Advanced Planning and Scheduling in Manufacturing and Supply Chains (eBook)

Yuri Mauergauz (Autor)

eBook Download: PDF

2016 | 1st ed. 2016
XXIII, 570 Seiten
Springer International Publishing (Verlag)
978-3-319-27523-9 (ISBN)

Infos

This book is a guide to modern production planning methods based on new scientific achievements and various practical planning rules of thumb. Several numerical examples illustrate most of the calculation methods, while the text includes a set of programs for calculating production schedules and an example of a cloud-based enterprise resource planning (ERP) system. Despite the relatively large number of books dedicated to this topic, Advanced Planning and Scheduling is the first book of its kind to feature such a wide range of information in a single work, a fact that inspired the author to write this book and publish an English translation.

This work consists of two parts, with the first part addressing the design of reference and mathematical models, bottleneck models and multi-criteria models and presenting various sample models. It describes demand-forecasting methods and also includes considerations for aggregating forecasts. Lastly, it provides reference information on methods for data stocking and sorting. The second part of the book analyzes various stock planning models and the rules of safety stock calculation, while also considering the stock traffic dynamics in supply chains. Various batch computation methods are described in detail, while production planning is considered on several levels, including supply planning for customers, master planning, and production scheduling. This book can be used as a reference and manual for current planning methods. It is aimed at production planning department managers, company information system specialists, as well as scientists and PhD students conducting research in production planning. It will also be a valuable resource for students at universities of applied sciences.

