Machinery Lubrication magazine published by Noria Corporation
Issue link: https://www.e-digitaleditions.com/i/1275515
8 | July - August 2020 | www . machinerylubrication.com ese types of questions are often missed; not because the test taker didn't know the answer but because the test taker was quick to select a "right answer" before reading all other options that may have included an even better answer. It is not always easy to know what the right actions should be to improve the reli- ability of your lubricated equipment. Often times daily work tasks are decided based on a quick justification that an action will provide benefit. While this is good, is it the best, most beneficial action to take right now? Consider the Pareto Principle, often called the 80:20 rule. is principle suggests that about 80% of the effects are due to about 20% of the causes. For example, if we analyze all the possible causes of a machine failure, there is a select 20% of those that are the root cause for roughly 80% of the occurrences of failure. ose 20% are called the "critical few". If each reliability effort, including your time today, is focused on addressing the critical few, then in theory those actions are the most important things that one can work on today. But first, all the possible actions must be analyzed before knowing which one to select as the best action. Just like the multiple-choice question. But there is one problem… what exactly are these "answers"? What are those "critical few"? For lubricated equipment, this might simply mean focusing on a specific set of machines deemed as the most critical in the plant. Or when looking at root cause concerns, adjusting plant-wide reliability focus to target a certain type of contaminant that is known to cause the largest number of contamination related failures. Fortunately, many of these justifications are well documented for the general case. For example, the critical few reasons why bearings fail are improper lubrica- tion and contamination. More specifically, an article from Machinery Lubrication magazine in 2009 titled "Lubricant Failure = Bearing Failure" identified how improper lubrication failure is responsible for 40-50% of bearing failure. is includes lubrication failure modes such as: • Improper lubricant selection, such as incorrect viscosity selection or grease thickener type • Improper lubricant quantity, such as over- or under-greasing a bearing • Contamination, such as dirt ingression from bearing seals • Excessive temperatures, as a root cause, or part of a symptom from a different lubri- cant failure mode Reliability-centered maintenance uses at risk management as a reliability tool. e lubrication-related risk identified for machines helps justify a cost-effective strategy to avoid critical equipment from experiencing costly failure modes. Once the lubrication failure modes are identified, the following questions need to be assessed to ultimately rank their associated risk to the plant: • Which assets exhibit the greatest potential consequence if a failure event occurs? • W hat is the relative severit y of the consequences? • How likely are these failure modes to occur? • What can be done to prevent these events? W hen following RCM, the three phases (Decide, Analysis, Act) provide a s t r u c t u r e to b e f ol lowe d du r i n g implementation. In a recent Reliable Plant article on "How to Implement Reliability- Centered Ma intena nce" by Jonat ha n Trout, he best describes some important aspects on how to implement reliability-centered maintenance. Failure Patterns Machine failures can often seem random. is can seem even more true when analyzing a single failure event or looking at only frag- ments of information on failure events. Being effectively proactive about avoiding machine failures requires a view into the future. Maybe not literally, but creating a prediction of a future failure on your equipment can be greatly enhanced by understanding the patterns of the past and envisioning those patterns extend onwards into the future. Some patterns can be easy to spot, but in many cases the many known and unknown variables that go into a potential failure mode make it difficult. Recognizing failure patterns for lubricated machines has been done for decades and proved instrumental in improving reliability from the design improvements, better iden- tifying operating limitations and including maintenance recommendations. Some patterns are straight forward, such as a steadily rising failure rate that increases as time progresses. Others create predictions based on a known time where the likelihood of the failure will spike dramatically, known as the time-based wear-out. e bathtub curve is an often discussed failure curve that incorporates a few different failure patterns together. On the front end is the possibility of infant mortality, that suggests machines have a higher propensity to fail upon startup due to manufacturing defects, installa- tion errors, initial lack of internal cleanliness or other built-in problems. Once a certain time has passed, the failure due to one of these causes drops dramatically. is middle period can be a long time and if a failure were to exist, it may be due to operational factors or uncon- COVER STORY