Market Overview

Edwards Selects MapR to Help Advance Industry 4.0 Vision


First project at Fraunhofer EMFT continues research, development
and evaluation of specific sensor and Industrial Internet of Things
(IIoT) technologies for advanced analytics to help create smarter and
more reliable manufacturing plants.

Technologies, Inc
, the industry's leading data platform for AI
and Analytics, today announced that Edwards
, a world leader in vacuum and abatement solutions, is
using the MapR Data Platform to develop semiconductor industry solutions
to analyze data from its equipment within customer sites to deliver
predictive maintenance and near real-time anomaly detection as part of a
major step towards an Industry 4.0-based smart connected portfolio.

Edwards is a leading developer and manufacturer of sophisticated vacuum
products, abatement solutions, integrated solutions and related
value-added services. Edwards products are critical sub-systems to
manufacturing processes for semiconductors, flat panel displays, LEDs
and solar cells; are used within an increasingly diverse range of
processes. Edwards maintains 30 international sites, employing over
4,200 staff serving all major global semiconductor manufacturing

MapR will 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 David Hacker, strategic marketing manager for Edwards explained, "The
manufacturing of modern semiconductors include up to 1,000 process steps
with a significant and increasing proportion requiring vacuum and
abatement systems and a typical plant may have Edwards assets measured
in the 1,000's as critical sub-systems for these processes. Our vision
is to have all of these assets delivering near real-time information on
their performance and the detection of anomalies that may occur with a
deeper level of scrutiny. This allows us to create more evidence based,
relevant information on quality of vacuum service to enhance the
knowledge provided to customers so that they can quickly adapt to any
situation to deliver more efficiency and better quality of process
outcomes. Along with this, the data will enable increased and
predictable overall equipment availability along with ‘adaptive
triggers' for scheduled maintenance."

Edwards chose MapR to enable the capture and processing of diverse data
from a wide range of sources that is instrumental in helping it build
the machine learning models that will underpin many of these smarter
systems. "Our current and medium term aim is to include sensor data to
enhance the intrinsic Edwards asset data and to be able to make this
service available to other critical sub-system providers to create a
more granular and broader understanding of the environment that will
ultimately lead to adaptive control based on data analytics," said

"We have chosen MapR following a standard due-diligence method and the
experience of the openness of MapR in providing open exposure of their
customers to us and thus permitting us to form a preview of what it will
be like to work with MapR," said Hacker. "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."

"Our immediate needs also include the potential to interface seamlessly
to other platforms within our customers' sites so MapR's provision of
comprehensive API's is vital, but this is also important for us
internally as we need to vertically integrate to Edwards enterprise
resource planning and other related digital services," Hacker added.

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
, but tailored to meet the challenging demands for data and IP
security imposed by the semiconductor manufacturing sector.

Jim Stock, vice president of EMEA for MapR added, "Pioneers across many
industries recognize that working closely with suppliers, partners and
customers is vital to deliver new insights and breakthrough services.
Our implementation with Edwards highlights the benefits of a trusted
platform to enable multiple partners to seamlessly collaborate on data
intensive projects in areas such as the Internet of Things and Machine
Learning while retaining the highest levels of security and control."

About MapR

, provider of the industry's leading data platform for
AI and Analytics, enables enterprises to inject analytics into their
business processes to increase revenue, reduce costs, and mitigate
risks. MapR addresses the data complexities of high-scale and mission
critical distributed processing from the cloud to the edge, IoT
analytics, and container persistence. Global 2000 enterprises trust the
MapR Data Platform to help them solve their most complex AI and
analytics challenges. Amazon, Cisco, Google, Microsoft, SAP and other
leading businesses are all part of the MapR ecosystem. For more
information, visit

MapR is a registered trademark of MapR Technologies, Inc. in the
United States and other countries.
Other names and brands may be
the property of others.

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