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What is Predictive Maintenance (PdM)?
Predictive maintenance also known as PdM, is a technique that uses condition-monitoring techniques to predict and prevent sudden machine failures & to monitor the performance of equipment during operation. Predictive maintenance, is a maintenance strategy that involves continuously monitoring conditions (such as vibration and temperature) that indicate machine health.
Why is predictive maintenance important?
Predictive Maintenance allows for safety compliance, pre-emptive corrective actions, and increased asset life. It will help in machine learning & give more visibility into potential problems, predictive maintenance can help increase equipment uptime, reduce maintenance costs, and improve asset performance and longevity. The objective is to detect changes in baseline operating conditions, which can indicate a problem before the issue escalates to failure and costly downtime. By looking ahead, and knowing what failure is likely to occur when, pre-emptive investigations, maintenance schedule adjustments, and repairs can be performed before the asset fails
What are the advantage and disadvantage of predictive maintenance?
Predictive maintenance presents you with the best time to work on an asset so that maintenance frequency is minimal and reliability is as high as possible while eliminating unnecessary costs.
✓ Avoids major breakdowns and reduces downtime.
✓ Enables better asset management across its lifespan.
✓ Decreases costs, particularly with emergency maintenance.
✓ Provides the basis to develop predictive algorithms in the future.
However, there are few disadvantages to predictive maintenance like high start-up costs and the need for specialized personnel
How does it help ?
You don’t need to overhaul your entire plant for building a successful predictive maintenance strategy. In fact, IIoT technologies are both accessible and scalable. You can build a condition monitoring program to fit your exact needs and grow it in the future. The result is significant cost and time savings. Your maintenance teams will no longer need to perform unnecessary preventive maintenance tasks or replace parts that are still viable. You’ll also be able to avoid unnecessary downtime, both planned downtime associated with traditional preventative maintenance and unplanned downtime that results from a reactive maintenance strategy.
Types of Condition Monitoring for Predictive Maintenance
There are several techniques of predictive maintenance, all of which involve continuously learning & monitoring machine conditions in real time to identify problems quickly which are as follows:
- Vibration Monitoring
- Acoustic Monitoring
- Temperature Monitoring
- Power Monitoring
Vibration monitoring method looks for changes in vibration levels that can indicate deterioration of a machine’s rotating parts. For instance, a common cause of increased vibration is loose, misaligned, or worn components — such as motor bearings — that can lead to further damage to the machine if not addressed on time.
Wireless vibration sensors affixed to machinery measure changes in the amplitude, frequency, and intensity of vibration. The sensors can detect minute changes at frequencies that humans would not be able to detect on their own. Accelerometers, transducers commonly used in vibration analysis, measure changes in velocity resulting from changes in the equipment’s baseline vibration signature. They can also help maintenance teams pinpoint which component is causing the change in vibration, making it simpler to resolve the issue before it becomes a bigger problem.
Acoustic monitoring method is another technique of condition monitoring that uses changes in an asset’s audio output to identify potential problems. Similar to vibration monitoring, the acoustic monitoring technique begins by establishing a baseline for the sounds produced when a particular piece of equipment is in normal operation, as well as the sounds it emits during startup, rundown, and standby modes. The sensors are installed near the machinery which continuously monitor for subtle changes to the equipment’s baseline noises, or sound fingerprint.
Acoustic monitoring also works on noise cancellation technology so that the sounds made by a machine or component can be separated from the ambient sound of the worksite. The sensors used in acoustic monitoring are able to hear noises that humans cannot. Because of their sensitivity, they can pick up on subtle signs of deterioration in plenty of time for maintenance teams to address & prevent them.
Temperature monitoring technique uses temperature sensors to identify anomalous temperature increases on equipment, which can indicate potential issues. For example, abnormal increases in temperature can point to defective wiring, bad circuit terminations, or fuses that are approaching capacity.
Power monitoring method can identify power fluctuations in electrical machinery that can lead to massive, premature wear or failure. Power monitoring uses sensors to capture data on a wide variety of metrics including current (A), voltage (V), power (W), frequency (Hz), apparent power (VA), reactive power (var), power factor (PP), and total harmonic distortion / THD (%). If thresholds are exceeded, a power monitoring system can automatically issue an alarm to maintenance staff to immediately address the issue before asset damage occurs.
Being in the right place at the right time
There are many companies that manufacture/ supply instruments and provide services that assist in monitoring the condition of the machine to avoid untimely breakdown.
Aimil Ltd. is one of the Leading Instrumentation Company with ISO 9001:2015 Certification and Pan India presence who is also involved in a different area of engineering consultancy and have Joint venture with Pruftechnik, Germany who is a globally recognized company providing Condition Monitoring and Alignment Product & Services in the Indian market. Our experts can help your team with your requirements.
For more information contact us