Computer-aided lean management for the energy industry

Title:

Publication Information:

New York : Pennwell Corp., 2008

Physical Description:

xiv, 380 p. : ill., maps ; 24 cm.

ISBN:

9781593701574

Subject Term:

Energy industries -- Cost control -- Data processing

Energy industries -- Labor productivity -- Data processing

Energy industries -- Management -- Data processing

Industries -- Energy conservation -- Data processing

Added Author:

Anderson, Roger N.

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Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
Searching... PSZ JB	30000010210658	HD9502.A2 C65 2008	Open Access Book	Book	Searching... Unknown
Searching... PSZ KL	33000000002305	HD9502.A2 C65 2008	Open Access Book	Book	Searching... Unknown

In this new look at energy business operations, an expert team of scientists and engineers provide a road map for transforming energy business capabilities to meet growth imperatives in an increasingly competitive global economy. Extended to the energy industry are the best practices in computational sciences and the lean management principles currently used in other leading manufacturing industries. Computer-aided lean management (CALM) methodology uses the common-sense approach of measuring the results of actions taken and using those measurements to drive greater efficiency.

In their new book, the authors examine how CALM methodology will enable future electric power smart grids with the efficiencies necessary to serve urban expansion. CALM can also serve the oil and gas industry as it deals with dwindling geological supplies and emerging renewable resource competitors. In addition, the book explores the introduction of CALM in countries, such as China, India, and Russia, that are the new business environments of the 21st century and are therefore less inhibited by the need to transition from legacy systems. Developing the business capabilities of CALM will dramatically improve the business operations of all energy companies.

Preface	p. xiii
1 Introduction to CLAM	p. 1
Mission	p. 6
Methodology	p. 8
Moon Shot	p. 11
Strategic Guide	p. 14
Better Data Management	p. 19
Structural Guide for Thought Leaders	p. 20
Tactical Guide	p. 24
Decision-Making	p. 27
Goals	p. 28
Creating a collaborative operating environment	p. 29
Improving business efficiency	p. 30
Providing decision aids	p. 30
Optimizing asset management	p. 31
Developing a business optimizer	p. 31
Implementation	p. 32
Notes	p. 38
2 History	p. 39
Integrated Definition	p. 42
GE	p. 43
Toyota	p. 44
Boeing	p. 47
Field Industries	p. 52
Notes	p. 58
3 Components	p. 59
What Keeps Control-Center Operators Up at Night	p. 59
Integrated System Model	p. 62
Plant Model	p. 66
Million-node PM	p. 68
System interdependencies	p. 70
Infrastructure interdependencies	p. 70
Business Process Modeling	p. 71
Activity-based costing	p. 76
Implementation of BPM with BAM	p. 77
Scheduling in an uncertain world	p. 78
Dynamic scheduler	p. 79
Process mapping	p. 82
Performance management	p. 84
Computational Machine Learning	p. 87
SVM	p. 99
Boosting	p. 100
RL (approximate dynamic programming)	p. 105
Real Options	p. 109
Notes	p. 112
4 Systems Engineering	p. 113
SE Components	p. 120
PLCM	p. 120
Engineering integration	p. 125
Feature-based design	p. 128
Virtual supportability	p. 129
Supportability plan	p. 130
Cost and Cycle-Time Gains	p. 131
Component Mismatches	p. 134
5 IMP/IMS	p. 139
IMP	p. 140
Methods	p. 141
Integrated process teams	p. 141
System Development Process	p. 144
Requirements Definition	p. 150
Statement of needs	p. 150
Stakeholder requirements	p. 151
Functional definition	p. 152
System requirements	p. 152
Physical definition	p. 153
R&D requirements	p. 154
Design validation	p. 154
Acceptance plan	p. 154
Value Analysis	p. 155
IMS	p. 157
6 Big Picture	p. 169
Knowledge Management	p. 170
The knowledge cube	p. 171
Digital convergence	p. 173
Configuration of the RL controller	p. 178
Putting It All Together	p. 180
7 Additional Tools	p. 183
Suitability Matrix	p. 184
Transparent Performance Metrics	p. 188
RL Controller	p. 190
Real-Options Capabilities	p. 190
Putting It All Together	p. 191
8 Oil and Gas Operations	p. 197
Exploration and Production	p. 202
Increasing productivity	p. 203
Better supply-chain management	p. 205
Production Monitoring	p. 212
ISM	p. 212
PM	p. 216
Refinery Implementation	p. 223
Better scheduling of batch runs	p. 223
IT improvements	p. 226
9 Electric Operations	p. 229
Susceptibility to Failure	p. 230
Contingency Analysis and Variance Detection	p. 238
Time-to-Failure Predictions	p. 243
Backboning Feeders	p. 248
Closing the Feedback Loop	p. 250
Plant Model for NYC	p. 252
Notes	p. 260
10 Growth	p. 261
Asset Investments	p. 262
Opportunities and Impediments	p. 266
Gas-to-Electricity	p. 267
Real options in the offshore	p. 268
Scenario analysis	p. 276
Misalignment of Incentives	p. 280
Lean LNG project	p. 281
Disconnect from lessons learned	p. 283
Wellness	p. 285
ML analysis	p. 286
Customer Satisfaction	p. 289
Call-center rules engine	p. 290
Lost enterprise value	p. 291
Blackouts are bad	p. 293
Overbuilding	p. 294
Notes	p. 299
11 Energy Future	p. 301
The Scale of the Global Energy Problem	p. 308
Alternative Energy	p. 312
Today's Electricity Economy	p. 314
Price Signals	p. 318
The energy-smart apartment house	p. 320
Plug-in vehicles	p. 326
Transportation load added to the electric grid	p. 330
Intelligent Controllers	p. 333
RL component	p. 335
Infrastructure Interdependency	p. 336
Future Electric Economy	p. 341
Notes	p. 346
Further Reading	p. 347
Index	p. 355
About the Authors	p. 377

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