Throughput Optimization in Robotic Cells

Throughput Optimization in Robotic Cells

-

English

Description

Modern manufacturing processes have thoroughly incorporated automation and repetitive processing. The use of computer-controlled material handling systems to convey raw materials through the multiple processing stages required to produce a finished product is widely employed in industry world-wide. Central to these systems are robot-served manufacturing cells, or robotic cells. These cells perform a variety of functions including arc welding, material handling, electroplating, textiles creation, and machining. In addition, they are used in many different industries, including injection molding of battery components, glass manufacturing and processing, building products, cosmetics, lawn tractors, fiber-optics, and semi-conductor manufacturing. In the medical field, robotic cells are used to produce components for magnetic resonance imaging systems, for automated pharmacy compounding, to process nucleic acids, and to generate compounds for tests in relevant biological screens. Cells for grinding, polishing, and buffing handle many products, including rotors, stainless steel elbows for the chemical and the food industries, sink levers and faucets, propane tanks, flatware, automotive products, and more. All of this has resulted with the rapid growth of robotic cell scheduling. As manufacturers have employed them in greater numbers and greater varieties, analysts have developed new models and techniques to maximize these cells productivity. Competitive pressures will result in the development of more advanced cells and, hence, more sophisticated studies. Therefore, robotic cell scheduling should continue to attract the attention of a growing number of practitioners and researchers.



THROUGHPUT OPTIMIZATION IN ROBOTIC CELLS is a comprehensive introduction to the field of robotic scheduling. It discusses the basic properties of robotic cells and outlines in detail the tools most often used to analyze them. In doing so, the book will provide a thorough algorithmic analysis of optimal policies for a variety of implementations. The book provides a classification scheme for robot cell scheduling problems that is based on cell characteristics, and discusses the influence of these characteristics on the methods of analysis employed. Implementation issues are stressed. Specifically, these issues are explored in terms of implementing solutions and open problems.

