How SAS® Enables the Connected Factory
Connect disparate data sources in the era of Industry 4.0. Apply a combination of monitoring, diagnostics and predictive maintenance techniques to improve asset and product reliability, as well as lower the cost of unexpected downtime.
A holistic view of operations
- Remove barriers imposed by siloed operational systems and gain full visibility into what's happening on the shop floor and out in the field.
- Bring together the voices of the process, product and customer for a single, comprehensive view of both process and product quality.
- Integrate structured and unstructured operational data from sources across your business.
- Minimize unplanned downtime and increase the availability of key assets.
- Maximize overall equipment effectiveness (OEE).
- Increase return on assets (ROA) while reducing maintenance costs by shortening the mean time to repair (MTTR).
- Avoid rush parts deliveries, repair overtime payments and high buffer stocks.
Early warning of potential issues
- Apply quality-specific data models and patented analytics to drive early warning of emerging quality and reliability issues, data-driven root cause analysis and deeper process understanding.
- Help predict potentially catastrophic equipment and process incidents.
- Quickly identify design and production defects before they become widespread.
- Start small from one use case for a specific asset and grow in analytics maturity, number of use cases applied and scale of deployment for a smarter, more connected factory.
Why choose SAS for a connected factory & smart manufacturing software?
Apply predictive models to IoT, sensor and other equipment performance data to get early warning of potential failures or poor product performance. This translates into reduced equipment downtime, improved asset performance (improved yield and/or efficiency), reduced service related costs and improved SLA performance.
Reduce downtime & increase yields
Help ensure maximum operational efficiency of all machines in your connected factory production processes to increase yields and throughput and reduce energy consumption.
Lower maintenance & operations costs
Minimize costly unplanned downtime and optimize your maintenance cycles.
Create new revenue streams
Capture more value in the marketplace by augmenting your current product sales with high-margin service revenue.
Manufacturers Working Smarter With SAS
Optimizing the supply chain with analytics and IoT
Georgia-Pacific relies on SAS to improve equipment efficiency, reduce downtime, optimize shipping logistics and predict customer churn – balancing speed and quality to maximize efficiency and profitability.
Using machine learning to transform predictive maintenance for complex equipment
Lockheed Martin applies machine learning and IoT analytics to data from customers, its own engineers and parts vendors to form a real-time best practice for aircraft maintenance.
Putting IoT data from connected vehicles to work
Iveco Group uses SAS advanced analytics to interpret vast amounts of sensor data to uncover hidden insights that can reduce vehicle maintenance costs through innovative remote diagnostic tools.
Related Products & Solutions
- Advanced Analytics for IoT from SASAnalytics for IoT is a powerful platform with embedded AI and industry-leading streaming capabilities that enables you to drive innovation, efficiencies and results. SAS LU
- SAS® Asset Performance AnalyticsHarness M2M and sensor data to boost uptime, performance and productivity while lowering maintenance costs and reducing your risk of revenue loss.
- SAS® Field Quality AnalyticsDetect emerging issues and perform root-cause analysis to improve product quality and brand reputation.