Augury Data for Equipment Monitoring Prioritization/Design Considerations
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To expand on this, I know Augury collects a plethora of metadata for each machine/equipment. Is any analysis done overarching all of the equipment using that metadata to drive these types of insights?
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@Alexander Pastor - Yes, there is analysis that can be done utilizing the collected metadata to compare machine based on specified parameters. We recently introduced a new iteration to the Compare Machines tool that allows users to benchmark machine behavior and performance against other assets within their program. Here is some additional information on how to utilize that capability: https://view-su2.highspot.com/viewer/63ebcb47be21f558d2b3313a
There is a lot more opportunity to build this out and expand on the types of insights to help tackle the use cases that you mentioned. I've shared your thoughts and comments with our product organization as well.
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@Amy Marchesi The new iteration of Compare Machines looks beneficial. However, this is purely isolated to benchmarking assets within each company program, correct? Where I see the even greater potential for this is being able to benchmark against all other similar assets amongst all programs. I understand that there are likely complications or roadblocks to this, but here are a few things to think about:
What if we have a piece of equipment that just always seems to be going bad? And let's say it's not just at one of our facilities, but many of our facilities. Wouldn't it be great to know if our machines are performing significantly differently compared to even an "industry standard" that could be some aggregation of similar assets on other platforms? Perhaps that would help us look into how we are utilizing the equipment compared to other industries, or lead to some other conclusion for how we can extend the life of our equipment to meet the "industry standard".
What if during the design phase of a production line, we are trying to select between two similar motors that satisfy our criteria? If we had information on the average time to failure or average # of faults per year of both machines based on data from all the platforms, that might help us select the more reliable one.
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You are spot on Alex. Being able to hone in on "industry standard" and "best in class" are valuable benchmarks that can enable deeper dives into maintenance, installation/setup and application of service. In terms of operating environment, clean/dirty, we know these differences can create unique challenges in all these aforementioned areas. Service application is one area that is a black box to many, only to be sorted through multiple iterations of trial and error and continued confusion as to why one facilty realizes success while another cannot withstand another failure.
Example: Connected rotating systems (pump, gearbox & motor) may be most sensitive as associated fluid dynamics (NPSH, fluid level, vapor pressure, temperature, viscosity) may not be well understood or defined. Being able to capture service application would have significant customer benefits.
There are many other examples related to installation/setup and maintenance that can be identified as well.
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Hi @Alexander Pastor This is a good concept.. not sure how easy it would be for us today to turn that on, but we can take a look at it. Comparison functionality is improving regularly, so we can look at this concept. @Amy Marchesi will put that into the product team to evaluate, the "crowd-sourced" indicators could be super useful for everyone.
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@Alexander Pastor we reached out to the product team about this and @Jedidiah Kiesel would like to talk with you about this topic to explore use cases, how to display, etc. Would you be up to doing that? This is a use case we are exploring right now so this is great timing to help us advance it.
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For any who are reading this thread..
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