Foxborough, MA - ICONICS, a Microsoft Gold Certified Partner of the Year and provider of Web-enabled, OPC-based, HMI/SCADA Visualization and Manufacturing Intelligence software for Microsoft Windows® operating systems, announces the release of Quality AnalytiX, a Statistical Process Control (SPC) quality analysis suite that is flexible enough to apply to any quality monitoring application, yet simple to configure and deploy.

It offers an extensive set of SPC calculations, control charts, portal dashboard views and standard quality reports that can be applied in a variety of combinations to help pinpoint quality outliers. Quality AnalytiX is built upon ICONICS universal connectivity which, via a wide range of industrial and IT open standards, can easily connect to your equipment and systems to immediately drive improvements.

The demand to increase product quality and reduce scrap is critical in many manufacturing applications. The expectation to have Six Sigma or better conformance to product specifications is required today. Achieving best-in-class quality output requires continuous analysis and real-time quality control. 

Quality AnalytiX utilizes ICONICS Hyper Historian, a high performance mission critical plant data historian. The architecture supports large enterprise-wide quality programs as well as applications requiring very fast sample rates. Quality AnalytiX applies ICONICS browser-independent visualization technology, enabling it to publish all charts, dashboards and data views for viewing on any browser, tablet or smartphone.  In addition, ICONICS multimedia alarming can advise of quality deviations through SMS emails, alerts and marquees. 

Quality AnalytiX enables operators, quality personnel, manufacturing engineers and management to view quality SPC data and other production parameters impacting product quality. Users can apply any of the extensive set of SPC calculations to any process variable: X-bar, R-bar, S-bar, sigma, moving average, Cpk, Ppk and much more. Integrate SPC data into expressions and logic to drive corrective actions based on process trends.