Inhalt

Preface to the English Edition 6
Preface to the Russian Edition 8
Annotation 12
Advanced Planning and Scheduling (APandS) in Production and Supply Chains 12
Contents 14
About the Author 24
Part I: Modeling 25
1: Reference Model 26
1.1 Modelling of Business Process 26
1.2 Concept of Reference Model 28
1.2.1 Reference Models in Supply Chains 29
1.2.2 Reference Modelling Methodology 30
1.3 Production Description 32
1.3.1 Basic Types of Production 32
1.3.2 Production Scale and Strategy 36
1.4 Advanced Planning in IT Systems 38
1.4.1 Planning in IT Systems 38
1.4.2 Popularity and Effects of Advanced Planning 42
1.5 IT System Interaction Standards 44
1.6 Quality Parameters in Supply Chains 47
1.6.1 Markets and Their Main Properties 48
1.6.2 Quality Parameters and Different Supply Chain Levels 49
1.6.3 Balanced Scorecard 51
1.7 Utility of Quality Parameters 54
1.7.1 Concept of Utility 54
1.7.2 Typical Utility Functions 57
1.7.3 Utility Functions in Business Process Quality Evaluations 60
References 65
2: Mathematical Models 66
2.1 Simplest Planning Models 66
2.1.1 Classical Supply Management Model 66
2.1.2 Continuous Linear Optimization Model 68
2.2 Correlations Between Mathematical and Reference Models 75
2.2.1 Main Criteria and Constraints 75
2.2.2 Standard Classification of Planning Optimization Models 76
2.2.3 Production Scale and Plan Hierarchy in Classification 78
2.3 Priority Rules 81
2.3.1 Simple Rules 81
2.3.2 Some Useful Theorems 85
2.3.3 Combined Priority Rules 85
2.4 Production Intensity and Utility of Orders 87
2.4.1 Production Intensity 88
2.4.2 Dynamic Utility Function of Orders 93
2.5 More Complex Models of Linear Optimization 97
2.5.1 Integer Linear Optimization Model 97
2.5.2 Integer Linear Optimization Models with Binary Variables 98
2.6 Fixed Job Sequence Models 101
2.6.1 Branch-and-Bound Method with Minimum Cumulative Tardiness Tw 102
2.6.2 Branch-and-Bound Method with Maximum Average Utility 104
References 110
3: Production Bottlenecks Models 111
3.1 Theory of Constraints 111
3.1.1 Fundamentals of Theory of Constraints 111
3.1.2 Bottleneck Operation Planning 114
3.1.3 Planning for Buffers, Ropes, and Non-bottleneck Machines 117
3.1.4 Simple Example of Theory of Constraints in Application 119
3.1.5 Theory of Constraints in Process Manufacturing 120
3.1.6 Review of TOC Applications 122
3.2 Theory of Logistic Operating Curves 123
3.2.1 Production (Logistics) Variables 123
3.2.2 Some Notions Used in Queuing Theory 127
3.2.3 Plotting Logistic Operating Curves 129
3.2.4 Main Properties of Logistic Curves 132
3.3 Application of Logistic Operating Curves 132
3.3.1 Logistic Positioning 132
3.3.2 Bottleneck Analysis and Improvements 133
3.3.3 Evaluation of Overall Production Performance 134
3.4 Optimal Lot Sizing for Production Bottlenecks 138
3.4.1 Lot Sizing Heuristic 138
3.4.2 Analysis of Heuristic Solutions 141
3.5 Hierarchical Approach to Machinery Load Management 144
3.5.1 Principles of Workload Control Concept 145
3.5.2 Example of Application of Controlled Load Approach 146
References 148
4: Multi-criteria Models and Decision-Making 149
4.1 Basic Concepts in Multi-criteria Optimization Theory 149
4.1.1 Definition of Multi-criteria Optimization Problems 149
4.1.2 Pareto Optimality 152
4.1.3 Main Methods of Solving Multi-criteria Planning Problems 154
4.1.4 Analytical Method of Constructing a Trade-Off Curve 158
4.2 Optimized Multi-criteria Lot Sizing 160
4.2.1 Lot Sizing Based on Costs and Equipment 160
4.2.2 Analytical Lot Sizing with Two Criteria: Setup Time and Cost 162
4.3 Example of Multi-scheduling Problem 165
4.3.1 Special epsi-Neighbourhood of Efficiency Points 166
4.3.2 Solving Algorithm 167
4.4 Methods of Decision-Making Theory in Planning Problems 172
4.4.1 Some Information from the Decision Making Theory 172
4.4.2 Example of the Planning Problem Requiring Decision Making 175
4.4.3 Decision-Making Based on the Guaranteed Result Principle 178
4.4.4 Optimistic Decision-Making 179
4.5 Applications of Complex Decision-Making Methods 180
4.5.1 Hurwitz Principle 180
4.5.2 Savage Principle 181
