Sas Predictive Asset Maintenance

What does SAS® Predictive Asset Maintenance do?

SAS Predictive Asset Maintenance enables organizations to reduce the risk of revenue loss by reducing asset and plant downtime. By predicting events that can cause outages, the solution can help reduce the amount of unplanned maintenance and maintenance costs. It also helps organizations run their assets at peak performance, improving quality and reducing energy costs.

Why is SAS® Predictive Asset Maintenance important?

SAS Predictive Asset Maintenance helps organizations achieve optimized, sustainable maintenance strategies – and improved performance and availability of production equipment. It supports predic-tive maintenance of business critical assets and equipment, with minimal disruption to operations. As a result, you can maximize the use of maintenance resources to meet operational goals for profitability, safety and environmental compliance.

Who is SAS® Predictive Asset Maintenance intended for?

The solution is designed for those in the operations and maintenance community, and senior-level managers who are responsible for achieving and exceeding quality, productivity, utilization and cost targets throughout the supply chain. With SAS, they can improve productivity and reliability while reducing maintenance costs and downtime.

SAS® Predictive Asset Maintenance

Optimize asset maintenance for reduced downtime and increased productivity

Capital equipment investment de-mands a maintenance strategy that keeps operations up while guaranteeing safety and reliability. There is a constant demand for higher asset uptime, less unplanned maintenance and reduced maintenance costs.

Most organizations use basic monitor-ing consoles provided by the asset manufacturers to track performance and maintenance needs of equipment. Unfortunately, these consoles are limited in scope with little emphasis on analytics, resulting in isolated views into separate tags of assets. This process is resource intensive, time consuming, prone to false alerts and driven mostly by domain knowledge and biased judgment. As a result, organizations are forced to be reactive, rather than proac-tive, in their maintenance strategies.

SAS Predictive Asset Maintenance helps organizations achieve optimized, sustainable maintenance strategies and improved performance and availability of equipment. For predictive maintenance of assets with minimal disruption to pro-duction, look to SAS for the ability to:

• Improve equipment reliability and reduce unplanned downtime.

• Provide early warnings for more cost-effective maintenance.

• Reduce man hours and maintenance costs by pinpointing problems and aligning resources.

• Detect and correct issues earlier

to mitigate the risk of failures and

outages.

As a result, you can maximize the use of maintenance resources to meet operational goals for profitability, safety and environmental compliance.

Key Benefits

• Reduce shutdowns and downtime

Near-real-time monitoring and predic-tive alerts help you avoid major defects that can cause long downtimes. Alerts generated by predictive models also enable you to proactively address po-tential performance issues before they cause downtime or increase the length of planned shutdowns.

• Reduce unscheduled maintenance

Predictive and near-real-time perfor-mance alerts enable maintenance teams to fix issues during already-scheduled maintenance outages in a planned, more cost-efficient way, increasing availability and profits.

• Discover root-cause analysis

Award-winning analytics and predic-tive data mining capabilities drive continuously improved reliability and equipment efficiency, as well as better quality. They also help to identify the real drivers of performance issues out of hundreds, or even thousands, of measures and conditions. The avail-ability of this data helps engineers troubleshoot faster and initiate the best corrective action.

• Improve visibility

From legacy to modern MES, ERP, CMMS and other systems, SAS’ enterprise-maintenance-centric data model captures large volumes of data, regardless of format or source. The solution then transforms, standardizes and cleanses the data to prepare it for easy consumption by a wide range of user groups. The data model handles virtually any type of data, to incorporate both the current and future data types your organization may require.

FACT SHEET

Solution Overview

SAS Predictive Asset Maintenance is an analytic-driven solution that helps improve uptime of crucial assets and reduce maintenance-related disruptions of the operation, reducing stress on maintenance staff and resources. The advanced analysis workbench provides a rich set of root-cause analysis tools to identify the precursors of events. Data mining capabilities generate predictive alerts to help solve issues before they cause unscheduled downtime.

• Integration of all relevant data

SAS offers data integration and man-agement capabilities to capture all as-pects of the operation in near-real time - from sensor tags through operations and field performance. With the data model, you can overcome the barriers imposed by siloed operational systems. The solution provides true visibility into asset performance and its business im-pact and allows comparisons between different organizational units.