Subjects

Informations

Published by
Published 04 May 2007
Reads 8
EAN13 9780387709888
License: All rights reserved
Language English
Report a problem
Contents
Preface 1. ROBOTIC CELLS IN PRACTICE 1.1 Cellular Manufacturing 1.2 Robotic Cell Flowshops 1.3 Throughput Optimization 1.4 Historical Overview 1.5 Applications 2. A CLASSIFICATION SCHEME FOR ROBOTIC CELLS AND NOTATION 2.1 Machine Environment 2.1.1 Number of Machines 2.1.2 Number of Robots 2.1.3 Types of Robots 2.1.4 Cell Layout 2.2 Processing Characteristics 2.2.1 Pickup Criterion 2.2.2 TravelTime Metric 2.2.3 Number of PartTypes 2.3 Objective Function 2.4 Anα|β|γClassification for Robotic Cells 2.5 Cell Data 2.5.1 Processing Times 2.5.2 Loading and Unloading Times 2.5.3 Notations for Cell States and Robot Actions 3. CYCLIC PRODUCTION 3.1 Operating Policies and Dominance of Cyclic Solutions
ix
xv 1 2 3 7 9 11
15 15 15 16 17 17 17 17 18 20 20 20 24 24 24 25 29 29
x
4.
5.
3.2 3.3 3.4 3.5
THROUGHPUT OPTIMIZATION IN ROBOTIC CELLS
Cycle Times 3.2.1 Waiting Times 3.2.2 Computation of Cycle Times 3.2.3 Lower Bounds on Cycle Times Optimal 1Unit Cycles 3.3.1 Special Cases 3.3.2 General Cases: Constant TravelTime Cells 3.3.2.1 Optimization over Basic Cycles 3.3.3 General Cases: Additive and Euclidean Travel Time Cells Calculation of Makespan of a Lot 3.4.1 A Graphical Approach 3.4.2 Algebraic Approaches Quality of 1Unit Cycles and Approximation Results 3.5.1 Additive TravelTime Cells 3.5.1.1 Pyramidal Cycles 3.5.1.2 A 1.5Approximation Algorithm 3.5.1.3 A 10/7Approximation for Additive Cells 3.5.2 Constant TravelTime Cells 3.5.2.1 A 1.5Approximation Algorithm 3.5.3 Euclidean TravelTime Cells DUALGRIPPER ROBOTS Additional Notation Cells with Two Machines A Cyclic Sequence formMachine DualGripper Cells DualGripper Cells with Small Gripper Switch Times Comparing DualGripper and SingleGripper Cells Comparison of Productivity: Computational Results Efficiently Solvable Cases SingleGripper Cells with Output Buffers at Machines DualGripper Robotic Cells: Constant Travel Time 4.9.1 Lower Bounds and Optimal Cycles:mMachine Simple Robotic Cells 4.9.2 OneUnit Cycles 4.9.3 MultiUnit Cycles PARALLEL MACHINES SingleGripper Robots 5.1.1 Definitions 5.1.2kUnit Cycles and Blocked Cycles
4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9
5.1
34 34 35 39 40 40 43 51
61 63 63 64 65 66 68 68 74 87 89 94 101 102 104 107 114 116 122 128 131 141
143 144 146 153 154 154 156
Contents
6.
5.2
5.1.2.1 Structural Results forkUnit Cycles 5.1.2.2 Blocked Cycles 5.1.3 LCM Cycles 5.1.4 Practical Implications 5.1.4.1 Optimal Cycle for a Common Case 5.1.4.2 Fewest Machines Required to Meet Timelines DualGripper Robots 5.2.1 Lower Bound on Per Unit Cycle Time 5.2.2 An Optimal Cycle 5.2.3 Improvement from Using a DualGripper Robot or Parallel Machines
Cell 5.2.3.2 Installing Parallel Machines in a SingleGripper Robot Cell 5.2.3.3 Installing a DualGripper Robot in a SingleGripper Robotic Cell with Parallel Machines 5.2.3.4 An Illustration on Data from Implemented Cells
xi
156 157 165 169 169 171 171 172 175 180 5.2.3.1 Installing a DualGripper Robot in a Simple Robotic 181 182 183 187 MULTIPLEPARTTYPE PRODUCTION: SINGLEGRIPPER 191 192 194 206 207 211 216 217 225 229 231 231 238 244 247 250 251 253 264 268 270 270
ROBOTS MPS Cycles and CRM Sequences Scheduling Multiple PartTypes in TwoMachine Cells Scheduling Multiple PartTypes in ThreeMachine Cells 6.3.1 Cycle Time Derivations 6.3.2 Efficiently Solvable Special Cases SteadyState Analyses 6.4.1 Reaching Steady State for the SequenceCRM(π2) 6.4.2 Reaching Steady State for the SequenceCRM(π6) 6.4.3 A Practical Guide to Initializing Robotic Cells Intractable Cycles for ThreeMachine Cells 6.5.1 MPS Cycles with the SequenceCRM(π2) 6.5.2 MPS Cycles with the SequenceCRM(π6) 6.5.3 Complexity of ThreeMachine Robotic Cells Scheduling Multiple PartTypes in Large Cells 6.6.1 ClassUIndependent Problems: Schedule 6.6.2 ClassV1: Special Cases of the TSP 6.6.3 ClassV2: NPHard TSP Problems 6.6.4 ClassW: NPHard NonTSP Problems 6.6.5 Overview Heuristics for ThreeMachine Problems 6.7.1 A Heuristic Under the SequenceCRM(π2)
6.1 6.2 6.3 6.4 6.5 6.6 6.7
xii
THROUGHPUT OPTIMIZATION IN ROBOTIC CELLS
6.7.2 A Heuristic Under the SequenceCRM(π6) 6.7.3 Computational Testing 6.7.4 Heuristics for General ThreeMachine Problems 6.8 Heuristics for Large Cells 6.9 The Cell Design Problem 6.9.1 Forming Cells 6.9.2 Buffer Design 6.9.3 An Example 6.9.4 Computational Testing MULTIPLEPARTTYPE PRODUCTION: DUALGRIPPER ROBOTS 7.1 TwoMachine Cells: Undominated CRM Sequences 7.2 TwoMachine Cells: Complexity 7.2.1 Cycle Time Calculation 7.2.2 Strong NPCompleteness Results 7.2.3 Polynomially Solvable Problems 7.3 Analyzing TwoMachine Cells with Small Gripper Switch Times 7.4 A Heuristic for Specific CRM Sequences 7.4.1 A Performance Bound for Heuristic HardCRM 7.5 A Heuristic for TwoMachine Cells 7.6 Comparison of Productivity: SingleGripper Vs. Dual Gripper Cells 7.7 An Extension tomMachine Robotic Cells MULTIPLEROBOT CELLS 8.1 Physical Description of a MultipleRobot Cell 8.2 Cycles in MultipleRobot Cells 8.3 Cycle Times 8.4 Scheduling by a Heuristic Dispatching Rule 8.5 Computational Results 8.6 Applying an LCM Cycle to Implemented Cells NOWAIT AND INTERVAL ROBOTIC CELLS 9.1 NoWait Robotic Cells 9.2 Interval Pickup Robotic Cells 10. OPEN PROBLEMS 10.1 Simple Robotic Cells 10.2 Simple Robotic Cells with Multiple Part Types
7. 8. 9.
273 274 276 281 284 285 288 292 293
297 300 306 306 312 318
319 324 325 339
340 342 349 350 352 354 357 358 361 363 363 369 371 371 376
Contents
10.3 Robotic Cells with Parallel Machines 10.4 Stochastic Data 10.5 DualGripper Robots 10.6 Flexible Robotic Cells 10.7 Implementation Issues 10.7.1 Using Local Material Handling Devices 10.7.2 Revisiting Machines Appendices Appendix A A.1 1Unit Cycles A.1.1 1Unit Cycles in Classical Notation A.1.2 1Unit Cycles in Activity Notation Appendix B B.1 The GilmoreGomory Algorithm for the TSP B.1.1 The TwoMachine NoWait Flowshop Problem B.1.2 Formulating a TSP B.1.3 The GilmoreGomory Algorithm
xiii
376 377 377 378 378 378 379 383 383 384 385 387 387 387 388 389 B.2 The ThreeMachine NoWait Flowshop Problem as a TSP 394 409
Copyright Permissions
Index
413
http://www.springer.com/978-0-387-70987-1