Achieve higher manufacturing quality at a lower cost

Screenshot of SAS Production Quality Analytics showing cluster with highlight

SAS Production Quality Analytics

Drive deeper production process understanding with predictive analytics. Maximize throughput and quality with prescriptive analytics.



Key features

Fully understand operational processes so you can make sustainable improvements and lower associated costs with the combined power of data integration, automation and analytics.

Cloud native

Compatible with cloud technologies – including Docker and Kubernetes – for large-scale, elastic, multitenant, distributed services. Ready-made to take advantage of the large volumes of data generated by the IIoT.

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.

Get to know SAS Production Quality Analytics

Recommended resources for SAS Production Quality Analytics

Solution Brief

Improve manufacturing quality with advanced analytics across the entire product life cycle

Ebook

Quality 4.0 impact and strategy handbook

Webinar

Optimizing manufacturing quality & yield with SAS analytics


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