4.5.3 Shifted Ideal Method 182
References 184
5: Data for Planning 185
5.1 Composition of the Data Used for Planning 185
5.1.1 Archives of Design-Engineering Documentation and Orders 185
5.1.2 Reference Data and Standards 189
5.1.3 Databases of Transactional IT Systems 191
5.1.4 Decision Support Databases 192
5.1.5 Knowledge Bases 193
5.2 Data Storage and Management 196
5.2.1 Relational Databases 196
5.2.2 Concept of Object-Oriented Databases 198
5.2.3 Database Management Systems 199
5.2.4 Tiered Data Storage 200
5.2.5 Distributed Databases 201
5.2.6 Service Oriented Architecture of IT Systems 203
5.2.7 On-Line Analytical Processing 205
5.3 Information Exchange 208
5.3.1 Internal Data Communication 208
5.3.2 Data Transfer Between Enterprises 209
5.3.3 Information Exchange in Different Types of Cooperation 211
5.3.4 Information Exchange Automation 213
5.3.5 Use of Cloud Environment 216
References 218
6: Demand Forecasting 220
6.1 Demand Modelling Based on Time Series Analysis 220
6.2 Main Methods of Forecasting 222
6.2.1 Moving Average Method 222
6.2.2 Exponentially Smoothing Forecasting 224
6.2.3 Trend Adjusted Exponential Smoothing 225
6.2.4 Trend and Seasonality Adjusted Exponential Smoothing 227
6.3 Demand Aggregation 229
6.4 Aggregated Demand Forecasting 231
References 235
7: Examples of Advanced Planning Models 236
7.1 Joint Operation Model of APS System and ERP System from SAP R/3 236
7.1.1 Main Business Process Attributes in Various Industries 237
7.1.2 Software Modules for Planning Solutions 239
7.1.3 Planning Modules Interaction 240
7.2 Reference Model of Production Planning for Instrument Engineering Plant 242
7.2.1 Initial Planning Status Analysis 242
7.2.2 Decision Support Database 244
7.3 Mathematical Model in Chemical Industry 247
7.3.1 Analytical Structure of Model 247
7.3.2 Objective Function and Constraints 250
7.3.3 Some Results of Modelling 254
7.4 Rapid Supply Chain Reference Model in Clothing Industry 255
7.5 Schedule Model for a Machine Shop 258
7.5.1 Schedule Model with Specified Processing Stages 259
7.5.2 Optimality Criteria and Constraints 260
7.6 Multi-stage Logistics Chain Model 262
7.6.1 Some Notions in Logistics Chain Modelling 262
7.6.2 Dynamic Logistics Chain Optimization Model in Multi-stage Production 262
References 265
Part II: Planning Processes 266
8: Single-Echelon Inventory Planning 267
8.1 Inventory Types and Parameters 267
8.2 Inventory Management Models 268
8.2.1 Model with Fixed Quantity of Order 269
8.2.2 Model with Fixed Reorder Cycle 270
8.2.3 Two-Tier Inventory Management Model 271
8.2.4 Benchmarking of Inventory Management Models 273
8.2.5 Kanban Inventory Management Model 274
8.3 Inventory Management Model Under Uncertainty 276
8.3.1 Customer Service Level 276
8.3.2 Shortages Permitted Inventory Management Model 277
8.3.3 Demand Distribution Functions 278
8.3.4 Newsvendor Problem 280
8.4 Inventory Management Using Logistic Operating Curves 282
8.4.1 Storage Curves and Their Applications 282
8.4.2 Finished Product Inventory Sizing to Optimize the Overall Production Performance 284
8.5 Safety Stock Sizing 285
8.5.1 Calculation of Safety Stock with Random Demand 286
8.5.2 Sizing of Safety Stock with Two Random Variables 287
8.5.3 Sizing of Safety Stock with Three Random Variables 289
References 290
9: Supply Chain Inventory Dynamics 292
9.1 Stock Distribution Planning in the Chain 292
9.1.1 DRP Technique 292
9.1.2 Regular Maintenance of DRP Tables 295
9.1.3 Parallel Multi-product Planning 297
9.1.4 Inventory Dynamics at Long Lead Cycles 298
9.2 Supply Chain Fluctuations 300
9.2.1 Bullwhip Effect 300
9.2.2 Bullwhip Effect Factors 303
9.2.3 Methods of Reducing Supply Chain Fluctuations 305
9.3 Application of Logistics Operating Curves in Supply Chains 308
9.4 Inventory Echelon Accounting 311
9.4.1 Inventory Echeloning 311
9.4.2 Sequential Supply Chain 312
9.4.3 Supply Chain with Distribution 316
9.4.4 Dependency Between Echelon Stock and Number of Links of One Level in the Supply Chain 318
9.5 Inventory Planning in Spare Parts Supply Chains 319
