Make precision lubrication a foundational pillar for asset reliability.
It’s been estimated that more than 50% of failures to rotating equipment can be tied to lubrication, making precision lubrication a foundational pillar for asset reliability. What exactly is a lubrication failure? To some it may simply mean that no lubricant is present while, to others, it could mean that the wrong lubricant was used. Lubrication-related failures span a range of possible issues and outcomes, meaning our approach to failure prevention also needs to be expansive.
To address any failure mode, we first need to look at the failure, determine its potential impact on the organization, and develop an effective maintenance strategy. Oftentimes, Failure Mode Effect Analysis (FMEA) is used. FMEA is a key component of an overall Reliability Centered Maintenance (RCM) strategy. The outcome of a lubrication-specific FMEA is the deployment of a series of preventive, predictive, and proactive actions and activities, designed to either prevent or detect incipient lubrication failure.
Preventive activities are tasks that are performed according to a set schedule—either time, distance, or production cycles. Preventive tasks work well where there is well-defined time, distance, or cycle count correlation to the failure mode. Simple examples might be changing engine oil every 8,000 hours or greasing motor bearings every 6 months.
While preventive maintenance may be the first line of defense, many failures are not time dependent. As such, a better approach to failure prevention is to use a predictive-maintenance strategy in which measurements and data drive our decisions and actions. Examples might be vibration analysis or wear-debris detection using oil analysis. Predictive maintenance, often used as part of a broader condition-based maintenance (CBM) strategy, allows corrective action to be taken before catastrophic failure occurs.
While it is vital to detecting incipient lubrication failures, predictive maintenance, by itself, does not eliminate failures, nor does it extend component life. Imagine installing vibration sensors on a critical asset and taking continuous vibration readings. While the sensors may pick up early signs of incipient failure such as imbalance or misalignment, only by taking the appropriate corrective action will a failure be avoided.
Perhaps more importantly, predictive maintenance does not extend the life expectancy of an asset. Oil analysis, as an example, can measure the rate at which a machine is wearing, but the only way to change the wear rate and hence the time-to-failure is to address the underlying root cause driving a particular rate of wear. This type of maintenance strategy is referred to as proactive maintenance where data not only drives the early identification of failure, but points to a need to make a meaningful change in how the asset is maintained. For example, using a different lubricant or adding supplemental filtration to improve overall fluid cleanliness.
The best maintenance programs incorporate all three strategies—preventive, predictive, and proactive—in a holistic process to deliver optimum asset reliability.
Address these 10 common failures by developing a robust strategy to address each failure mode through appropriate preventive, predictive, and proactive maintenance.
Table 1 shows the 10 most-common lubrication failures, from lack of lubrication to lubricant contamination. While some are more common than others in specific industries, developing a robust strategy to address each failure mode through appropriate preventive, predictive, and proactive maintenance is key.
While applying the strategies listed in Table 1 will undoubtedly drive increased reliability, the reality is that the cost to apply predictive, particularly proactive, strategies to every asset is often cost prohibitive for most organizations. As such, we need to look at not just failures but overall risk.
In reliability terms, risk can be defined as the product of probability of failures, multiplied by the consequence. Consequence could include factors such as possible production losses, safety issues, or environmental non-compliance. Whenever an asset is deemed to be at high risk, either because it has a high failure rate or a high consequence of failure, every effort should be made to understand key failure modes and what combination of predictive and proactive strategies offers the best chance of mitigating failure.
Preferred practice is the balance between reduced failure costs and increased maintenance spend.
Key to success is recognizing “preferred practices” (Figure 1). Unlike best practices, which often represent an all but unobtainable level of precision that few organizations can afford to deploy, “preferred practice” is the minimum investment required to achieve a certain reliability objective, without incurring excessive spending over and above the benefits that might be realized through improved lubrication.
By applying a risk-based approach, including the deployment of predictive and proactive measures to deliver “preferred” lubrication practices, companies can achieve effective maintenance cost reduction, while eliminating lubrication-related failure. EP
By Mark Barnes, PhD CMRP, Des-Case Corp.
Mark Barnes, CMRP, is Senior Vice President at Des-Case Corp., Goodlettsville, TN (descase.com). He has 21 years of experience in lubrication management, oil analysis, and contamination control.
EP Editorial Staff | June 1, 2023
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