MapR Customer: Edwards

Edwards Selects MapR to Help Advance Industry 4.0 Vision

Edwards is a world leader in the manufacturing and supply of industrial vacuum systems and abatement solutions. Edwards has selected MapR to provide a core technology in a major shift for Edwards that embraces real-time data analysis from its equipment to help its customers improve quality and yields in vacuum-intense semiconductor manufacturing processes.


"As our industry sector is still largely focused on on-premise solutions for its data, the ability to deliver on-premise, hybrid and cloud implementations that all have an intrinsic and universal security model offers us a seamless future migration as and when this industry sector opens up to that transition."

- David Hacker, Strategic Marketing Manager for Edwards


The first deployment of the MapR platform is currently underway in a joint project between Edwards and Fraunhofer-Gesellschaft, in a cooperation that involves research, development and evaluation of specific sensor and IIoT technologies, with the aim of generating and securing high-quality data to feed advanced analytics. Key is the research on the correlation between process and pump behaviour to be piloted in the semiconductor cleanroom environment of Fraunhofer EMFT with a key role played by this new technology stack based on the MapR Data Platform.

Novel Machine Learning techniques will be used to detect anomalies in sensor data. For this purpose, data fusion of several sensor data for combination and pattern recognition, as well as algorithms for detection of specific states of instability are needed. The aim is to improve the process of predictive maintenance by exploring new machine learning algorithms fed with sensor data from above and below the cleanroom floor, to predict future performance and anomalies.

A secure connection will be implemented to allow data, machine learning models and equipment status to be exchanged in real-time between secure locations: on premise at the Fraunhofer EMFT CMOS line, and remote in the cloud or Edwards HQ. As well as reducing response time for service, this simplifies analytical model development and deployment. The aim is to demonstrate a new reference architecture, consistent with the principles of RAMI 4.0, but tailored to meet the challenging demands for data and IP security imposed by the semiconductor manufacturing sector.



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