9.5.1 METRIC Method in Spare Parts Supplies 320
9.5.2 Inventory Planning for Central Spare Parts Storage Using (R,Q) Model 324
9.6 Coordinated Planning Between Two Supply Chain Members 327
References 330
10: Planning of Supplies to Consumers 331
10.1 Sales and Operation Planning 331
10.1.1 Interrelation Between Various Planning Directions with Sales and Operations Plan 331
10.1.2 Sales and Operation Planning Methods 333
10.2 Sales and Operation Plan Optimization Using Linear Programming 336
10.2.1 Single Aggregated Product Group Optimization 337
10.2.2 More Complex Case of Optimization of Sales and Operations Plan 340
10.3 Customized Reservation of Products 344
10.3.1 Business Process of Response to New Orders 344
10.3.2 Arrangement of Orders 345
10.3.3 Running ATP Process 347
10.4 Agreement of Order Specifications with Customers 349
10.4.1 Problem Criteria and Their Evaluation 349
10.4.2 Selection of Ordered Product Analogues 350
References 356
11: Lot Sizing 357
11.1 Classification of Lot-Sizing Problems 357
11.1.1 Lot Properties and Main Problems 357
11.1.2 Lot-Sizing Problems with No Capacity Limits 359
11.1.3 Lot-Sizing Problems with Limited Capacities and Large Planning Periods 360
11.1.4 Lot-Sizing Problems with Limited Capacities and Small Planning Periods 361
11.2 Constant Demand Lot-Sizing Problems 362
11.2.1 Models with Gradual Inventory Replenishment 363
11.2.2 Model Applicable to the Machinery Industry If No Cost Information Is Available 365
11.2.3 Three-Parameter Models for Machinery Industry 367
11.2.4 Lot Sizing at Discounted Prices 369
11.3 Lot Sizing at Variable Demand and Limited Planning Horizon 370
11.3.1 Exact Solution 371
11.3.2 Heuristic Silver-Meal Algorithm 374
11.3.3 Part Period Balancing 377
11.3.4 Groff´s Heuristic Rule 378
11.3.5 Period Order Quantity 380
11.4 Lot Sizing with Constraints 381
11.5 Multi-product Deliveries and Orders 384
11.5.1 Optimal Multi-product Lot Sizing 384
11.5.2 Multi-product Deliveries over Multiple Periods 386
11.5.3 Power-of-Two Policies for Multi-product Deliveries 388
References 389
12: Production Planning 391
12.1 Master Production Planning 391
12.1.1 Master Planning as Product Tables 392
12.1.2 Group Master Planning 397
12.1.3 Master Production Plan Optimization 399
12.2 Material Requirement Planning 401
12.2.1 Production Lot Duration 402
12.2.2 Optimal Production Lot Sizing 404
12.2.3 Analysis of the Material Requirement Plan 408
12.3 Project-Based Planning 409
12.3.1 Critical Path Method 409
12.3.2 Cost Optimization at Various Project Stages 412
12.4 Stability of Planning 416
12.4.1 Quantitative Evaluation of Planning Stability 417
12.4.2 Methods of Planning Stability Improvement 419
References 422
13: Shop Floor Scheduling: Single-Stage Problems 423
13.1 Single-Machine Scheduling with Minimized Overdue Penalties 423
13.1.1 Schedule with the Minimum of Delayed Jobs 424
13.1.2 Scheduling with Minimum Weighted Tardiness per Each Job 424
13.1.3 Schedule Optimization with Earliness/Tardiness 427
13.2 Common Shipment Date Scheduling 428
13.2.1 Fixed Date Schedule Optimization 428
13.2.2 More Complex Cases of Scheduling with Fixed Date 430
13.2.3 Selection of Optimal Midpoint Date for Shipping 431
13.3 Some Other Scheduling Problems for Jobs with Fixed Processing Time 433
13.3.1 Schedules for the Case of Several Jobs, the Part of Which Has the Preset Sequence 433
13.3.2 Scheduling of Jobs with Different Arrival Time 435
13.3.3 Scheduling of Jobs with Different Arrival Time and Different Shipment Time 436
13.3.4 Job Sequence-Based Setup Time Scheduling 437
13.4 Periodic Scheduling with Lots of Economic Sizes 439
13.4.1 Equal-Time Schedules for All Products 439
13.4.2 Variable-Time Schedules for Different Products 441
13.5 Group Technology in Schedules for a Single Machine 444
13.5.1 Group Scheduling for Series Batches 445
13.5.2 Group Scheduling for Parallel Batches with Minimum Tardiness Criterion 448
13.5.3 Group Scheduling for Parallel Batches with Maximum Average Utility Criterion 450
13.6 Parallel Machine Scheduling 458
13.6.1 Identical Parallel Machine Scheduling 458
