Machinery Lubrication magazine published by Noria Corporation
Issue link: https://www.e-digitaleditions.com/i/1356397
www . machinerylubrication.com | March - April 2021 | 29 www . machinerylubrication.com | March - April 2021 | 29 ML is whole interconnected future sounds wonderful and has the potential to take us into a new world where machines emit almost zero waste and have the capability of communi- cating the precise moment they need attention. Surely that day will come, although for that we will have to cross many deserts and ship- wreck in unexpected places. Today, machines still suffer unexpected failures and millions of dollars are lost in downtime and whether in that marvelous new era to come or in the current one, machines will still age and will ultimately be replaced. ose of us who have seen a machine/ component fully degrade wonder what can be done to extract a few more service hours before the replacement. e most notable event of this type that I've experienced happened in the Bolivian highlands at an altitude of more than 13,000 feet above sea level. We only needed the machine to last 20 more hours (a little more than a day of operation) in order for the project completion costs to be kept to planned levels, but the oil leaks in the powertrain were nearly unstoppable. Using SAE 40 oil, consumption was over 50 liters per hour and the outlook was rather grim. It was at that moment that a senior technician, one who had lived through count- less maintenance-related battles, decided to mix tar with the oil; the leaks were minimized and we reached the desired 20 hours needed to complete that part of the project. Applying a chemically equal but higher viscosity oil is a common solution when the machine is approaching its end of life, as doing so reduces wear, leaks and friction. Under most circumstances, it is necessary that a machine continues to operate under a regime as close to ideal as possible in order for the operating line to be maintained without causing losses or breaks in production. In the United States, the current average age of machinery depends on the industrial sector as well as its geographical location. ere are sectors that come from an economic boom with an average machine age of close to ten years. However, at the other extreme are indus- tries whose assets, such as gearboxes, began operating in the 1980s. In many cases, this machinery is under a predictive maintenance program that uses technologies such as vibra- tion, thermography or oil analysis. When using oil analysis as a maintenance tool, it is relatively Figure 2: Iron (Fe) wear values from a set of samples of 63 gearboxes Time Failure Rate Figure 3: Iron (Fe) wear measured values updated to Bathtub Curve Early Mortality Random Failures Wear-Out easy to set limits for component surface wear when the machine is in the flat phase of the bathtub curve. When we move to the sides of the curve, current data becomes less certain and it is very difficult to set those limits. In recent years, the bathtub curve has a short and simple initial stage, meaning the machines undergo a short premature life and enter full performance quickly. Additionally, due to all the technology available, we have been able to extend the service life of the machines, anticipating potential catastrophic failures and healing injuries before it is too late. At the other end of the curve in question, we can see that the effects of proper mainte- nance, advances in component improvements and control mechanisms on machines have allowed their service life to be extended as much as possible, although in many cases this has a downside to predictive maintenance itself. What reasoning should be applied in the aging fault zone? Let's address this question using a case study. Case study and field application In 2016, with an approximate popula- tion of 80 gearboxes and good traceability of oil analysis reports as a maintenance tool, Industry "A" was aware that these machines were already close to completing their life cycle. Around 30% of this group of gearboxes showed signs of aging wear and the subse- quent unscheduled downtime was directly related to aging failures. e remaining 60% showed evidence of following the same path as the previous group, and the last group did not show very aggressive signs of aging. e Planning & Scheduling department estimated that it would take between 5 to 6 years to replace all machines with clear signs that they had entered the final stage of their useful life (90%). is meant that it would be necessary to control and extend the life of the assets for the 5 to 6 years it would take to replace them. Within this scenario, all predictive main- tenance tools would need to be be used with