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PDM Technology Provides Strategic Differentiator in Competitive Markets
Aware Technology Launches Global VAR Initiative to Capture Application Opportunities
The value added reseller (VAR) program provides a licensing framework by which data-rich technology companies and research organizations can leverage PDM as an extension to their existing product and service offerings. The framework offers flexibility in terms of PDM’s licensing and integration within the member’s offerings. It enables members to capitalize on PDM’s unique data analytics. The patented data clustering capability within PDM is ideally suited for complex ‘big data’ streaming analytics applications. Those opportunities are the product of exponential growth in available data.
“Simply put, PDM enables our resellers to provide capabilities that were previously unavailable in the market. As a technology extension it provides clear market differentiation,”
The VAR program provides participating members with special licensing rights within an appropriate field of use. Applications are abundant due to the diversity of industry segments where data is currently underutilized. Although their June 2011 study focused on five industry segments, McKinsey & Company underscored the untapped benefits of “big data” to all sectors due to the potential for newly discovered variability, automated information synthesis and decision-making, among other factors. This breadth of opportunity provides Aware Technology and its VAR program with enormous opportunity in the manufacturing, process and related industrial markets.
Foundational members of the program include technology firms and research organizations. Control Station has integrated PDM within the company’s PlantESP™ monitoring and diagnostic platform. Control Station helped form Aware Technology in 2011, and it has been applying PDM within the process manufacturing sector to anticipate the failure of critical production equipment. Florida Atlantic University deployed PDM as part of a National Science Foundation Industry/University Cooperative Research Center (NSF I/UCRC), Center for Advanced Knowledge Enablement (CAKE) program to establish novel insights into the management of their LEED® Platinum certified engineering building. ChemStaff and MARS are deploying PDM to improve safety and operations in nuclear power plants in the US and China, respectively.
“Manufacturing facilities are overflowing with data yet most lack the ability to interpret it,” commented Dennis Nash, Control Station’s President. “PDM identifies relationships and variability in the data that could lead to catastrophic equipment failure. That insights imparts a distinct competitive advantage to our core technology offerings.”
PDM leverages a powerful data clustering and pattern recognition algorithm first introduced by NASA and more recently enhanced by Aware Technology. The original NASA algorithm has been used extensively in the monitoring of complex systems ranging from the launch of the Space Shuttle to the control and maintenance of the International Space Station. PDM actively monitors the data streams from numerous, interacting sources, and it applies a clustering algorithm to recognize patterns – patterns that represent the fingerprints of unusual and/or troubling trends. It is the only solution in the category of condition monitoring and anomaly detection technologies with the ability to adapt to changing conditions.
About Aware Technology
Aware Technology delivers “Automation Confidence through System Awareness,” by offering automated learning technology based on a combination of NASA Pattern Recognition and Data Clustering algorithms and automation industry specific Intellectual Property. Founded in 2011, Aware Technology delivers PDM (Process Data Monitor), with an assortment of supporting products and technology, delivered as an Enterprise Appliance, or as a SaaS (Software as a Service) Private Cloud hosted application. PDM learns from the day to day operation of your systems and automatically generates an experience database. It then generates confidence metrics for usual behavior and delivers notification on unusual behavior.