Augury: Leveraging IoT and AI for Real-Time Machine Health Insights
Technology Category
- Analytics & Modeling - Machine Learning
- Functional Applications - Manufacturing Execution Systems (MES)
Applicable Industries
- Equipment & Machinery
- Healthcare & Hospitals
Applicable Functions
- Maintenance
- Product Research & Development
Use Cases
- Additive Manufacturing
- Manufacturing Process Simulation
Services
- Cloud Planning, Design & Implementation Services
- Data Science Services
About The Customer
Augury has grown steadily since its startup days, now employing more than 100 people in New York and Israel who work to provide customers superior insights into the health and performance of their machines. Specifically, the company helps high-speed manufacturing and continuous production for Fortune 500 companies in industries such as pharmaceuticals, food and beverage, and consumer packaged goods, among others. In these “always-on” manufacturing environments, maintaining production health is key. Augury’s technology helps customers perform vital monitoring of their manufacturing and production lines using IoT devices and manufacturing analytics. The platform includes sensors, networking connectivity, dashboards, and diagnostics.
The Challenge
Augury, a company dedicated to providing insights into the health and performance of manufacturing machines, was facing a challenge. The founders of Augury, graduates of the Technion—Israel Institute of Technology, realized that while they could often tell when a machine was malfunctioning based on changes in sound or performance, the machines themselves lacked the ability to signal exactly what was going wrong. This led to inefficient troubleshooting methods such as manually cleaning fan airways to solve software problems. Furthermore, as Augury grew and began to handle a significant increase in enterprise customers, it needed to rebuild its IoT platform to be able to scale sufficiently. It required a stable cloud solution for IoT that could offer superior scalability, as well as a broad range of technologies and functionality.
The Solution
Augury decided to launch a startup dedicated to making machines smarter and more reliable, using machine learning and IoT technology. Augury was launched in 2011 as a cloud-based solution deploying IoT devices that are connected to manufacturing machines around the world. These devices continuously send data to the cloud where it is analyzed by Augury’s machine learning algorithms, resulting in insights that are immediately provided to its customers. To handle the increase in enterprise customers, Augury decided to complete a full migration to Google Cloud, moving all of the company’s microservices to Google Kubernetes Engine (GKE). Augury uses Google Cloud big data technology including Cloud Dataflow and BigQuery to push data from basic Cloud Storage buckets into BigQuery tables, which enables tens of millions of machine learning features. This allows Augury to run faster research cycles and enhance the algorithms that predict machine failures.
Operational Impact
Quantitative Benefit
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