From the Editors of CONTROL
Just a few years ago, John Kapron couldn’t tell how well DTE Energy’s electricity generating plants were performing when he wasn’t there, or if they were operating at all. Things have changed. Now, he told the audience at Matrikon Summit 2007 on May 9, he can use a Blackberry or other mobile workforce device organized according to a unit capacity framework (UCF) to check the status of almost every device at DTE’s plants in Michigan.
This can include viewing vibration data, 24-hour performance reports, current market data, and operator logs. Most of these reports are dynamically updated, and pages can be drilled into to find, for example, who was responsible for a specific de-rating event.
DTE’s two main divisions, Detroit Edison and Mich Con, operate nine major power plants and other facilities, and nearly all their units have ABB’s distributed control systems (DCSs) for a total of 300,000 process data tags. To the DCSs it’s installed since the early 1980s, DTE added OSI PI data historian in 1999-2000, engineering applications enabled by Matrikon’s Operational Insight and Control Performance Monitor, and finally a 24/7 Performance Center in 2005 and Performance Center Applications in 2006.
Kapron, DTE’s technological specialist, says all these efforts are designed to secure plant-floor data, turn it into useful, actionable information, and get it in front of decision-makers. He says DTE basically drives its raw-data foundation up through an organizational pyramid, whose layers include engineering applications data, web visualization for easy access, system dashboards, expert user systems, business intelligence, and finally key-performance indicators (KPIs) for overall fleet optimization. Likewise, the Performance Center enables continuous, real-time, predictive asset condition monitoring to maximize DTE’s asset market value.
Kapron adds that DTE developed its data visualization and optimization system by first taking all of its discrete data, and then building models based on it. This is important, for example, because DTE’s coal-fired Monroe power plant uses three types of coal, and checking their chemistry before they reach the boiler can help optimize operations, as well as find and asses any problems.
DTE next used WEBviz software to build DCS displays for the 6,000 total displays that it and ABB installed in the past. They also implemented screen replication functions and the capability to link them on the web, which enabled DTE’s dynamic report updating capabilities.
“We can click on our screens, and get instant trends, and even play back events from last night or earlier,” says Kapron. “And now, besides being able to see relevant data on our dashboards on our mobile workforce devices, we can see past reports, and future projections.”
Sumanth Makunur, DTE’s senior engineer, adds that DTE takes data from 150-160 different data processing sources and applications, and unifies it all with Matrikon’s Operational Insight Framework (resolution) integrated application environment. This provides a consistent framework for data analysis, reporting, and consistent graphical user interface (GUI). “Basically, all the data goes into one big bucket, and then is separated into business information, market information, and other categories,” says Makunur.
In its pilot implementation at Monroe’s pulverizer assessment application, Operational Insight provided milling, process, and production costs, as well as EAFs, Smart Signal watch list, work performed, work pending, and alarms data. To accomplish this, the software organizes data from a variety of Maximo, SAP, unit capacity, alarm, EPRI, PI and P3M-based sources onto one screen, which DTE calls an Equipment Hierarchy, for each piece of equipment. This includes both a hierarchical system index (HSI) and a work breakdown structure (WBS). “This common hierarchical thread allows common reporting, common methodologies, and an expanded system dashboard,” adds Makunur. “We now can go in three clicks from the plant level to the unit level; drill down on process costs; achieve the appropriate balance of preventive, corrective, and predictive maintenance; and all of this drives performance excellence,” says Makunur.