Achieve higher manufacturing quality at a lower cost.

Get a comprehensive view of quality and operational performance across the enterprise and throughout your supply chain. Better support IIoT 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.


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.

Quality explorations

View high volumes of process sensor data in context of production events like batch and product changeovers. Visually identify areas needing investigation for a faster, deeper understanding of process.

Predictive quality

Mathematically model your production quality measures, such as yield. Run these models in real time and get predictive alerts on quality issues before they happen.

Process optimization

Use machine learning algorithms to analyze your process and determine the optimal setpoints. Maximize yield throughput while minimizing cost.

Our objective is to improve production, not spend time producing or collecting data. muRata logo Makoto Miyamori Senior Manager, No. 2 Manufacturing Innovation Section Manufacturing Enhancement Department

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