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Augury provides manufacturers and other industrial sectors with insights into the health of machines, processes, and operations to transform how people work and what they can create. Together with their customers, we are building a world where the combined work of people and machines makes life better in every way. Their Machine Health and Process Health solutions use purpose-built AI, trained by industry experts and the world’s largest data library, to help customers eliminate production downtime, improve process efficiency, maximize yield, and reduce waste and emissions. Augury’s global customers achieve 3-10x ROI, often in a matter of months.
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The predictive capabilities of the vibration data have been very impressive - we regularly receive alerts on machines that are operating outside of spec, and the contextual analysis provided with the alerts helps our plant teams understand what steps are needed to address the issues. The diagnostics are generally accurate and we've benefited from the guidance around potential machine failures and probable timelines and confidence levels for these failures. The platform user interface is user-friendly, well-organized, and generally intuitive - our plant teams have provided positive feedback around the visualizations of machine health and the associated performance metrics for the machines that we have instrumented with sensors. The ability to communicate directly with analysts in the platform has been a well-used and effective feature. The support program (remote diagnostics, formal training, knowledge bases and how-to resources, and technical documentation) is mature and targeted at the right audience for an organization of our size.
The part I like most about Augury is how understandable the insights are. Instead of handing over raw vibration data, it explains the issue in simple terms and gives a clear recommendation. This makes it easier for technicians and managers alike to act on the data without needing a data expert to interpret results. It's also helped get operations and maintenance on the same page, which is not always easy.
The information it gathers helps ensure machine health. This aids in ensuring planned preventative maintenance and cost saving. It is also a step into the future with AI within engineering diagnosis.
The implementation process was complex and resource-intensive, as we had to coordinate personnel to help with asset inventory, sensor deployment, system calibration, and data collection for baseline well in advance of seeing the benefits of the solution. We required quite a bit of IT support to enable the connectivity of the solution in our plant environments. We have experienced uneven adoption of the platform by end users - some of our experienced maintenance leads were initially distrustful of the alerts that were sent out by the system and required training and some follow-up inspections to demonstrate the validity of the data being collected. The Augury ecosystem uses proprietary sensors, which limits the amount of integration with our other plant monitoring systems, creating a data silo and limiting our ability to evaluate the vibration sensor data within the broader context of our plant data ecosystem.
While Augury has been a useful tool for us there are a few rough edges. Some alerts can feel a little too broad, and integration with our older equipment wasn't plug and play. The bigger challenge, though, was cultural. It took time for people to trust the system and adjust their routines based on what it suggested.
I deal with any hardware failures, and depending on the location of endpoints it can be problematic.