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									Using PI for Back Testing Usage-
Based and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset

Larry Hruby             Gopal GopalKrishnan, P.E.
Basin Electric          OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
   – Basin has Ventyx AssetSuite (aka Indus Passport)
   – DTE has IBM Maximo
• Case studies for back-testing:
   – Usage-based strategies
   – Condition-based strategies
• Q&A
                                         Sebastien Cournoyer, CMRP
                                         DTE Energy
What You Can Expect
• Talk is not product specific – use several tools available
  in the PI Infrastructure

• Start with maintenance tasks and work backward to
  see if data exists in operations history that can be used
   – Collect additional equipment inspection data for proactive

• Use PI tools and in-house resources in small
  increments without new capital outlay
Coal-fired Power Plant

        Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
  wholesale provider (generation and
  transmission) of power to 126 Rural
  Electric Systems covering portions of 9
• Operate coal, wind, gas, oil based
  power generating facilities and a
  synthetic natural gas production facility
• Capacity
   – 3623 MW (Base load)
   – 405 MW (Peaking – CTs)
   – 136 MW (Wind)
  Basin - Leland Olds Station (LOS)
  Lignite with PRB (Powder River Basin)

Unit 1: 220 MW - 1966
 Pulverized Coal Boiler (Babcock & Wilcox)
 Turbine, GE
 DCS, Emerson Ovation 2007 upgrade

Unit 2: 440 MW - 1975
 Cyclone boiler (Babcock & Wilcox)
 Turbine, Alstom
 DCS, Emerson Ovation 2006 upgrade

Under Construction:
 Limestone Scrubbers for SO2 capture         Leland Olds, Stanton, North Dakota
  ($410MM capital project)
Leland Olds Station (LOS)– Software Infrastructure

   OSIsoft PI (piloted in 2005)
      • 20,000 tags
      • Emerson Ovation DCS, Rockwell PLCs, GE relays

   Ventyx Asset Suite (previously Indus Passport)
      • Started using in 1998 as Passport, has evolved into Asset
        Suite in 2008
      • Used for Work Management, PM’s, Inventory,
        Equipment spec’s & history, Purchasing, Contracts
 Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
  (CBM) for years
   – Vibration, oil analysis, thermography etc.
• Investigated Rockwell and OSI PI as platform to feed
  CBM and operational data to AssetSuite
• PI data reviewed:
   –   Standard PM work orders usage based
   –   Machine status work order management
   –   Sensor drift and calibration
   –   Control Loop Health
   –   Condition-based notification
DTE Energy – Detroit Edison
                 Detroit Edison
                 • Michigan’s largest electric utility with 2.2
                   million customers
                 • Over 11,000 MW of power generation
                   from 7 plants - mostly coal fired
                 • 54,000 GWh in electric sales
                 • $4.7 billion in revenue

                         DTE Energy - Detroit Edison
   DTE - Plants and Performance Center

   Monroe – 3,135 mw           Belle River – 1,260 mw       Harbor Beach – 103 mw

Trenton Channel - 730 mw   Performance Center – 11,588 mw    St Clair – 1,417 mw

   River Rouge - 527 mw          Greenwood – 785 mw            Fermi – 1,100 mw
DTE – History of PI and Maximo

• PI is a key infrastructure and technology enabler for
  real-time operations data as part of the “Enterprise
  Business System” at DTE
Additional details from a Nov. 2008 presentation at:

• IBM-Maximo is a key application for work management as part of
  the “Enterprise Business System” at DTE
Additional details at:
DTE – Details of PI usage
• In use since 1998 –
  started with a pilot at
  Monroe in 1998
• Enterprise Agreement for
  corporate wide use
• PI is an infrastructure
  product – magnitude of
  use and functionality is
DTE - Total Fleet Management
                  Drives Performance Excellence
                            Process Costs
                             Asset Health
                       Operational Performance
                             Market Value
                          Fleet Optimization
Work Management
      SAP                  Real-time                            Fuel Coat Framework
     Maximo                                                    Unit Capacity Framework
                      Process Applications
                                    Expert Systems

                               SME Status Displays

                                    WEB Portal

                           Distributed Control Systems (DCS)
                                 Distributed PI Historians
 DTE - Control & Technology Framework
  Fossil Generation                                   Making right decisions when it matters!
Business Unit Strategy                                           Drives Performance Excellence
                                          Fleet                              Fleet Optimization
                                       Optimization                     Process Costs, Asset Health,
     Actionable                          Process Costs
                                                                    Operational Performance, Market Value
                                         Asset Health,
Information – KPI’s                      Market Value    15%
                                                                             Relate all Data Sources
                                 Business Intelligence                 ProcessNet Framework
                                  Outage & De-rate (UCF)      (PI, ProcessGuard, Maximo, SAP, UCF, P3M,
                                   Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)
                                                                           Advanced Analysis & Process Optimization
                                    Expert Systems                                         Reliability Academy
                            Predictive Monitoring, Optimization              Equipment, Process, Performance, Reliability Models
                               MBO/PdM/Risk Assessment 60%                          Closed Loop Process Optimization

