Comparing machines and creating an "industry index' for performance.. would you be interested?

James Newman

Hello all... @Alexander Pastor started a great conversation about the new compare machines functionality. His request (which we love) is the idea of being able to compare against more than just his own machines, but using Augury's vast database of machines to compare against 'industry best practice' for different types of machines.

We love this idea, and @Jedidiah Kiesel from our team is leading a discovery process to create use cases, understand how users might leverage this information and basically do a feasibility study to help craft a product story for creating this type of functionality.

We would like to ask for your help in this journey, so if you are interested in participating, have ideas and/or thoughts, we want to talk with you. Please respond to this thread and we will start the conversation. Thanks @Alexander Pastor and @Scott Reed for starting the brainstorming!

See the original post by Alexander here:

https://augury.vanillacommunities.com/discussion/65/augury-data-for-equipment-monitoring-prioritization-design-considerations

[Deleted User]

I think this is a good idea. We probably need some context though. For example, I can install a fan on a monolithic slab and have a low amount of vibration. If I install that same fan on a two-story high metal framework, the sympathetic structure borne vibration will also be detected by the endpoints, leading to elevated readings. The fan may be fine in the second case if the motor and fan are moving (swaying) together on the framework, but the data sets may not truly be comparable. In short, the mounting characteristics and process/operational characteristics are important considerations.

Alexander Pastor

Raymond brings up a good point about contextual information for specific use cases, but if we start looking at large sample sizes, we can start to think about using the central limit theorem to approximate the industry average. There are some assumptions and other considerations that need to be made here, but the main concept I think James is getting at here is leveraging that vast Augury database to gain insights utilizing the metadata and contextual information that Augury does obtain.

Kevin Loos

Might be interested from ICL-Lawrence to explore this new 'industry index' performance KPI. Would be great to know how we are performing on similar equipment vs. industry standards and best practices.