29 March, 2024

Predictive maintenance in hydraulic systems proves cheaper in the long run

20 August, 2019

The operation of hydraulic systems is clearly critical, regardless of whether they function for 10 minutes every few weeks, or 24/7. Achieving an uptime utopia, however, depends largely on the successful implementation of an optimised maintenance strategy. In the hydraulics arena, many different maintenance strategies can be found, including those based on breakdown, preventative, predictive and proactive approaches. Today, there is a growing trend in support of a predictive maintenance approach, the explanation for which is outlined in a new white paper written by independent industry expert Steve Skinner in association with Webtec.


The white paper, entitled ‘Predictive maintenance – cheaper in the long run’, in the first instance highlights that the objective of any maintenance programme is ensuring that the point of catastrophic failure is never reached, while at the same time providing a cost-effective solution. To achieve these goals, the maintenance approach must indicate that action is taken as close to the end of useful component life as possible – before the point of rapid deterioration or breakdown.

All of the commonly deployed maintenance strategies are assessed in the white paper for their strengths and weaknesses. Breakdown maintenance, for example, is extremely cost effective provided no parts fail during the machine’s lifetime, or where the consequences of component failure are trivial. In terms of disadvantages, however, this type of approach essentially ‘gambles’ that a part will last for the working life of the machine. Moreover, in many industries, unexpected component failure will likely prove expensive, as well as dangerous.

With regard to preventive maintenance, which involves estimating when machine parts are likely to wear out, then scheduling their replacement before this occurs, such a strategy is useful when component lifetimes can be predicted reasonably accurately and where operating life is relatively insensitive to operating conditions. Whenever useful lifetime is difficult to predict or significantly affected by operating conditions, then other maintenance procedures may be more appropriate.

Foreseeing all possible eventualities

Moving to proactive maintenance, this approach attempts to foresee all possible eventualities that could lead to a breakdown, then evaluate their likelihood of occurring and their effect on machine operation. Based on a combination of these parameters, potential failure causes or consequences can then either be eliminated or reduced to an acceptable level. On the flip side, proactive maintenance can add cost to a system which must be balanced against the likely cost of unexpected breakdowns. In addition, although a proactive maintenance procedure may extend the useful life of some components, it cannot on its own predict the imminent failure of a component, so unexpected breakdowns are still possible.

Last but far from least, predictive maintenance works by monitoring the performance of a system or its major components in order to determine when action is required. System components include hydraulic fluid, filters, pumps, hoses, motors, cylinders, accumulators and servo/proportional control valves.

Monitoring and measuring the Performance Level (PL) of these components in effect assesses how well they are performing compared with their ‘as-new’ condition. PL can be measured in terms of speed, energy efficiency, accuracy, noise level or any other parameter that is relevant to operation. In a mechanical system it is likely that the PL of a machine’s components will gradually decline over time due to common factors as wear, corrosion, ageing or fatigue. It is also likely that, at a certain point, the deterioration in performance will start to accelerate, ultimately resulting in complete, and sometimes catastrophic, failure.

Early warning of failure

By measuring PL, an early warning of failure can be obtained, which in turn can be used to avoid unnecessary machine shutdowns and ensure that components with a significant portion of their useful life remaining are not replaced needlessly. The upshot is that the long-term cost of using predictive maintenance works out considerably cheaper.

As a further benefit, monitoring component health can yield valuable information on wear patterns, which can be utilised as part of continuous improvement programmes. Experience in this methodology dictates that very often component lifetimes can be extended when their operating characteristics are monitored and understood.

In an industrial landscape where production downtime costs are rising and instrumentation costs are falling, predictive maintenance is becoming an increasingly effective method of ensuring machine uptime, making it an indispensable tool for the future of industry as a whole.

The full white paper can be downloaded at www.webtec.com/education

www.webtec.com




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