Production and operations analysis
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| Format: | Buch |
| Sprache: | English |
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McGraw Hill Irwin
2001
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| Ausgabe: | 4. ed., internat. ed. |
| Schriftenreihe: | The McGraw Hill Irwin series : Operations and decision sciences
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| 250 | |a 4. ed., internat. ed. | ||
| 264 | 1 | |a Boston [u.a.] |b McGraw Hill Irwin |c 2001 | |
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Datensatz im Suchindex
| _version_ | 1819649555391578112 |
|---|---|
| adam_text | Contents
Chapter 1 Strategy and Competition 3
1.1 Manufacturing Matters 5
1.2 A Framework for Operations Strategy 7
Strategic Dimensions 7
1.3 The Classical View of Operations Strategy 9
Time Horizon 9
Focus 10
Evaluation 11
Consistency 12
1.4 Competing in the Global Marketplace 13
Problems for Sections 1 4 16
Snapshot Application: Read Rite Wins with International
Strategic Alliance 17
1.5 Strategic Initiatives: Reengineering the Business Process 18
1.6 Strategic Initiatives: Just in Time 21
1.7 Strategic Initiatives: Time Based Competition 23
1.8 Strategic Initiatives: Competing on Quality 24
Problems for Sections 5 8 26
1.9 Matching Process and Product Life Cycles 27
The Product Life Cycle 27
The Process Life Cycle 28
The Product Process Matrix 30
Problems for Section 9 31
1.10 Learning and Experience Curves 32
Learning Curves 32
Experience Curves 35
Learning and Experience Curves and Manufacturing
Strategy 36
Problems for Section 10 37
1.11 Capacity Growth Planning: A Long Term Strategic Problem 38
Economies of Scale and Economies of Scope 39
Make or Buy: A Prototype Capacity Expansion Problem 40
Dynamic Capacity Expansion Policy 41
Issues in Plant Location 45
Problems for Section 11 47
1.12 Summary 48
Additional Problems for Chapter 1 49
Appendix 1 A Present Worth Calculations 51
Bibliography 52
xxiii
Contents in Brief
Chapter 1 Strategy and Competition 3
Appendix 1 A Present Worth Calculations 51
Chapter 2 Forecasting 55
Appendix 2 A Forecast Errors for Moving Averages and Exponential
Smoothing 106
Appendix 2 B Derivation of the Equations for the Slope and Inter¬
cept for Regression Analysis 108
Appendix 2 C Glossary of Notation for Chapter 2 109
Chapter 3 Aggregate Planning 113
Appendix 3 A Glossary of Notation for Chapter 3 157
Supplement 1 Linear Programming 161
Chapter 4 Inventory Control Subject to Known Demand 193
Appendix 4 A Mathematical Derivations for Multiproduct Con¬
strained EOQ Systems 239
Appendix 4 B Glossary of Notation for Chapter 4 240
Chapter 5 Inventory Control Subject to Uncertain Demand 243
Appendix 5—A Notational Conventions
and Probability Review 293
Appendix 5 B Additional Results and Extensions for the
Newsboy Model 294
Appendix 5 C Derivation of the Optimal (Q, R) Policy 296
Appendix 5 D Probability Distributions for Inventory
Management 297
Appendix 5 E Glossary of Notation for Chapter 5 300
Chapter 6 Supply Chain Management 305
Chapter 7 Push and Pull Production Control Systems: MRP and JIT 355
Appendix 7—A Optimal Lot Sizing for Time Varying Demand 406
Appendix 7 B Glossary of Notation for Chapter 7 410
Chapter 8 Operations Scheduling 413
Supplement 2 Queuing Theory 473
Chapter 9 Project Scheduling 503
Appendix 9 A Glossary of Notation for Chapter 9 554
Chapter 10 Facilities Layout and Location 557
Appendix 10 A Finding Centroids 626
Appendix 10—B Computing Contour Lines 628
Chapter 11 Quality and Assurance 635
Appendix 11—A Approximating Distributions 706
