next generation asset management - home page | ge … · energy consuming systems like lighting ......

The Prescriptive Promise Next Generation Asset Management

Turning industrial trends and patterns from noise into action

2 The Prescriptive Promise

11/26/2013

Time series

Sensor devices

High velocity Temperature

Pressure

Speed

Sampled down to the microsecond Millions streamed into storage

Available for modeling, statistics and analytics

Definition 1 Example

data sources 2

Sampled and captured 3 Stored and analyzed 4

Industrial Data What Is It?


11/26/2013

Data generated from one of many machines at one of many plants producing a specific personal care product

Industrial Data How does it get Big?


11/26/2013

Industrial Big Data The Three V’s of Big Data

Velocity Volume Variety

PLC DCS

PAC

LIMS

ERP

CMMS

Operators

Loop

Controllers

HMI

SCADA


11/26/2013

Line-level Trend Data with Historical Storage

Common Configuration

One-Click Historization

Enhanced Visualization

Embedded Ultra High Speed Writes (1MM+ writes/sec)

Small footprint

Intelligent collection

Site / Plant Data w/ Model Context

N-Way Distributed (One Server View)

• Always available

• Scales with Hardware

Centralized Administration

What We’re Doing about it


11/26/2013

1 mo 2 mo 3 mo 1 yr 5 yr 10 yr

Why Hadoop based Historian

Operational Data Warehouse

SAN Redundant

Fault tolerant Fast

Expensive

Hadoop Shared Data

Shared Compute Scalable

Inexpensive (commodity Hardware)

$$$$/TB $/TB


11/26/2013

Historian HD Cloud Enabled

Proficy

Historian

Proficy

Historian

Proficy

Historian

Proficy

Historian

Historian HD


11/26/2013

Processor

Map to where data it resides and parallel process

An

swe

r

Processor Processor Processor

Processor

Processor Processor Processor

Processor

Have I seen this start up sequence

across my fleet of assets in the last 10 years?

Historian HD Cloud Enabled

Historian HD


11/26/2013

Analytics Maturity Steps Insight to Action

Monitor

Analyze

Predict

Optimize

Learn

Va

lue

Time


11/26/2013

Prognostics

Know Current State

Understand Causes

Operations

Predicting Problems

Today

Monitor

Diagnose

Predict

Optimize

Learn

Va

lue

Time


11/26/2013

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.

Automotive company saves on energy costs

Monitor

6

Payback on energy cost savings

months


11/26/2013

Automotive company saves on energy costs

Monitor

6

Payback on energy cost savings

months

Infrastructure required Control Networks SCADA and Historians Threshold based alarming Control charting


11/26/2013

Diagnose

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.

Performance monitoring in a mining concentrator

$2M Productivity improvement


11/26/2013

Diagnose

Infrastructure required Historical and real time data Equipment performance monitoring Process performance monitoring Data driven troubleshooting

Performance monitoring in a mining concentrator

$2M Productivity improvement


11/26/2013

Single-sensor analysis or equation based models using traditional thresholds & rules

Bearing Temp

Real-time, multi-variable analysis

Bearing Temp

Load

Ambient

Normal Operation Early Stages of Damage

ALARM / TRIP

ALARM / TRIP

Predict


11/26/2013

Applying Equipment Knowledge Combustion Turbine Example

Wheel Space Model

Fuel System Model

Combustion Model

Compressor Model

Mechanical Model

Lube Oil Model


11/26/2013

Ambient Temperature

Gross Load

Inlet Guide Vane Position

Compressor Air Flow

Compressor Discharge Temperature

Compressor Discharge Pressure

Compressor Inlet Temperature

Compressor Inlet Pressure

Inlet Differential Pressure

Inlet Bleed Valve Position

Compressor Pressure Ratio

Inputs Outputs

Internals Calculation

Applying Equipment Knowledge Combustion Turbine Example


11/26/2013

Applying Failure Knowledge Combustion Turbine Example

• Sensor Issues • Bearing Failure Modes:

• Bearing Cooling Loss

• High Radial Preload

• High OA, 1X, 2X, 1/2X Vibration

• High Axial Thrust

• Sensor Issues • IGV Control • Icing • Bellmouth Problem • Inlet Bleed Heat

• Inlet Filter blockage • Performance

• Pressure Ratio • Temperature

Ratio

• Sensor Issues • Filter Pluggage • Temperature

Control • Cooling Side

Fouling • Vapor Pressure

Lock

• Sensor Issues • Fuel Inlet Supply • Gas Inlet Valve Control

• Inlet Guide Vane Control

• Fuel Manifold

• Sensor Issues • Compressor Bleed

Problem

• Wheelspace Seal Problem

• Sensor Issues • Combustor Cold Spot • Combustor Hot Spot • Performance

Degradation • Exhaust Thermocouple

Sensor Issue • Inlet Bleed Valve • Turbine Cooling Issues • High Exhaust Emission

Wheel Space Model

Fuel System Model

Combustion Model

Compressor Model

Mechanical Model

Lube Oil Model


11/26/2013

Predict

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.

Avoided catastrophic damage to combustion turbine at O&G facility

$30M Potential lost production


11/26/2013

Predict

Infrastructure required Similarity Based Modeling Neural Networks Rule Induction Engines Random Forest Industrial Large Data Analytics as a Service

Avoided catastrophic damage to combustion turbine at O&G facility

$30M Potential lost production


11/26/2013

Process Optimization + Asset Health Advanced Process Control

Pro

cess

7 Catches 1 Catch

Increase yield / throughput

Monitor

Analyze

Predict

Optimize

Learn

Va

lue

Time


11/26/2013

Optimize

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%

Productivity optimization in a mining smelter

$20M Productivity Improvement


11/26/2013

Optimize

Infrastructure required Equipment performance monitoring Process performance monitoring Data driven troubleshooting Model predictive control Process Simulation Industrial Big Data

Productivity optimization in a mining smelter

$20M Productivity Improvement


11/26/2013

Learn V

alu

e

Time

Leverage Big Data

Industrial Big Data

Pattern match deviations Faster analytic

deployment


11/26/2013

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

next generation asset management - home page | ge … · energy consuming systems like lighting ......

Documents