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Using PI for Back Testing Usage- Based and Condition-Based Maintenance Strategies Prior to Deployment in Asset Management Gopal GopalKrishnan, P.E. OSIsoft,

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Presentation on theme: "Using PI for Back Testing Usage- Based and Condition-Based Maintenance Strategies Prior to Deployment in Asset Management Gopal GopalKrishnan, P.E. OSIsoft,"— Presentation transcript:

1 Using PI for Back Testing Usage- Based and Condition-Based Maintenance Strategies Prior to Deployment in Asset Management Gopal GopalKrishnan, P.E. OSIsoft, Inc. Larry Hruby Basin Electric Mark Blaszkiewicz Sebastien Cournoyer, CMRP DTE Energy

2 Agenda 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

3 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 maintenance Use PI tools and in-house resources in small increments without new capital outlay

4 Coal-fired Power Plant

5 Basin Electric Power Cooperative HQ – Bismarck, North Dakota, wholesale provider (generation and transmission) of power to 126 Rural Electric Systems covering portions of 9 states 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)

6 Basin - Leland Olds Station (LOS) Fuel: Lignite with PRB (Powder River Basin) blending Unit 1: 220 MW Pulverized Coal Boiler ( Babcock & Wilcox) Turbine, GE DCS, Emerson Ovation 2007 upgrade Unit 2: 440 MW Cyclone boiler ( Babcock & Wilcox) Turbine, Alstom DCS, Emerson Ovation 2006 upgrade Under Construction: Limestone Scrubbers for SO2 capture ($410MM capital project) Leland Olds, Stanton, North Dakota

7 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, PMs, Inventory, Equipment specs & history, Purchasing, Contracts

8 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

9 DTE Energy – Detroit Edison Detroit Edison Michigans 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

10 DTE - Plants and Performance Center Greenwood – 785 mwRiver Rouge mw Fermi – 1,100 mw Monroe – 3,135 mw Trenton Channel mw Belle River – 1,260 mw St Clair – 1,417 mw Harbor Beach – 103 mw Performance Center – 11,588 mw

11 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 presentation at: IBM-Maximo is a key application for work management as part of the Enterprise Business System at DTE Additional details at:

12 Success! 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 expanding

13 DTE - Total Fleet Management Real-time Process Applications Distributed Control Systems (DCS) Distributed PI Historians WEB Portal SME Status Displays Applications Expert Systems Financials Work Management SAP Maximo Market MISO, Fuel Coat Framework Unit Capacity Framework Drives Performance Excellence Process Costs Asset Health Operational Performance Market Value Fleet Optimization

14 Discrete data Limited value Actionable Information – KPIs Distributed Control Systems (DCS) Distributed OSIsoft PI Historians Large Population of Data Post Event Analysis DCS, PLC & PI 90% Business Intelligence Outage & De-rate (UCF) Maintenance & Market Relate all Data Sources ProcessNet Framework (PI, ProcessGuard, Maximo, SAP, UCF, P3M, Predictive Monitoring, NeuCo, LIMS, Plant View..) 25% % Complete ABB System Dashboards Fleet Status Assessment Fleet Drill down Subject Matter Experts 90% WEB Visualizing Plant Alarm, DCS Real-time WEB Graphics Easy Access to Information Standard User Interface WEB Visualization 100% Engineering Applications PMAX, Digital Fuel Tracking, Fuel Cost Framework Process Discrete Data Engineering Applications RFID, PMAX, DFTS, eNote, Fuel Cost Framework, Alarm Management 90% Expert Systems Predictive Monitoring, Optimization MBO/PdM/Risk Assessment Advanced Analysis & Process Optimization Reliability Academy Equipment, Process, Performance, Reliability Models Closed Loop Process Optimization 60% DTE - Control & Technology Framework Fossil Generation Business Unit Strategy People Making right decisions when it matters! Fleet Optimization Process Costs Asset Health, Market Value Drives Performance Excellence Fleet Optimization Process Costs, Asset Health, Reliability Operational Performance, Market Value 15%

15 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

16 Usage-based Criteria Run-hours - – 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 PI totalizer PI time-filtered conditional expressions (time-weighted and event-weighted)

17 Service Water Pump – Usage Based Pumps were off for extended period, however the PM WO still went out - 28 PM hours

18 Fuel Conditioner – Usage Based Equipment runs about 80% of total year; usage based maintenance can save 152 PM hours

19 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

20 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

21 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

22 Secondary Air Heater Plugging Air heater tube plugging causes DeltaP (green line) to increase over several months and is a trigger for maintenance

23 Boiler (convection section) Tubes - Plugging Rapid rate of change of Delta P over several days is a trigger for maintenance

24 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

25 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

26 Vibration – Conveyor Motor Shaft realignment resolves the vibration issue

27 Instrument Drift – O2 Analyzer – U2-E Based on redundant dual sensors

28 Transmitter Drift Good Not Good Boiler feedwater pump discharge pressure Based on redundant triple transmitters (PressA, PressB and PressC) XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

29 Transmitter Drift – U1 – Spray Flow Green – Delta between the transmitters Blue – Unit 1 is at about 220 MW

30 Firing Rate Control Loop – Boiler Exit O2 O2 set point: Approx. 3.2% Actual process value (green line): Varies from 1% to 5.5%

31 Firing Rate Control Loop – See Notes At purple crosshair, air (red) peaks when coal (yellow) dips causing O2 (green) to peak after 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….

32 Manual Inputs – Operator Rounds in PI Source: aspx (retrieved Jan 2009) Operator Rounds: V-PLOW status on a coal conveyor belt 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)

33 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.

34 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 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

35 Findings 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 calibrations Vibration data – combine with equipment operating conditions for better diagnostics

36 Enterprise Gateway SOA (service oriented architecture) to exchange information between the PI System and any external system via web services.

37 Questions?

38 Thank you

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