Rob Spiegel

June 1, 2015

4 Min Read
Siemens Juices Big Data Analytics with Omneo

Siemens PLM has created Omneo Performance Analytics (PA), an application in Omneo, which the company picked up when it acquired Camstar last fall. Omneo PA was designed to manage product performance intelligence -- big data analytics in simpler terms. The platform monitors data across a product's supply chain and customer experience, analyzing billions of data combinations in seconds. The goal is to uncover hidden intelligence that can pinpoint the source of product issues.

As an example, one customer discovered a problem with a product and was able to quickly identify the depth and breadth of the problem. "They found a problem on a product they were shipping and they didn't know how big the problem was. Was it across the production center, across multiple products, across suppliers?" Steve Bashada, SVP, Cloud Services, Siemens PLM, told Design News.

Omneo-screen.jpg

Using Big Data displayed in a comprehendible view, the customer was able to identify and make a change in the product over a weekend. "That's the power of having data at your fingertips -- seeing the scenario, seeing the breadth of the data, and then acting on it," said Bashada. "In the past, they would have had uncertainty about the problem for days, and then they wouldn't have known the breadth. Instead they had an instant view of their data."

MORE FROM DESIGN NEWS: Unstructured Big Data Is a Big Manufacturing Challenge

According to Bashada, the biggest problem with big data is not accessing it. The difficulty is getting a clear view of it. "There is quite a bit of data being produced, and many companies are operationalizing their data," he said. "Some are producing data but can't look at it. It's hard for them to put together the entire picture. They need a platform that can put together parts of the data to create a big picture, which is sometimes called actionable threads."

He also noted that most companies he visits are already working on managing their data, but it's not usable. "Every customer has a big data solution they've been working on, and it's lying over there dead," said Bashada. "They just can't get the thing synchronized. It's not an easy job. People don't know what data they need to look at or what value it has."

Discovery, Monitoring, and Dashboards

Omneo PA offers three components in a big data cloud environment: discovery, monitoring, and dashboards. Discovery provides a rapid combination analysis of all possible data sets, creating a view into big data. Discovery identifies and displays the highest contributing factors to data anomalies. The anomalies present questions the company previously did not know to ask.

The graphical monitoring provides a view of product performance across the value chain, from design and production through supplies and customers. This allows companies to track current and emerging trends related to their products so they can make fact-based, data-driven decisions.

MORE FROM DESIGN NEWS: Learning to Use Big Data

The dashboard workspace allows for customization of data analytics definitions and key performance indicators (KPIs). Definitions and corporate-wide KPIs are built as modeling objects with multi-level definitions, for easy reuse. This structure was designed to help users interactively explore custom data analytics and KPIs or schedule them for monitoring, and view the results whenever needed. "You set the KPI, set the range, and you can get an alert each time it exceeds the range," said Bashhada. "You visually set up the KPIs."

One of the aspects of big data that often surprises its users is hidden patterns that reveal product problems that show up in unexpected ways that make it hard to trace back to a product flaw. "Product performance analytics empowers us to discover hidden patterns in data in order to ensure optimal product performance," said Bashada.

He noted that every customer he visits has a big data project, and all of them are under supported. "They try it themselves first, but they don't have 100 people working on it. They have two smart guys in the hole, and that works for half a solution," he said.

Rob Spiegel has covered automation and control for 15 years, 12 of them for Design News. Other topics he has covered include supply chain technology, alternative energy, and cyber security. For 10 years he was owner and publisher of the food magazine, Chile Pepper.

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About the Author(s)

Rob Spiegel

Rob Spiegel serves as a senior editor for Design News. He started with Design News in 2002 as a freelancer and hired on full-time in 2011. He covers automation, manufacturing, 3D printing, robotics, AI, and more.

Prior to Design News, he worked as a senior editor for Electronic News and Ecommerce Business. He has contributed to a wide range of industrial technology publications, including Automation World, Supply Chain Management Review, and Logistics Management. He is the author of six books.

Before covering technology, Rob spent 10 years as publisher and owner of Chile Pepper Magazine, a national consumer food publication.

As well as writing for Design News, Rob also participates in IME shows, webinars, and ebooks.

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