The Prescriptive Promise

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1 Next Generation Asset Management Turning industrial trends and patterns from noise into action

2 Industrial Data What Is It? 1 Definition 2 Example data sources Time series Sensor devices High velocity Temperature Pressure Speed 3 Sampled and captured 4 Stored and analyzed Sampled down to the microsecond Millions streamed into storage Available for modeling, statistics and analytics 2

3 Industrial Data How does it get Big? Data generated from one of many machines at one of many plants producing a specific personal care product 3

4 Industrial Big Data The Three V s of Big Data Velocity Volume Variety PLC DCS LIMS PAC ERP HMI Operators SCADA Loop Controllers CMMS 4

5 What We re Doing about it Line-level Trend Data with Historical Storage Common Configuration One-Click Historization Enhanced Visualization Site / Plant Data w/ Model Context N-Way Distributed (One Server View) Always available Scales with Hardware Centralized Administration Embedded Ultra High Speed Writes (1MM+ writes/sec) Small footprint Intelligent collection 5

6 Why Hadoop based Historian $$$$/TB Operational $/TB Data Warehouse 1 mo 2 mo 3 mo 1 yr 5 yr 10 yr SAN Redundant Fault tolerant Fast Expensive Hadoop Shared Data Shared Compute Scalable Inexpensive (commodity Hardware) 6

7 Historian HD Cloud Enabled Proficy Historian Proficy Historian Historian HD Proficy Historian Proficy Historian 7

8 Answer Historian HD Cloud Enabled Have I seen this start up sequence across my fleet of assets in the last 10 years? Map to where data it resides and parallel process Historian HD Processor Processor Processor Processor Processor Processor Processor Processor Processor 8

9 Value Analytics Maturity Steps Insight to Action Optimize Learn Predict Analyze Monitor Time 9

10 Value Today Optimize Learn Predict Operations Predicting Problems Prognostics Diagnose Monitor Understand Causes Know Current State Time 10

11 Monitor Automotive company saves on energy costs Underlying cause? Energy consuming systems like lighting were left on when production stopped. Value to the customer? Customer achieved up to 7 times the amount of return over their investment to implement the SCADA system to tie production to supporting ancillary systems. 6 months Payback on energy cost savings 11

12 Monitor Automotive company saves on energy costs Infrastructure required Control Networks SCADA and Historians Threshold based alarming Control charting 6 months Payback on energy cost savings 12

13 Diagnose Performance monitoring in a mining concentrator Underlying cause? Poor concentrator performance as a result of changes in feed material properties, de-tuned control and inconsistent operator intervention. Value to the customer? Understanding reasons for poor performance enabled corrective actions. Continuous performance monitoring and troubleshooting helps sustain performance. $2M Productivity improvement 13

14 Diagnose Performance monitoring in a mining concentrator Infrastructure required Historical and real time data Equipment performance monitoring Process performance monitoring Data driven troubleshooting $2M Productivity improvement 14

15 Predict Single-sensor analysis or equation based models using traditional thresholds & rules Bearing Temp ALARM / TRIP Real-time, multi-variable analysis Bearing Temp ALARM / TRIP Load Ambient Normal Operation Early Stages of Damage 15

16 Applying Equipment Knowledge Combustion Turbine Example Wheel Space Model Fuel System Model Compressor Model Mechanical Model Combustion Model Lube Oil Model 16

17 Applying Equipment Knowledge Combustion Turbine Example Compressor Inlet Temperature Compressor Inlet Pressure Inlet Differential Pressure Inlet Guide Vane Position Compressor Air Flow Inlet Bleed Valve Position Gross Load Ambient Temperature Inputs Outputs Compressor Pressure Ratio Compressor Discharge Pressure Compressor Discharge Temperature Internals Calculation 17

18 Applying Failure Knowledge Combustion Turbine Example Wheel Space Model Mechanical Model Sensor Issues Bearing Failure Modes: Bearing Cooling Loss High Radial Preload High OA, 1X, 2X, 1/2X Vibration High Axial Thrust Compressor Model Sensor Issues IGV Control Icing Bellmouth Problem Inlet Bleed Heat Inlet Filter blockage Performance Pressure Ratio Temperature Ratio Fuel System Model Sensor Issues Fuel Inlet Supply Gas Inlet Valve Control Inlet Guide Vane Control Fuel Manifold Lube Oil Model Sensor Issues Filter Pluggage Temperature Control Cooling Side Fouling Vapor Pressure Lock Sensor Issues Compressor Bleed Problem Wheelspace Seal Problem Combustion Model Sensor Issues Combustor Cold Spot Combustor Hot Spot Performance Degradation Exhaust Thermocouple Sensor Issue Inlet Bleed Valve Turbine Cooling Issues High Exhaust Emission 18

19 Predict Avoided catastrophic damage to combustion turbine at O&G facility Underlying cause? Increased vibrations indicated damaged blades on combustion turbine. Value to the customer? The blade was 3-5 days from liberation. Scheduled outage avoided production loss and turbine repair costs. $30M Potential lost production 19

20 Predict Avoided catastrophic damage to combustion turbine at O&G facility Infrastructure required Similarity Based Modeling Neural Networks Rule Induction Engines Random Forest Industrial Large Data Analytics as a Service $30M Potential lost production 20

21 Process Value Process Optimization + Asset Health Advanced Process Control Optimize Learn Predict Increase yield / throughput Analyze Monitor 7 Catches 1 Catch Time 21

22 Optimize Productivity optimization in a mining smelter Underlying cause? Conservative and inconsistent operation in the drying section was constraining plant production Value to the customer? Optimized control increased dryer productivity by 10% $20M Productivity Improvement 22

23 Optimize Productivity optimization in a mining smelter Infrastructure required Equipment performance monitoring Process performance monitoring Data driven troubleshooting Model predictive control Process Simulation Industrial Big Data $20M Productivity Improvement 23

24 Value Learn Faster analytic deployment Pattern match deviations Leverage Big Data Time Industrial Big Data 24

25 Industrial Performance & Reliability Center Our experienced equipment and software engineers monitor thousands of assets 7 days/week for more than 70 sites globally in Mining, Oil & Gas, Power Generation, and Aviation. Each month: 3000 customer advisories 500 cases 200 catches Air Heater Blower Chiller System Compressor Condenser Cooling Tower Engine Fan FCC Feedwater Heater Gas Turbine Gearbox Generator Heat Exchanger HRSG Incinerator Jet Engine Level Control Valve Mill Motor Pulverizer Pump Steam Turbine Tower Transformer TRVL Screen 25

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