Getting Intelligence from Your Big Data

Sept. 22, 2015
Schneider Electric’s latest iteration of its Wonderware Intelligence software helps customers make faster, more advanced queries on their industrial Big Data.

One of the biggest problems with Big Data is simply that it’s big. Where this is a really big deal is getting a handle on how to put it all to work. With so much data coming from a range of disparate sources, it can be difficult to create the necessary context to make business decisions based on real-time operations metrics.

Wonderware Intelligence tackles that by helping manufacturers collect data from many different places—whether historians, ERP systems, quality systems or other sources—and put it into context to present key performance indicators (KPIs) in intuitive dashboards.

“A customer may need KPIs where bits of that data needs to come together, get rationalized and accumulated,” said Maryanne Steidinger, director of product marketing for asset, operations and information software at Schneider Electric. “Intelligence accesses the source data and puts it into context.”

At the Wonderware 2015 Conference this week in Dallas, Schneider Electric Software released the latest version of its enterprise manufacturing intelligence software, Wonderware Intelligence 2014 R2.

The newest version collects, calculates and contextualizes data and metrics from multiple sources across the manufacturing operation, puts it into a centralized storage and updates it all in near real time. Optimized for retrieval, the information can be used to monitor KPIs via customizable dashboards, as well as for drill-down analysis and insights into operating and overall business performance.

The improvements addressed in the newest version of Intelligence include:

  • The ability to use stored procedures to increase the speed of queries.
  • The ability to dynamically use start and end times for more precise queries.
  • Streamlined administrator rights for the Intelligence service.

Where Intelligence previously operated on a first-in-first-out (FIFO) basis, it now accesses the most recent information first, which improves the query time and overall performance, Steidinger explained.

Intelligence enables customers to really understand the important aspects of their manufacturing operations—like quality, throughput, variance, productivity, etc.—by rolling it all into a dashboard personalized for various enterprise and plant roles.

“Wonderware Intelligence is an easy-to-use, non-disruptive solution that improves how our customers visualize and analyze industrial Big Data,” said Graeme Welton, director of Advansys (Pty) Ltd., a South African company that provides specialized industrial automation, manufacturing systems and business intelligence consulting and project implementation services. “It allows our customers to build their own interactive dashboards that can capture, visualize and analyze key performance indicators and other operating data. Not only is it more user-friendly, it has better query cycle times, it’s faster and it has simpler administration rights. It’s an innovative tool that continues to drive quality and value.”

Though the dashboards are personalized to put the right data into the hands of the right person, they nonetheless provide everyone in the operation the same version of the truth drawn from a single data warehouse. The interactive and visual nature of the dashboards significantly increases the speed and confidence of the users’ decision-making, which allows them to improve their productivity, reduce operating costs and increase profitability.

“By not having to manually collect, calculate and store data, and then having easy access to and the right context for that data, users are able to improve their processes and optimize their energy consumption, often providing a return on investment within weeks of implementation,” said Christian-Marc Pouyez, Intelligence software product manager for Schneider Electric Software. “For example, its easy access to operating performance data allows users to compare trends so they can identify the root cause of some unscheduled downtime or other incident. Preventive measures can then be employed to eliminate future incidence, which means better overall performance. In fact, some customers have seen their productivity increase by more than 20 percent, while their manufacturing and productions costs, including their energy usage, have dropped more than 10 percent.”

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