Appendix 11 B Glossary of Notation for Chapter 11 on Quality and
Assurance 708
Chapter 12 Reliability and Maintainability 713
Appendix 12—A Glossary of Notation on Reliability and
Maintainability 767
Appendix: Tables 771
Index 789
xxi
Chapter 2 Forecasting 55
2.1 The Time Horizon in Forecasting 56
2.2 Characteristics of Forecasts 57
2.3 Subjective Forecasting Methods 57
2.4 Objective Forecasting Methods 58
Causal Models 59
Time Series Methods 59
Snapshot Application: Advanced Forecasting Inc. Serves
the Semiconductor Industry 60
Problems for Sections 1 4 61
2.5 Notation Conventions 62
2.6 Evaluating Forecasts 62
Problems for Section 6 65
2.7 Methods for Forecasting Stationary Series 66
Moving Averages 66
Problems on Moving Averages 69
Exponential Smoothing 69
Multiple Step Ahead Forecasts 74
Comparison of Exponential Smoothing and Moving
Averages 74
Problems for Section 7 75
Snapshot Application: Sport Obermeyer Slashes Costs with Improved
Forecasting 76
2.8 Trend Based Methods 77
Regression Analysis 77
Problems for Section 8 79
Double Exponential Smoothing Using Holt s
Method 79
More Problems for Section 8 81
2.9 Methods for Seasonal Series 81
Seasonal Factors for Stationary Series 81
Seasonal Decomposition Using Moving Averages 83
Problems for Section 9 87
Winters s Method for Seasonal Problems 87
More Problems for Section 9 92
2.10 Pi actical Considerations 92
Mode] Identification and Monitoring 92
Simple versus Complex Time Series Methods 93
2.11 Overview of Advanced Topics in Forecasting 94
Box Jenkins Methods 94
Simulation as a Forecasting Tool 95
Forecasting Demand in the Presence of Lost Sales 96
2.12 Linking Forecasting and Inventory Management 98
2.13 Historical Notes and Additional Topics 99
2.14 Summary 100
Additional Problems on Forecasting 101
Appendix 2 A Forecast Errors for Moving Averages and
Exponential Smoothing 106
Appendix 2 B Derivation of the Equations for the Slope and Intercept
for Regression Analysis 108
Appendix 2 C Glossary of Notation for Chapter 2 109
Bibliography 110
Chapter 3 Aggregate Planning 113
3.1 Aggregate Units of Production 114
3.2 Overview of the Aggregate Planning Problem 116
3.3 Costs in Aggregate Planning 118
Problems for Sections 1 3 120
3.4 A Prototype Problem 121
Evaluation of a Chase Strategy (Zero Inventory Plan) 123
Evaluation of the Constant Workforce Plan 125
Mixed Strategies and Additional Constraints 126
Problems for Section 4 127
3.5 Solution of Aggregate Planning problems by Linear
Programming 129
Cost Parameters and Given Information 130
Problem Variables 130
Problem Constraints 131
Rounding the Variables 132
Extensions 133
Other Solution Methods 135
3.6 Solving Aggregate Planning Problems by Linear Programming:
An Example 136
Problems for Sections 5 and 6 138
3.7 The Linear Decision Rule 141
3.8 Modeling Management Behavior 142
Problems for Sections 7 and 8 144
3.9 Disaggregating Aggregate Plans 144
Snapshot Application: Welch s Uses Aggregate Planning for Production
Scheduling 146
Problems for Section 9 147
3.10 Production Planning on a Global Scale 147
3.11 Practical Considerations 149
3.12 Historical Notes 150
3.13 Summary 150
Additional Problems on Aggregate Planning 152
Appendix 3 A Glossary of Notation for Chapter 3 157
Bibliography 157
Supplement 1 Linear Programming 161
1 Introduction 161
2 A Prototype Linear Programming Problem 162
3 Statement of the General Problem 164
Definitions of Commonly Used Terms 164
Features of Linear Programs 165
4 Solving Linear Programming Problems Graphically 167
Graphing Linear Inequalities 167
Graphing the Feasible Region 169
Finding the Optimal Solution 170