• Automated monitoring and alerting

A large-scale, automatic engine continuously monitors the health of all assets. It tests new sensor or condition data against defined rules and thresh-olds. Once tests have been flagged, supporting control charts and other reports can be supplied. Alerts can be published and sent through a variety of different media, such as Web portals, e-mail, pager, etc. The system lets you refine and integrate business rules for repeated use, enabling a continuous improvement process.

• Predictive modeling/model management

With unparalleled predictive modeling capabilities and techniques, you will receive alerts regarding equipment and assets that are likely to fail in the future. You can use this information to address these issues during scheduled maintenance for improved productiv-ity and performance. New sensor data and conditions are scored near-real time against predictive models that are developed based on historical events.

SAS® Supply Chain Intelligence Portal

Analytical Workbench with JMP® Journal

The solution’s model manager flawless-ly documents the history of the models (development, approval, adjustments, etc.) and sends alerts when the accu-racy of the models decreases.

• Advanced analysis workbench

The advanced analysis workbench enables maintenance and reliability engineers to analyze performance issues in a highly interactive and visual environment. It serves a broad variety of users, ranging from the casual user to the expert statistician. The solution provides a broad spectrum of tools to help you identify the root cause of performance issues, as well as identify metrics and conditions that indicate future issues.

• Reporting and key performance indicator (KPI) dashboards with drillable alerts

At any point in time, you can access per-formance information through standard and ad hoc reports, KPI dashboards, drillable views, snapshots and trends, and Web-based reports and graphs. The executive dashboard enables reporting on current performance at various levels and geographies. You can share information among those who need it at all levels of the organization.

Key Features

Enterprise-maintenance-centric data model• Measurementdatainbothcontinuousandcategoricalmeasures• Asset/equipmentdata• Physicalfailureanalysisdata• Failuredata• Inspectionrecords• Maintenancerecords• Environmentaldata• Costattributes• Organizationaldata• Operationsdata

Automated monitoring and alerting• Drilldownbyorganization• Drilldownbyassetgroup

Predictive modeling/model management• Decisiontree• Neuralnetwork• Regressionanalysis• Clustering• Scoring• Modelmanagement

Advanced analysis workbench• Paretocharts• Controlcharts• Histograms• Distributionanalysis• Regressionandcurvefitting

Reporting and KPI dashboards with drillable alerts• KPIdashboard• Web-basedreports• Web-basedgraphs

About SAS

SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. With innovative business applications supported by an enterprise intelligence platform, SAS helps customers at 45,000 sites improve performance and deliver value by mak-ing better decisions faster. Since 1976, SAS has been giving customers around the world THE POWER TO KNOW®.

SAS Service Intelligence Architecture Metadata Server

• AIX, HP PA-RISC, HP IPF, Linux 32-bit, Linux 64-bit for IPF, Solaris SPARC, Solaris for x64, z/OS, Windows 32-bit, Windows 64-bit IPF

SAS Service Intelligence Architecture Midtier

• AIX, HP IPF, Solaris SPARC, Windows 32-bit

Required software

• Web application server (e.g., Tomcat, IBM WebSphere)

• Web file server (e.g., Xythos WebFile Server)

Technical Requirements

Client

SAS Service Intelligence Architecture Clients

• Windows 32-bit workstations

Server

SAS Service Intelligence Architecture Data Integration Server

• AIX, HP PA-RISC, HP IPF, Linux 32-bit, Linux 64-bit for IPF, Solaris SPARC, Windows 32-bit

SAS Service Intelligence Architecture Server

• AIX, HP PA-RISC, HP IPF, Linux 32-bit, Linux 64-bit for IPF, Solaris SPARC, Solaris for x64, z/OS, Windows 32-bit, Windows 64-bit IPF

SAS Service Intelligence Architecture OLAP Server

• AIX, HP PA-RISC, HP IPF, Linux 32-bit, Linux 64-bit for IPF, Solaris SPARC, Solaris for x64, z/OS, Windows 32-bit, Windows 64-bit IPF

SAS Institute Inc. World Headquarters +1 919 677 8000To contact your local SAS office, please visit: www.sas.com/offices

SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration. Other brand and product names are trademarks of their respective companies. Copyright © 2008, SAS Institute Inc. All rights reserved. 103652_507497.1008