                                System Dashboards                                        Fleet Drill down
                               Fleet Status Assessment                90%             Subject Matter Experts

                                   WEB Visualizing                                       Standard User Interface
                            Plant Alarm, DCS Real-time WEB Graphics                            WEB Visualization
                            Easy Access to Information                     100%
                                                                                            Process Discrete Data
                             Engineering Applications                                         Engineering Applications
                                                                                              RFID, PMAX, DFTS, eNote,
                        PMAX, Digital Fuel Tracking, Fuel Cost Framework
                                                                                                Fuel Cost Framework,
                               Process Discrete Data                              90%            Alarm Management

Discrete data                                                                                     Post Event Analysis
                            Distributed Control Systems (DCS)
                             Distributed OSIsoft PI Historians                                        DCS, PLC & PI
Limited value
                             Large Population of Data                                 90%
                                                                                                   % Complete
Link Operations and Maintenance

• Business goals
   – Usage based maintenance (UBM) strategies
      • Mostly, data is already in PI
   – Condition-based maintenance (CBM) strategies
      • When relevant data not in PI, collect equipment inspection
        specifically designed to drive maintenance benefits
• Business justification
   – Calendar-based maintenance strategy := Amount of
     maintenance will be same as last year
   – UBM and CBM:= Opportunities for savings
   – Use PI history and Maintenance history to:
      • Back-test calendar based PM for conversion to UBM
      • Back-test corrective work order (CM) events for conversion
        to CBM
Usage-based Criteria
                     • PI totalizer
                     • PI time-filtered conditional expressions
• Run-hours -        (time-weighted and event-weighted)

  – Coal feed conveyor
  – Pulverizer
  – High pressure service water pumps
• Run-modes - number of starts, number of
  trips – Peaker CT blades
• Run-weight - tonnage processed (mining
  industry), flow-rate (time-integral) converted
  to volume
Service Water Pump – Usage Based
  Pumps were off for extended period, however the PM WO still went
  out - 28 PM hours
Fuel Conditioner – Usage Based
         Equipment runs about 80% of total year; usage based
         maintenance can save 152 PM hours
Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site
Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site
Condition-based Criteria
• Equipment failure is known to be correlated to a
  slowly degrading metric that can be monitored
   – Temperature (Motor windings, Bearing)
   – Pressure or DeltaP (heat-exchanger plugging, filters)
   – Vibration – Amplitude, FFT etc. ; Also interpret along
     with operations data in PI
• Instrument and transmitter calibration
• Control loop health
Secondary Air Heater Plugging
      Air heater tube plugging causes DeltaP (green line)
      to increase over several months and is a trigger for
Boiler (convection section) Tubes - Plugging
       Rapid rate of change of Delta P over several days
       is a trigger for maintenance
Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.
Green line shows the inlet water temperature which
is relatively constant
Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide
Vibration – Conveyor Motor
            Shaft realignment resolves the vibration issue
Instrument Drift – O2 Analyzer – U2-E
  Based on redundant dual sensors
Transmitter Drift
            Boiler feedwater pump discharge pressure
            Based on redundant triple transmitters (PressA,
            PressB and PressC)
            XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

                                Not Good
Transmitter Drift – U1 – Spray Flow
             Green – Delta between the transmitters
             Blue – Unit 1 is at about 220 MW
Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%
Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….
         Manual Inputs – Operator Rounds in PI
     Equipment inspection data collection specifically designed to help maintenance
     tasks (data not already in PI)
     Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

aspx (retrieved Jan 2009)

            Operator Rounds: V-PLOW status on a coal conveyor belt
Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.
Manual Inputs – Operator Rounds in PI
    Equipment inspection data specifically designed to help with
    maintenance tasks (data not already in PI)
    Everything we visually inspect, measure or observe can be recorded in PI
    to track, trend and monitor
•   Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
•   Dust Collector
•   Screw conveyor
•   Electric motor
•   Reducer
•   Bearings
•   Transfer point / chute liner condition
•   Limit-torque actuator
•   Hydraulic cylinder, Pneumatic cylinder
•   Pumps
•   Mechanical seals
•   Conveyor skirting
•   Conveyor scraper, primary and secondary
•   Idler, roll assembly
•   Pulley
•   Lube system
•   Coupling
•   Torque coupling
•   Valve
•   Piping
• Operations history and maintenance history can validate and
  quantify benefits for usage-based criteria prior to deployment

• Use manual input data (Manual Logger) to supplement condition-
  based strategies

• Review control loops, including the instruments, transmitters and

• Vibration data – combine with equipment operating conditions
  for better diagnostics
Enterprise Gateway
    SOA (service oriented architecture) to exchange information
    between the PI System and any external system via web services.
Thank you


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