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

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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, Inc. Larry Hruby Basin Electric.

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slide1
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 BlaszkiewiczSebastien Cournoyer, CMRP DTE Energy

agenda
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

what you can expect
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

coal fired power plant
Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

basin electric power cooperative
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)
basin leland olds station los
Basin - Leland Olds Station (LOS)

Fuel:

Lignite with PRB (Powder River Basin) blending

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

($410MM capital project)

Leland Olds, Stanton, North Dakota

leland olds station los software infrastructure
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
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
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
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

Fermi – 1,100 mw

River Rouge - 527 mw

Greenwood – 785 mw

dte history of pi and maximo
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:

www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

IBM-Maximo is a key application for work management as part of the “Enterprise Business System” at DTE

Additional details at:

http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

dte details of pi usage
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

Success!

dte total fleet management
DTE - Total FleetManagement

Drives Performance Excellence

Process Costs

Asset Health

Operational Performance

Market Value

Fleet Optimization

Financials

Work Management

Market

Expert Systems

SME Status Displays

MISO,

Fuel Coat Framework

Unit Capacity Framework

SAP

Maximo

Real-time

Process Applications

WEB Portal

Applications

Distributed Control Systems (DCS)

Distributed PI Historians

dte control technology framework
DTE - Control & Technology Framework

Fleet

Optimization

Process Costs

Asset Health,

Market Value

Drives Performance Excellence

Fleet Optimization

Process Costs, Asset Health,

Reliability

Operational Performance, Market Value

Actionable

Information – KPI’s

15%

Relate all Data Sources

ProcessNet Framework

(PI, ProcessGuard, Maximo, SAP, UCF, P3M,

Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Business Intelligence

Outage & De-rate (UCF)

Maintenance & Market

25%

Advanced Analysis & Process Optimization

Reliability Academy

Equipment, Process, Performance, Reliability Models

Closed Loop Process Optimization

Expert Systems

Predictive Monitoring, Optimization

MBO/PdM/Risk Assessment

60%

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%

Process Discrete Data

Engineering Applications

RFID, PMAX, DFTS, eNote,

Fuel Cost Framework,

Alarm Management

Engineering Applications

PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data

Discrete data

Limited value

90%

Post Event Analysis

DCS, PLC & PI

Distributed Control Systems (DCS)

Distributed OSIsoft PI Historians

Large Population of Data

90%

People

Making right decisions when it matters!

Fossil Generation

Business Unit Strategy

ABB

% Complete

link operations and maintenance
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
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)
service water pump usage based
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
Fuel Conditioner – Usage Based

Equipment runs about 80% of total year; usage based maintenance can save 152 PM hours

coal conveyor usage based
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
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
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
Secondary Air Heater Plugging

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

boiler convection section tubes plugging
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

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
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 motor1
Vibration – Conveyor Motor

Shaft realignment resolves the vibration issue

instrument drift o2 analyzer u2 e
Instrument Drift – O2 Analyzer – U2-E

Based on redundant dual sensors

transmitter drift
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)

Good

Not Good

transmitter drift u1 spray flow
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
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
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
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)

Source: www.aeec.com/conveyor/Belt_Cleaners/Vplow.aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

breaker inspection sheet
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 pi1
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

findings
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

enterprise gateway
Enterprise Gateway

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

thank you
Thank you

www.osisoft.com

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