Identifying the Optimal Solution Directly by Graphical
Means 172
5 The Simplex Method: An Overview 173
6 Solving Linear Programming Problems with Excel 174
Entering Large Problems Efficiently 177
7 Interpreting the Sensitivity Report 179
Shadow Prices 179
Objective Function Coefficients and Right Hand Sides 181
Adding a New Variable 182
Using Sensitivity Analysis 182
8 Recognizing Special Problems 184
Unbounded Solutions 185
Empty Feasible Region 186
Degeneracy 187
Multiple Optimal Solutions 188
Redundant Constraints 189
9 The Application of Linear Programming to Production
and Operations Analysi s 190
Bibliography 191
Chapter 4 Inventory Control Subject to Known Demand 193
4.1 Types of Inventories 194
4.2 Motivation for Holding Inventories 195
4.3 Characteristics of Inventory Systems 196
4.4 Relevant Costs 197
Holding Cost 197
Order Cost 199
Penalty Cost 200
Problems for Sections 1 4 201
4.5 The EOQ Model 203
The Basic Model 203
Inclusion of Order Lead Time 206
Sensitivity 208
EOQ and JIT 209
Problems for Section 5 210
4.(i Extension to a Finite Production Rale 211
Problems tor Section 6 213
4.7 Quantity Discount Models 214
Optimal Policy for All Units Discount Schedule 2 16
Summary of the Solution Technique for All Units Discounts 217
Incremental Quantity Discounts 218
Summary of the Solution Technique for Incremental Discounts 219
Other Discount Schedules 219
Problems for Section 7 220
4.8 Resource Constrained Multiple Product Systems 221
Problems for Section 8 225
4.9 EOQ Models for Production Planning 226
Problems for Section 9 230
4.10 Software for Inventory Control 231
Snapshot Application: Mervyn s Recognized for State of the Art
Inventory Control System 232
4.11 Historical Notes and Additional Topics 233
4.12 Summary 233
Additional Problems on Deterministic Inventory Models 234
Appendix 4 A Mathematical Derivations for Multiproduct
Constrained EOQ Systems 239
Appendix 4 B Glossary of Notation for Chapter 4 240
Bibliography 241
Chapter 5 Inventory Control Subject to Uncertain Demand 243
Overview of Models Treated in This Chapter 244
5.1 The Nature of Randomness 245
5.2 Optimization Criterion 248
Problems for Sections 1 and 2 248
5.3 The Newsboy Model 250
Notation 250
Development of the Cost Function 250
Determining the Optimal Policy 251
Optimal Policy for Discrete Demand 253
Extension to Include Starting Inventory 254
Extension to Multiple Planning Periods 255
Problems for Section 3 256
5.4 Lot Size Reorder Point Systems 259
Describing Demand 259
Decision Variables 259
Derivation of the Expected Cost Function 260
The Cost Function 262
5.5 Service Levels in (Q, R) Systems 264
Type 1 Service 265
Type 2 Service 265
Optimal (Q, R) Policies Subject to Type 2 Constraint 266
Imputed Shortage Cost 268
Scaling of Lead Time Demand 268
Estimating Sigma when Inventory Control and Forecasting
Are Linked 269
*Lead Time Variability 270
Calculations in Excel 270
Problems for Sections 4 and 5 271
5.6 Additional Discussion of Periodic Review Systems 273
0, S) Policies 273
?Service Levels in Periodic Review Systems 273
Problems for Section 6 274
5.7 Multiproduct Systems 275
ABC Analysis 275
Exchange Curves 277
Problems for Section 7 280
*5.8 Overview of Advanced Topics 281
Multiechelon Systems 281
Perishable Inventory Problems 283
5.9 Electronic Data Interchange 283
Snapshot Application: Triad s Inventory Systems Meet
Markets Needs 284
5.10 Historical Notes and Additional Readings 285
5.11 Summary 286
Additional Problems on Stochastic Inventory Models 287
Appendix 5 A Notational Conventions and
Probability Review 293
Appendix 5 B Additional Results and Extensions
for the Newsboy Model 294
