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This Maintenance Management article series introduces and discusses maintenance management strategies, systems and processes for optimizing plant and equipment maintenance, maximizing equipment uptime, and for minimizing operating costs.
This Maintenance Management series aims to provide reputed, useful content that improves an operation’s and organization’s maintenance effectiveness.
The Maintenance Management series of articles are provided with permission of Lifetime Reliability Solutions.
NOTE: The series does not cover related commercial or vendor software or database management applications.
Many companies adopt root cause failure analysis (RCFA) and then drop it. They use it for while and get no benefit. RCFA is often ineffective when used to solve individual problems. But when used to find systematic causes of problems and improve business systems, it provides grand payback for the effort.
Keywords: root cause failure analysis, business process improvement
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Much of what we do in engineering and maintenance we accept without question. People say, ―It‘s been done that way for decades,‖ implying that it must be correct. But for equally as many decades have come stories of failed and broken machinery, plant and businesses. On one hand we continue to unquestioningly do what has been done for generations, yet on the other hand we cannot stop equipment failing. There is a subtle connection between the two of which we are only just becoming aware. The connection is obvious when you realise that we have been running our businesses by risk and luck, and not on facts and understanding.
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When you do a Root Cause Failure Analysis or a 5- Why there are no promises that you will actually find the true root cause and fix your problem. Investigating the cause of a failure is fraught with traps, such as making wrong assumptions, insufficient evidence, misinterpreting the evidence, misunderstanding, personal bias and second-guessing. There are necessary issues you need to be aware of that affect the RCA and 5-Why methods, and there are some good practices that you can adopt to improve your chance of doing a successful analysis when applied to equipment failures.
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Maintenance and reliability problems are not new. Our forefathers and ancestors understood the value of smart maintenance and high reliability. They learnt from experience and passed their knowledge down to us through parables, stories, and sayings. The timeless advice of our forbearers on successful maintenance and reliability is as applicable to us now as it has been to every generation since the dawn of civilisation.
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What can a 25-year veteran of condition monitoring tell you about how to do better maintenance and get
better reliability?
First a little background. Max started his vibration analysis monitoring company back in the late 1970’s. He and his company developed expertise and technologies in condition monitoring over many years. They monitored and reported on a large range and number of machines, and worked for numerous companies. He and his people were the recognised experts in vibration monitoring and control. [Read more…]
A useful Maintenance Key Performance Indicator (KPI) drives reliability growth while guiding your choices for improving maintenance effectiveness and efficiency. A useful maintenance KPI lets you identify the issues causing your maintenance effects and helps you select the right strategy to either support or correct the actions producing the results. It is important that when you select a range of maintenance KPI you pick those that let you improve both equipment reliability and maintenance performance and not simply tell you that you have problems in your business.
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This paper is primarily on understanding how to get extraordinary equipment reliability. The paper explains where equipment failures start in organisations. It clarifies the need to recognise the effect, and to control the influence, of interacting processes across the life cycle. It explains the successful philosophies and practices used in high reliability organisations and it introduces a reliability-causing methodology to help companies find what to do to become high-reliability organisations.
Predictive Maintenance applies condition monitoring techniques to discover potential failures. While finding a problem before it becomes a failure is good, companies can end up with so much work that maintenance backlog skyrockets, maintenance costs blow-out and people burn-out. Understanding when a predictive maintenance strategy can cause uneconomic maintenance, or why condition monitoring can produce unending failures, is vital if you want reliable equipment with low maintenance cost.
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Plant and equipment do not fail by accident. There are causes. Whether equipment fails depends on the capacity of their parts to handle stresses, when stresses are applied and the size of those stresses. These are probabilistic events – they are random, with many possibilities. Timing the start of failure, or its continuation to a breakdown, is mostly speculation because it depends on which past and future scenarios occur. It seems that luck and chance has a large say on the lifetime reliability of equipment. But there is a way to guide equipment reliability and performance toward the results you want.
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The level of care given to an equipment item depends directly on the size of business risk if it fails. Reduce the chance of its failure and you increase its reliability. It becomes vital to know the full range of risks each part within an equipment item will suffer. The right asset management strategy starts by knowing which parts are at risk and it is completed when the necessary actions to prevent all failures are in use. Asset Management that does not identify all the risks to equipment parts when selecting equipment maintenance and operating strategies will get you doing the wrong work.
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The data gathered from operating condition inspections and performance monitoring trends will increasingly appear alongside process plant performance data and be used to assign maintenance priorities and maximise plant uptime and equipment reliability.
Measuring machinery health by performance monitoring has the potential to give warning of a developing failure through the changing levels of a suitable parameter being measured, thereby indicating a change in condition of a component, machine or system.Keywords: machinery performance monitoring, machine condition assessment, equipment health monitoring
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Change to Component Health Monitoring for Massive Equipment Reliability Improvement. Many condition monitoring (CM) techniques require that your machines and equipment reach a near failed state before they detect the symptoms of failure. This guarantees that you will have many machines in your operation always near-to-failure. Outstanding reliability instead requires you to create the conditions of long-lasting machinery health and to ensure those conditions are always present. As a consequence of having a machine health improvement focus you proactively cause equipment wellness in your operation and thereby create huge reliability growth.
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The advent of the microprocessor has enormously advanced the process of vibration data acquisition and analysis in recent years. Measurement tasks that took hours only two decades ago can now be completed in minutes and better decisions made because of better data presentation.
However, the basic processes of measurement and analysis have remained essentially unchanged, just like the machines from which the vibration is measured. The results of the measurement and data analysis need to be compared with known standards or guidelines and decisions made as to whether the machine is acceptable for service or maintenance should be planned. Increasingly these processes are being handled electronically but we are still a long way from replacing the fundamental knowledge and experience of the vibration analyst.
In this article we will review the basic principles of vibration measurement and analysis in order to lay the foundation for capable fault diagnosis to be considered later.
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When it comes to Risk we have simplified it so much that we have failed Einstein’s advice, “Everything should be made as simple as possible, but not simpler.” It has been made too simple and missed the connection between risk and reliability.
Equipment risk has a direct impact on equipment reliability. What risks you allow your production plant and equipment to suffer will negatively impact its reliability. About 6 months ago I was playing about with the risk equation and a mathematical connection between risk and reliability revealed itself.
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Reliability Centred Maintenance (RCM) was developed by the aircraft industry and it has now migrated into industries across the world. The aircraft industry does RCM differently to other industries. RCM fails in general industry because inherent problems in the business design of most organisations are prevented in the airline industry with business processes imposed by legal regulation. Using the RCM methodology does not instil the business disciplines needed for RCM to deliver its benefits.
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