Software solutions and analytics developer SAS Analytics was chosen by stainless steel manufacturer Ulbrich Stainless Steel to provide an artificial intelligence- (AI-) embedded Internet of Things (IoT) solution to analyse data created by Ulbrich’s plant sensors.

This was done to deal with maintenance and production challenges to keep producing precision metals such as stainless steel on time at its plants.

“Precision and quality are key factors in manufacturing highly engineered metals that support our customers’ varied needs,” says Ulbrich COO Jay Cei.

He mentions that collecting machine and sensor data from the company’s factories and integrating that with enterprise resource planning system data will help the company understand the intricate relationships between equipment, people, suppliers and customers. “Using SAS to learn what our IoT data means is critical for understanding how we can become more productive and efficient in the future.”

Cei points out that streaming analytics will not only help Ulbrich understand what is happening now with its machines, but it will also enable it to predict future events, such as when a machine needs maintenance before it breaks down, says business intelligence and analytic services provider and SAS implantation partner Pinnacle Solutions president DJ Penix.

Streamlined Results

Using SAS Analytics for IoT allows business access to a range of AI, machine learning and streaming analytics available.

The software provides a simplified way for users to prepare stationary and streaming IoT data for analysis without specialised skills. Whether a data scientist or a business manager, they can use SAS Analytics to select, launch, transform and operationalise IoT data to make informed, timely decisions.

The upgraded SAS software provides open application program interfaces to enable integration with other SAS, third-party and open-source products.

“SAS talks about ‘democratising analytics’ as the ethos behind SAS Analytics for IoT,” said market intelligence firm IDC research director Marta Muñoz Méndez-Villamil in an IDC Market Note.

“This comes as a welcome message to a technology that seems to be stuck at precisely this stage. Tools and solutions that help simplify analytics, insights visualisation, and actioning of IoT data accelerate enterprises’ time to value from their IoT implementations.”

SAS IoT VP Jason Mann emphasises that companies can no longer afford to ignore the hidden signals in their IoT data.

“To thrive, organisations need a solution that addresses data complexity and automates timely and accurate decision-making. SAS Analytics for IoT delivers this capability across the entire analytics life cycle – from data preparation to discovery to scalable deployment.”

Technology market research firm Arc Advisory Group research director Mike Guilfoyle says there is a gulf between companies undertaking analytics-driven digital transformation and those successfully scaling their efforts.

“This is due in large part to the underlying complexity of Industrial IoT ecosystems and the many business needs related to them. “To be successful with IoT, an organisation needs an analytics solution that can support a diversity of needs, including myriad use cases, disparate user requirements, agnostic interoperability with systems and sources, the capacity to manage data at rest and in motion, and a breadth of analytics methods.”

SAS showcased its SAS Analytics for IoT and its embedded AI capabilities through connected patient, connected quality, and connected equipment demonstrations at analytics conference SAS Global Forum held in April in Dallas, in the US.