damage and results in costly machinery downtime. For example, if you are running a machine with two bearings, and each has a mean-time-to-first-failure (MTTF) rate of 8,760 hours, the odds of a problem occurring within the next month is 8%. However, the odds of a problem occurring within the next year would be 86%.

By identifying these issues early, manufacturers not only reduce downtime and increase machine productivity, they also eliminate potential secondary damage such as worn out shafts and burned out motors which add to severity of the damage and are very expensive to fix or replace. At the same time, they can reduce their spare parts inventory, extend the length of equipment lifecycles, and improve plant safety.

Implementation choices

Manufacturers who decide to pursue a vibration analysis maintenance scheme have two options. One strategy is to hire a consulting firm to perform the task. This option gives the manufacturer access to high levels of expertise and high-performance monitoring equipment.

However, the manufacturer typically pays a high price for that expertise hundreds and sometimes thousands of dollars. Moreover, since monitoring is only performed periodically, it is often difficult for the manufacturer to know how often to use the consultant and how much to spend to ensure a successful predictive maintenance program.

The second option is to mount monitoring sensors directly onto or into the equipment on the factory floor. This approach offers continuous, always-on monitoring and a comprehensive view of the condition of the machinery. It also gives the manufacturer better control of maintenance costs and schedule.

Vibration sensor selection

Engineers should be aware that the current generation of sensors can suffer from a variety of limitations. First and foremost, vibration sensors on the market today may offer limited performance. That is, many vibration sensors only operate below 5 kHz, and most maintenance problems begin at a higher-frequency pitch.

Critical vibration generally begins to occur in the 8-kHz range. As the device, whether it be a faulty bearing or gear, begins to degrade, the equipment begins to shake and the pitch of the vibration moves into the lower range. Often, by the time the pitch of the vibration drops under 5 kHz, substantial damage has occurred. For earlier indication of potential problems, manufacturers need sensors able to monitor higher frequency vibrations (see Fig. 2 ).

Fig. 2. Vibration indicating bearing wear can occur at frequencies above the detection capabilities of many sensors.

Many piezoelectric vibration sensors typically require a high voltage and are packaged in bulky metal cans not designed for high-volume manufacturing. As a result they come at relatively high cost. In addition, these devices typically require frequent calibration to ensure consistent performance.

Recently, designers have been investigating a new approach to vibration analysis using a micro-electro-mechanical-system-based approach. Engineers have developed a precision single-chip MEMS device able to withstand the rigors of the industrial environment.

For example, the ADXL001 vibration sensor improves early detection of equipment failures by measuring motor-bearing vibration and irregularities up to 22 kHz. The device uses unique differential accelerators in the form of two side-by-side MEMS mechanisms to cancel out common-mode noise.

Compact devices such as this (it is available in a 5 x 5-mm package) allow manufacturers to easily design a sensor into a motor control circuit or mount it onto existing equipment. And having equipment with this capability lets users cost-effectively monitor vibration and shock continuously without interrupting normal equipment operation. Using an hermetic packaged like that used in the automotive industry makes the sensor highly reliable in extreme environments.

This MEMS technology requires no calibration, so it simplifies vibration monitoring. And armed with precision data converters, DSP processors, and sophisticated software, engineers can use such sensors to rapidly create more complex solutions. By driving the output of the sensor through the DSP, for example, a designer can perform various processing techniques such as filtering and amplification. ■

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