Appendix 5 C Derivation of the Optimal (Q, R) Policy 296
Appendix 5 D Probability Distributions
for Inventory Management 297
Appendix 5 E Glossary of Notation for Chapter 5 300
Bibliography 301
Chapter 6 Supply Chain Management 305
The Supply Chain as a Strategic Weapon 306
Snapshot Application: Wal Mart Wins with Solid Supply Chain
Management 307
6.1 The Transportation Problem 308
The Greedy Heuristic 311
6.2 Solving Transportation Problems with Linear Programming 313
6.3 Generalizations of the Transportation Problem 315
Infeasible Routes 315
Unbalanced Problems 315
6.4 More General Network Formulations 316
Problems for Sections 1 4 319
Snapshot Application: IBM Streamlines Its Supply Chain for Spare Parts
Using Sophisticated Mathematical Models 320
6.5 Distribution Resource Planning 322
Problems for Section 5 324
6.6 Determining Delivery Routes in Supply Chains 325
Practical Issues in Vehicle Scheduling 329
Snapshot Application: Air Products Saves Big with Routing
and Scheduling Optimizer 330
Problems for Section 6 331
6.7 Designing Products for Supply Chain Efficiency 332
Postponement in Supply Chains 333
Additional Issues in Supply Chain Design 334
Snapshot Application: Dell Computer Designs the Ultimate
Supply Chain 335
Problems for Section 7 336
6.8 The Role of Information in the Supply Chain 336
The Bullwhip Effect 337
Electronic Commerce 340
Electronic Data Interchange 341
Web Based Transactions Systems 342
Problems for Section 8 343
6.9 Multilevel Distribution Systems 343
Problems for Section 9 346
6.10 Designing the Supply Chain in a Global Environment 346
Supply Chain Management in a Global Environment 349
Snapshot Application: Digital Equipment Corporation Uses
Mathematical Modeling to Plan Its Global Supply Chain 350
Problems for Section 10 351
6.11 Summary 351
Bibliography 352
Chapter 7 Push and Pull Production Control Systems: MRP and JIT 355
MRP Basics 356
JIT Basics 358
7.1 The Explosion Calculus 359
Problems for Section 1 364
7.2 Alternative Lot Sizing Schemes 366
EOQ Lot Sizing 367
The Silver Meal Heuristic 368
Least Unit Cost 369
Part Period Balancing 370
Problems for Section 2 371
7.3 Incorporating Lot Sizing Algorithms into the Explosion
Calculus 373
Problems for Section 3 375
7.4 Lot Sizing with Capacity Constraints 375
Problems for Section 4 379
7.5 Shortcomings of MRP 380
Uncertainty 380
Capacity Planning 381
Rolling Horizons and System Nervousness 383
Additional Considerations 384
Snapshot Application: Raymond Corporation Builds World Class
Manufacturing with MRP II 386
Problems for Section 5 387
7.6 JIT Fundamentals 387
The Mechanics of Kanban 388
Single Minute Exchange of Dies 389
Advantages and Disadvantages of the Just in Time
Philosophy 390
Implementation of JIT in the United States 393
Problems for Section 6 395
7.7 A Comparison of MRP and JIT 395
7.8 MRP Software: A Big Business 397
7.9 Historical Notes 399
7.10 Summary 400
Additional Problems for Chapter 7 401
Appendix 7 A Optimal Lot Sizing for Time Varying Demand 406
Appendix 7 B Glossary of Notation for Chapter 7 410
Bibliography 410
Chapter 8 Operations Scheduling 413
8.1 Production Scheduling and the Hierarchy of Production
Decisions 414
8.2 Important Characteristics of Job Shop Scheduling Problems 416
Objectives of Job Shop Management 417
8.3 Job Shop Scheduling Terminology 418
8.4 A Comparison of Specific Sequencing Rules 419
First Come, First Served 420
Shortest Processing Time 421
Earliest Due Date 421
Critical Ratio Scheduling 421
8.5 Objectives in Job Shop Management: An Example 423
Problems for Sections 1 5 424
8.6 An Introduction to Sequencing Theory lor a Single Machine 425
