By combining the power of data integration, automation and analytics, SAS enables you to fully understand operational processes so you can make sustainable improvements and lower associated costs.
Enterprise quality-centric data model
Captures large volumes of data regardless of format or source – from legacy to modern MES, ERP and other systems.
Automated monitoring & alerting
Continuously monitors the health of all processes to ensure quality throughout manufacturing and operations with a large-scale, automatic monitoring engine.
Predictive modeling
Provides an array of analytical tools – including explorative analysis, design of experiments with optimizers, and cause-and-effect tools such as Ishikawa diagrams – to optimize process and equipment setups.
Advanced analysis workspace
Lets users analyze quality issues and explore areas of improvement in a highly interactive and visual environment. Serves a broad variety of users, from the casual user to the high-end statistician.
Reporting & KPI dashboards
Delivers customizable reports and graphs enabling information sharing among all who need it. Includes standard and ad hoc reports, KPI scorecards, drillable views, snapshots and trend analysis from across the manufacturing operation.
Get a comprehensive view of quality and operational performance across the enterprise and throughout your supply chain. Achieve better IIoT support with advanced data models.
Get support for the Industrial Internet of Things (IIoT).
With real-time monitoring throughout the enterprise, it's easier to identify patterns while processes are ongoing. You can be more proactive with fixing or avoiding problems and making improvements to equipment and processes on the plant floor.
Gain a holistic view of the enterprise.
An enterprise quality-centric data model can handle practically any type of data from virtually any source – including supplier data. And state-of-the-art analytics and reporting capabilities enable you to align performance strategies with results, so you can close the gaps between targets and actual performance.
Improve quality and minimize production costs.
Our advanced analytics, predictive data mining and machine learning capabilities drive continuous quality improvements, improved reliability and higher yields. With tighter controls and more efficient processes, you can minimize rework and scrap rates. This improves the overall manufacturing cost structure.
Understand changes quickly.
World-class quality control delivers up-to-the-minute insight into the performance and quality of your operations, enabling tighter process control at every level. Early-warning analytics alerts you to potential quality and performance issues so you can address them proactively before they escalate into customer problems.
Our objective is to improve production, not spend time producing or collecting data.Makoto Miyamori Senior Manager, No. 2 Manufacturing Innovation Section Manufacturing Enhancement Department
Solving Data Complexity Issues Across the Analytics Life Cycle
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