13.6.2 Schedules for Parallel Unrelated Machines 460
References 463
14: Shop Floor Scheduling: Multi-stage Problems 464
14.1 Synchronized Flowshop Production 464
14.1.1 Discrete Product Lines 465
14.1.2 Lines for Process Production 466
14.1.3 Flexible Flow Lines 467
14.2 Automated Assembly Lines 469
14.2.1 Scheduling for Unpaced Assembly Lines 470
14.2.2 Scheduling for Paced Assembly Line 473
14.2.3 Scheduling for Mixed Assembly Lines 477
14.3 Unsynchronized Flowshop Production 479
14.3.1 Modelling for Unsynchronized (Discontinuous) Flow Lines 480
14.3.2 Optimization for Two-Machine Group Flow Lines 483
14.3.3 Campbell, Dudek, and Smith Algorithm 485
14.3.4 Nawaz, Enscore, Ham Algorithm 486
14.4 Job-Shop Production 487
14.4.1 Shifting Bottleneck Algorithm 488
14.4.2 Job-Shop Production Scheduling Using Dynamic List Algorithms 493
References 500
15: Multi-criteria Scheduling 501
15.1 Just-in-Time Production Scheduling 501
15.1.1 Starting Group of Jobs with Fixed Sequence 501
15.1.2 Scheduling for Identical Parallel Machines with Common Shipment Date 505
15.2 Multi-objective Algorithms for Some Simple Production Structures 506
15.2.1 Scheduling for Two-Machine Flowshop Production 506
15.2.2 Schedule for Parallel Uniform Machines 509
15.2.3 Some Other Problems and Solving Challenges 515
15.3 Scheduling Based on Cost and Average Orders Utility 517
15.3.1 Sequenced Job Scheduling with Sequence-Dependent Setups 518
15.3.2 Group Scheduling for Parallel Batches Based on Maximum Average Utility and Minimum Setup Costs 527
15.4 Application of Decision Theory Methods 531
15.4.1 Application of Savage Principle for Decision-Making 532
15.4.2 Application of Hurwitz Principle for Decision-Making 534
15.5 Decision-Support Systems 535
15.5.1 Decision-Support System for Hybrid Flow Lines 535
15.5.2 Some Other Decision-Support Systems 537
References 539
Appendix A: Symbols 541
Appendix B: Abbreviations 543
Appendix C: Classification Parameters of Schedules 545
C.1 Parameters in Field ? 545
C.2 Parameters in Field beta 546
C.3 Parameters in Field gamma 546
Appendix D: Production Intensity Integral Calculations 548
Appendix E: Scheduling Software Based on Order Utility Functions 552
E.1 General 552
E.2 Description of Work with File1.xls 552
E.2.1 Worksheet 552
E.2.2 How to Use the Program 553
E.2.3 Planning Result Analysis 556
E.2.4 Errors During Program Run 558
E.3 Description of Work with File2.xls 558
E.3.1 Worksheet 558
E.3.2 How to Use the Program 559
E.4 Description of Work with File3.xls 560
E.4.1 Worksheet 560
E.4.2 How to Use the Program 561
E.4.3 Planning Results Analysis 562
E.4.4 New Task 562
E.5 Description of Work with File4.xls 563
E.5.1 Worksheet 563
E.5.2 How to Use the Program 563
E.6 Description of Work with File5.xls 565
E.6.1 Worksheet 566
E.6.2 How to Use the Program 566
E.7 Description of Work with File6.xls 568
E.7.1 Worksheet 568
E.7.2 How to Use the Program 569
E.8 Description of Work with File7.xls 571
E.8.1 Worksheet 571
E.8.2 How to Use the Program 572
E.9 Description of Work with File8.xls 572
E.9.1 Worksheet 573
E.9.2 How to Use the Program 573
Appendix F: Using Clobbi 575
F.1 General 575
F.2 Description of Planning Possibilities in the System 577
F.3 Description of Service Operation 578
F.3.1 Generating Manufacturing Schedules 579
F.4 Clobbi Service Advantages 580
F.5 Online Registration of Manufacturing Events 582
F.6 ClobbiCommercial Use 583

Produkt-Details

• Erscheint lt. Verlag: 25.4.2016
• Zusatzinfo: XXIII, 570 p. 186 illus., 25 illus. in color.
• Verlagsort: Cham
• Sprache: englisch
• Original-Titel: Продвинутое планирование и расписания (AP&S) в производстве и цепочках поставок
• Themenwelt: Mathematik / Informatik ► Mathematik
• Themenwelt: Technik
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management ► Planung / Organisation
• Schlagworte: Bottleneck Operation Planning • Demand Forecasting • Engineering Economics • linear optimization • Manufacturing • Supply chains • Supply Management Model
• ISBN-10: 3-319-27523-2 / 3319275232
• ISBN-13: 978-3-319-27523-9 / 9783319275239