Shortest Processing Time Scheduling 426
Earliest Due Date Scheduling 427
Minimizing the Number of Tardy Jobs 427
Precedence Constraints: Lawler s Algorithm 428
Problems for Section 6 431
8.7 Sequencing Algorithms for Multiple Machines 432
Scheduling n Jobs on Two Machines 434
Extension to Three Machines 435
The Two Job Flow Shop Problem 437
Problems for Section 7 440
8.8 Stochastic Scheduling: Static Analysis 442
Single Machine 442
Multiple Machines 443
The Two Machine Flow Shop Case 445
Problems for Section 8 446
8.9 Stochastic Scheduling: Dynamic Analysis 447
Selection Disciplines Independent of Job
Processing Times 449
Selection Disciplines Dependent on Job Processing Times 450
The cfi Rule 452
Problems for Section 9 452
8.10 Assembly Line Balancing 453
Problems for Section 10 458
Snapshot Application: Manufacturing Divisions Realize Savings
with Scheduling Software 459
8.11 Simulation: A Valuable Scheduling Tool 460
8.12 Post MRP Production Scheduling Software 461
8.13 Historical Notes 462
8.14 Summary 463
Additional Problems on Scheduling 464
Bibliography 470
Supplement 2 Queuing Theory 473
1 Introduction 473
2 Structural Aspects of Queuing Models 474
3 Notation 475
4 Little s Formula 476
5 The Exponential and Poisson Distributions in Queuing 476
Aside All
6 Birth and Death Analysis for the M/M/l Queue 478
7 Calculation of the Expected System Measures
for the M/M/l Queue 481
8 The Waiting Time Distribution 482
9 Solution of the General Case 484
10 Multiple Servers in Parallel: The M/M/c Queue 486
11 The M/M/l Queue with a Finite Capacity 490
12 Results for Nonexponential Service Distributions 493
13 The M/G/oo Queue 495
14 Optimization of Queuing Systems 496
Typical Service System Design Problems 497
Modeling Framework 497
15 Simulation of Queuing Systems 499
Bibliography 501
Chapter 9 Project Scheduling 503
9.1 Representing a Project as a Network 504
9.2 Critical Path Analysis 507
Finding the Critical Path 510
Problems for Sections 1 and 2 514
9.3 Time Costing Methods 516
Problems for Section 3 521
9.4 Solving Critical Path Problems with Linear Programming 522
Linear Programming Formulation of the Cost Time
Problem 524
Problems for Section 4 526
9.5 PERT: Project Evaluation and Review Technique 527
Path Independence 532
Problems for Section 5 536
9.6 Resource Considerations 537
Resource Constraints for Single Project Scheduling 537
Resource Constraints for Multiproject Scheduling 539
Resource Loading Profiles 540
Problems for Section 6 542
9.7 Organizational Issues in Project Management 544
9.8 Historical Notes 545
9.9 Project Management Software for the PC 546
Snapshot Application: Project Management Helps United Stay
on Schedule 548
Snapshot Application: Thomas Brothers Plans Staffing with Project
Management Software 548
9.10 Summary 548
Snapshot Application: Florida Power and Light Takes Project
Management Seriously 549
Additional Problems on Project Scheduling 550
Appendix 9 A Glossary of Notation for Chapter 9 554
Bibliography 554
Chapter 10 Facilities Layout and Location 557
10.1 The Facilities Layout Problem 558
10.2 Patterns of Flow 559
Activity Relationship Chart 560
From To Chart 561
10.3 Types of Layouts 564
Fixed Position Layouts 564
Product Layouts 565
Process Layouts 565
Layouts Based on Group Technology 565
Problems for Sections 1 3 568
10.4 A Prototype Layout Problem and the Assignment Model 569
The Assignment Algorithm 570
Problems for Section 4 573
* 10.5 More Advanced Mathematical Programming
Formulations 574
Problem for Section 5 575
10.6 Computerized Layout Techniques 575
CRAFT 576
COFAD 581
ALDEP 581
CORELAP 582
PLANET 583
