SAS Joins CESMII to Accelerate the Adoption of Analytics and AI
CARY, N.C., Feb. 7, 2023 -- More and more top manufacturers use artificial intelligence (AI), machine learning and streaming analytics from SAS to transform operations and better serve customers. SAS has joined CESMII, the Smart Manufacturing Institute, to further promote the use of advanced analytics across manufacturing.
“Facing a challenging economy and lingering supply chain disruptions, manufacturers are seeking to digitally transform themselves while boosting sustainability,” said John Dyck, CEO of CESMII. “Combining CESMII’s approach for standardized and contextualized manufacturing data with SAS’ deep expertise in AI and machine learning can help today’s smart manufacturers adapt to changing conditions and meet evolving customer needs."
Advanced analytics like AI and machine learning, when combined with big data management, streaming analytics, and edge computing, help transform data from Internet of Things (IoT) sensors into faster and more accurate decisions. These technologies support overall resiliency for manufacturing companies, helping them better use data to enhance production quality and efficiency, improve business decisions and support bottom-line growth.
“In high-tech factories, smart cities, and connected vehicles, technologies like AI, machine learning and streaming analytics drive digital transformation. And they help industrial organizations succeed, even in a challenging economy,” said Jason Mann, Vice President of IoT at SAS. “As a CESMII member, SAS will help more manufacturers better use these technologies to transform.”
Manufacturers Rely on SAS
By joining CESMII, SAS seeks to bring the power of analytics and data-driven manufacturing to more companies of all sizes and in all segments. Smart manufacturing organizations already seeing value from SAS include:
- Georgia-Pacific uses SAS Viya, SAS’s cloud-native, massively parallel analytics and AI platform, to improve equipment efficiency, reduce downtime, optimize shipping logistics and predict customer churn. With SAS, Georgia-Pacific saw a 30 percent reduction in unplanned downtime and a 10 percent improvement in overall efficiency, optimally balancing speed and quality to maximize profitability.
- Lockheed Martin (NYSE: LMT) applies SAS IoT analytics and machine learning to power predictive maintenance, reduce costs, and keep its C-130J Super Hercules aircraft mission-ready for search and rescue, peacekeeping, scientific research, military operations, humanitarian relief and more. Lockheed Martin saved 2,000 hours of aircraft downtime in six months by moving from reactive to predictive maintenance.
Manufacturing Analytics from SAS
The manufacturing industry has shifted, with digital transformation, sustainability and supply chain challenges here to stay. Manufacturers that do not evolve will get left behind, losing their competitive edge and their customers.
SAS advanced analytics deliver insights that manufacturers need to shift from being reactive to proactive. These insights help them make better decisions so they can exceed production goals and lower costs. With SAS analytics, smart manufacturers identify and solve numerous issues around quality, asset performance, service, warranty claims, supply chains and changing demand.
“Manufacturers have always embraced innovation,“ said Charles Phillips, Global Marketing Manager for Manufacturing at SAS. “Through advanced analytics and its many uses, manufacturers are quickly seeing the value delivered by machine learning, computer vision, streaming analytics and more.”
CESMII is the United States' national institute on Smart Manufacturing, driving cultural and technological transformation and secure industrial technologies as national imperatives. By enabling frictionless movement of information between real-time Operations and the people and systems that create value in and across Manufacturing organizations, CESMII is impacting manufacturing performance through measurable improvements in areas such as: quality, throughput, costs/ profitability, safety, asset reliability and energy productivity.