Machinery Lubrication magazine published by Noria Corporation
Issue link: https://www.e-digitaleditions.com/i/1480588
www.machinerylubrication.com | September - October 2022 | 9 ML ML ML ML domain knowledge, common sense and a dose of good old-fashioned wisdom? HUMAN HEALTH DIAG- NOSTICS VS. EQUIPMENT HEALTH DIAGNOSTICS I am in the middle of dealing with my own health crisis because of a recent diagnosis and treatment of B-Cell Non-Hodgkin's Follicular Lymphoma. In June 2021, I found a lump in my neck and reported it to my medical team. Once reported, this led to additional blood tests, ultrasounds, CAT scan, live X-ray needle biopsy and then a PET Scan to confirm the assumed diagnosis and next steps. None among us ever wants to hear those three dreaded words: "You have cancer!" However, being able to assess all the data available to me, examining statistical outcomes of the treatment efficacy available and getting expert advice from oncologists and other specialists allowed me to make the wisest decision that was right for me. Compare and contrast that to the reality of asset and equipment health management. I have been involved in the business of tribology and lubrication as an end-user, reliability engineer and vendor in industries such as mining (both surface and underground), heavy construction and aggregates, rail trans- portation, oil and gas and renewable energy. I have seen organizations deploy state-of-the-art condition monitoring and analysis technolo- gies in the form of inline oil sensors, wireless vibration accelerometers, SCADA data, Artifi- cial Intelligence (AI), Machine Learning (ML), Industrial Internet of ings (IIoT), Edge Computing and Big Data — always with the thought that this would be the next all-encom- passing silver bullet to solve every issue. In the end, a piece of hardware, a sensor, an oil sample, an FFT or a thermography image is just that — a bit of data that needs to be priori- tized, acted upon with root cause identification and resolved through a deliberate course of action. In the high-dollar engineering and maintenance world, professionals are required to act with deliberate and intentional purpose, or the outcome is nothing more than putting out fires, changing parts, maintaining the status quo and performing business as usual. Technology is great. e advancements that have been made in just the last ten years alone in the field of machinery condition monitoring have been amazing. But successfully utilizing the data these tools give us really boils down to action and prioritization — moving from a diagnostic approach to a prognostic approach. is requires combining the data from tech- nology sources with a solid understanding of and commitment to basic maintenance funda- mentals and traditional oil analysis. Your outcomes, will be different than another maintenance or reliability specialist at a different organization based on your environmental conditions, maintenance expectations and personal experience. Using your experience, gathering insights from oil analysis reports and sensor data and combining that with the expertise of your lab and lubrication vendor will help you make the wisest decision. THREE STAGES OF RESPONSE What we discussed above is essentially the "stages of response" you would go through after receiving results from testing. e three stages include interpretation, decision and action. ese stages can apply to both machine health monitoring and human health. Just as with my own cancer diagnosis, you need to be able to bring together all the data avail- able, examine the options available, make the wisest decision for your equipment and organization and then act on that decision. 1. Interpretation • Questions about the results: Do you have trust in the numbers, flags and commentary? If you do have concerns, chat with your laboratory (or doctor) to get more details. • K nowledge of the situation: is is typically an internal conversation — you may discuss it amongst your family or dive deep into your own under- standing of your situation. From an organizational perspective, your opera- tions group should be able to provide context a round oil ser vice hours, component hours and recent repairs that can potentially impact the interpre- tation of the results. • Add it iona l perspec t ive: Dif ferent parties can interpret results differently, so getting perspectives (or second opin- ions) from equipment manufacturers, oil suppliers or other sources can help build consensus. 2. Decision • Weigh your options and make the call: You could be faced with a "do something or nothing" decision, or you may have NONE AMONG US EVER WANTS TO HEAR THOSE THREE DREADED WORDS: "YOU HAVE CANCER!"