Computerized Methods versus Human Planners 584
Dynamic Plant Layouts 584
Other Computer Methods 585
Problems for Section 6 586
10.7 Flexible Manufacturing Systems 589
Advantages of Flexible Manufacturing Systems 590
Disadvantages of Flexible Manufacturing Systems 591
Decision Making and Modeling of the FMS 592
The Future of FMS 596
Problems for Section 7 597
Snapshot Application: Kraft Foods Uses Optimization and Simulation
to Determine Best Layout 598
10.8 Locating New Facilities 598
Measures of Distance 599
Problems for Section 8 600
10.9 The Single Facility Rectilinear Distance Location
Problem 600
Contour Lines 604
Minimax Problems 604
Problems for Section 9 607
10.10 Euclidean Distance Problems 609
The Gravity Problem 609
The Straight Line Distance Problem 610
Problems for Section 10 612
10.11 Other Location Models 612
Locating Multiple Facilities 613
Further Extensions 614
Problems for Section 11 617
10.12 Historical Notes 618
10.13 Summary 618
Additional Problems on Layout and Location 620
Spreadsheet Problems for Chapter 10 625
Appendix 10 A Finding Centroids 626
Appendix 10 B Computing Contour Lines 628
Bibliography 631
Chapter 11 Quality and Assurance 635
Overview of This Chapter 637
11.1 Statistical Basis of Control Charts 638
Problems for Section 1 640
11.2 Control Charts for Variables: The X and R Charts 642
X Charts 645
Relationship to Classical Statistics 646
R Charts 647
Problems for Section 2 649
11.3 Control Charts for Attributes: The p Chart 650
p Charts for Varying Subgroup Sizes 653
Problems for Section 3 654
11.4 Thee Chart 656
Problems for Section 4 658
11.5 Classical Statistical Methods and Control Charts 659
Problem for Section 5 660
* 11.6 Economic Design of X Charts 660
Problems for Section 6 667
11.7 Overview of Acceptance Sampling 668
11.8 Notation 670
11.9 Single Sampling for Attributes 670
Derivation of the OC Curve 672
Problems for Section 9 674
* 11.10 Double Sampling Plans for Attributes 675
Problems for Section 10 677
11.11 Sequential Sampling Plans 678
Problems for Section 11 682
11.12 Average Outgoing Quality 682
Problems for Section 12 684
Snapshot Application: Motorola Leads the Way with Six Sigma
Quality Programs 685
11.13 Total Quality Management 686
Definitions 686
Listening to the Customer 686
Competition Based on Quality 688
Organizing for Quality 689
Benchmarking Quality 690
The Deming Prize and the Baldrige Award 691
ISO 9000 693
Quality: The Bottom Line 694
11.14 Designing Quality into the Product 695
Design, Manufacturing, and Quality 697
11.15 Historical Notes 700
11.16 Summary 700
Additional Problems on Quality and Assurance 702
Appendix 11 A Approximating Distributions 706
Appendix 11 B Glossary of Notation for Chapter 11 on Quality
and Assurance 708
Bibliography 710
Chapter 12 Reliability and Maintainability 713
Overview of This Chapter 715
12.1 Reliability of a Single Component 715
Introduction to Reliability Concepts 715
Preliminary Notation and Definitions 717
The Exponential Failure Law 720
Problems for Section 1 723
12.2 Increasing and Decreasing Failure Rates 725
Problems for Section 2 727
12.3 The Poisson Process in Reliability Modeling 728
Series Systems Subject to Purely Random Failures 732
Problems for Section 3 732
12.4 Failures of Complex Equipment 733
Components in Series 733
Components in Parallel 734
Expected Value Calculations 735
K Out of N Systems 736
Problems for Section 4 737
12.5 Introduction to Maintenance Models 738
12.6 Deterministic Age Replacement Strategies 740
The Optimal Policy in the Basic Case 740
A General Age Replacement Model 742
Problems for Section 6 746
