Availability: The First Element of Overall Equipment Effectiveness (Part 2)

Availability: The First Element of Overall Equipment Effectiveness (Part 2)

Lagging Metrics for Asset Management

The previous article in this series introduced the Availability metric and discussed how to account for planned unavailability. Availability, Yield/Speed, and Quality are the three elements of the Overall Equipment Effectiveness (OEE) metric. Organizations experience some combination of equipment-induced, operations-induced, and marketing-induced losses that will adversely affect Availability, Yield/Speed, and/or Quality of production.

Written by: Drew Troyer, CRE, CMRP


As noted, Availability is the number of hours a plant or system is running divided by 8,760. Unavailability may be planned and intentional or unplanned and unintentional. Here, we’re focusing on the unplanned type and categorizing it for accurate analysis, which, in turn, can help reduce or eliminate this particular unavailability.

When one thinks of unplanned events that adversely affect availability, equipment failures immediately come to mind. At a causal level, equipment fails because it is poorly designed, inappropriately operated, or inappropriately maintained. However, there also are some non-equipment-related reasons for unplanned unavailability of production assets. These losses are operations-induced and/or marketing induced and can affect availability, yield and/or quality of production. First, let’s examine the equipment-induced causes.

EQUIPMENT-INDUCED UNPLANNED AVAILABILITY

Unplanned equipment-induced availability losses occur when machines aren’t fit for service. To reduce these losses, the cause for the downtime-producing failures must be identified. These causal factors are summarized in Fig. 1. This article will be addressing the green boxes.

 

♦   Incorrect Equipment Design. Design represents the “DNA,” i.e., the genetic code for reliability, of machines. Of course, reliability drives availability. Maintenance is intended to restore the reliability of equipment; it can’t alter a machine’s inherent reliability. In addition to designing for reliability, machines must be designed for maintainability, operability, flexibility, adaptability, inspectability, sustainability, and all the other “abilities” required to meet the organization’s production, safety, and environmental objectives.

♦   Excessive or Insufficient Preventive Maintenance. The purpose of preventive maintenance, as the name suggests, is to prevent failures. Common preventive-maintenance (PM) activities include lubrication, adjustments, and time-based rebuilds. When optimized and executed correctly, these types of PMs extend equipment life and assure production availability. Done incorrectly, the actions are regressive and compromise availability. For example, when greasing an electric motor, the intent is to assure that the bearings have a sufficient supply of fresh, healthy grease to help them run reliably. However, if over-greased, the excess grease passes through the motor’s inner seal, contaminates the windings, and inhibits cooling of the motor. Heat, in turn, accelerates the rate at which the stator-winding insulation degrades. Therefore, it’s important to optimize our PM planning: We want to do enough preventive maintenance to ensure equipment reliability, but we don’t want to do so much that it becomes counterproductive.

♦   Poorly Executed Preventive Maintenance. It’s not enough to make sure we apply the correct amount of preventive maintenance. The task must be executed correctly. This is where precision maintenance comes into play. Measurement-driven, precision maintenance emphasizes fit, tolerance, quantity, and quality details. For the motor-greasing example, would it be adequate to just get the regrease interval right? No, we also must be sure to apply the correct type of lubricant, with the correct performance properties; the right volume must be applied to the drive-end and non-drive-end bearings; and the lubricant must be in good condition and free of contaminants.

 “Hard-time” rebuilds represent another example of a PM activity that might be regressive and produce unplanned availability, if executed poorly. A hard-time rebuild is one that occurs based upon time, distance, or cycles. For example, if we have a policy to rebuild a machine based on it reaching a time/distance/cycles threshold, we may actually take a perfectly good operating asset out of service, disassemble it, then introduce failure modes in the process of putting back together.

To use a human-body analogy, consider that the risk of heart attack for Western males increases with age, particularly over the age of 50. How would you feel if, on your 50th birthday, your physician called and suggested that you make an appointment for a heart transplant? I would be very concerned. Among other things, I don’t know that my existing heart is defective. I can’t be sure that proposed transplanted heart transplant would be free of defects. And I am certain that anesthesia and the opening and closing of a body’s thoracic region carry risks.

♦   Wrong or Insufficient Inspections and Monitoring. To avoid the risks associated with hard-time maintenance, most organization employ inspections, condition monitoring, and non-destructive testing (NDT) to drive condition/inspection-directed maintenance. Doing so eliminates the guesswork from maintenance. When an abnormal condition is observed through inspections or monitoring, a notification is written and approved or denied. If approved, a priority is assigned, and the job is planned, scheduled, and executed to correct the problem or restore healthy conditions that, if not addressed, would increase the risk of failure. It’s imperative that we match the inspection and monitoring plan for an asset to its probable failure modes. It’s also crucial to inspect or monitor the assets health at the correct interval. If the interval is too long, a failure can transition from the incipient stage to the catastrophic stage between observations.

Referring again to our human body analogy, scheduling a heart transplant simply because one turns 50 years of age doesn’t make a lot of sense. But scheduling an electrocardiogram and a few other tests at the age of 50 does make sense. If heart disease is found, an appropriate course of treatment starts. It might be a pharmacological solution, angioplasty, by-pass surgery, valve replacement, or, possibly, a heart transplant. However, the decision would be based upon tests and data.

Better yet, turn the clock back to when you were 25. The risk of a heart attack is quite low for a healthy 25-yr-old. At that age, we could expect our physicians to check blood pressure, cholesterol, etc. A high cholesterol level doesn’t indicate a heart attack, nor does it guarantee that one would ever occur. But, given the fact that elevated cholesterol is a known root cause of heart disease, by taking actions to reduce it, one targets a primary root cause and helps reduce the likelihood of heart disease later in life.

CONCLUSION

To recap: Availability is an essential lagging metric for asset management. And it’s a primary driver of OEE. Unavailability can be planned or unplanned. The unplanned type of unavailability can be equipment-induced, production-induced, and/or marketing-induced. There are many causes for equipment-induced downtime.

See Related Articles below to access additional articles in the OEE series.

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Related Articles:

(Pt 1) Availability: The First Element of Overall Equipment Effectiveness

  January 2022 , Lagging Metrics for Asset Management: OEE / Drew Troyer, CRE , Principal

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Drew Troyer, CRE, Principal

Drew D. Troyer hat sich T.A. Cook 2018 als Principle angeschlossen. Er bringt fast 30 Jahre Erfahrung und Fachwissen im Reliability Engineering und Asset Management mit. Der Certified Reliability Engineer (CRE) und Certified Maintenance & Reliability Professional (CMRP) kann außerdem einen MBA vorweisen. Mit diesen Qualifikationen verfügt er über das Know-how und die notwendigen Fähigkeiten, um in den Anlagen seiner Kunden versteckte Potenziale zu ermitteln.

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