12.7 Planned Replacement under Uncertainty 747
Planned Replacement for a Single Item 747
Block Replacement for a Group of Items 750
Problems for Section 7 753
*12.8 Analysis of Warranty Policies 755
The Free Replacement Warranty 756
The Pro Rata Warranty 757
Extensions and Criticisms 759
Problems for Section 8 760
12.9 Software Reliability 761
Snapshot Application: Reliability Centered Maintenance Improves
Operations at Three Mile Island Nuclear Plant 762
12.10 Historical Notes 762
12.11 Summary 763
Additional Problems on Reliability and Maintainability 764
Appendix 12 A Glossary of Notation on Reliability
and Maintainability 767
Bibliography 768
Appendix Tables 771
Index 789
|
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| dewey-full | 658.5 |
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| dewey-ones | 658 - General management |
| dewey-raw | 658.5 |
| dewey-search | 658.5 |
| dewey-sort | 3658.5 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| edition | 4. ed., internat. ed. |
| format | Book |
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| genre | 1\p (DE-588)4151278-9 Einführung gnd-content 2\p (DE-588)4123623-3 Lehrbuch gnd-content |
| genre_facet | Einführung Lehrbuch |
| id | DE-604.BV017195328 |
| illustrated | Illustrated |
| indexdate | 2024-12-23T16:18:02Z |
| institution | BVB |
| isbn | 0072312653 007118127X |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-010362528 |
| oclc_num | 44634391 |
| open_access_boolean | |
| owner | DE-703 |
| owner_facet | DE-703 |
| physical | XXXVI, 810 S. Ill., graph. Darst. 1 CD-ROM (12 cm) |
| publishDate | 2001 |
| publishDateSearch | 2001 |
| publishDateSort | 2001 |
| publisher | McGraw Hill Irwin |
| record_format | marc |
| series2 | The McGraw Hill Irwin series : Operations and decision sciences |
| spellingShingle | Nahmias, Steven Production and operations analysis Administración de la producción Productiemanagement gtt Production management Operations Research (DE-588)4043586-6 gnd Management (DE-588)4037278-9 gnd Ablaufplanung (DE-588)4122751-7 gnd Produktmanagement (DE-588)4125960-9 gnd Produktionswirtschaft (DE-588)4123986-6 gnd Produktion (DE-588)4047347-8 gnd Produktionstheorie (DE-588)4121520-5 gnd |
| subject_GND | (DE-588)4043586-6 (DE-588)4037278-9 (DE-588)4122751-7 (DE-588)4125960-9 (DE-588)4123986-6 (DE-588)4047347-8 (DE-588)4121520-5 (DE-588)4151278-9 (DE-588)4123623-3 |
| title | Production and operations analysis |
| title_auth | Production and operations analysis |
| title_exact_search | Production and operations analysis |
| title_full | Production and operations analysis Steven Nahmias |
| title_fullStr | Production and operations analysis Steven Nahmias |
| title_full_unstemmed | Production and operations analysis Steven Nahmias |
| title_short | Production and operations analysis |
| title_sort | production and operations analysis |
| topic | Administración de la producción Productiemanagement gtt Production management Operations Research (DE-588)4043586-6 gnd Management (DE-588)4037278-9 gnd Ablaufplanung (DE-588)4122751-7 gnd Produktmanagement (DE-588)4125960-9 gnd Produktionswirtschaft (DE-588)4123986-6 gnd Produktion (DE-588)4047347-8 gnd Produktionstheorie (DE-588)4121520-5 gnd |
| topic_facet | Administración de la producción Productiemanagement Production management Operations Research Management Ablaufplanung Produktmanagement Produktionswirtschaft Produktion Produktionstheorie Einführung Lehrbuch |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010362528&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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