Optimization in polymer processing / editors, António Gaspar-Cunha and José António Covas.

Format:

Book

Contributor:

Gaspar-Cunha, António.

Covas, J. A.

Series:

Chemical engineering methods and technology.

Chemical engineering methods and technology

Language:

English

Subjects (All):

Plastics.

Production engineering.

Physical Description:

1 online resource (241 p.)

Edition:

1st ed.

Place of Publication:

Hauppauge, N.Y. : Nova Science Publishers, c2011.

Language Note:

English

Summary:

Plastics processing is a major industrial activity, which yields components and systems for a wide range of industries, such as packaging, automotive, aeronautics, electrical and electronic, sports and leisure, toys, civil and construction, and agriculture. Most plastic components are manufactured either by extrusion or injection molding, but other techniques such as blow molding and thermoforming are also important. The productivity of these technologies is dictated by the equipment design, choice of the operating conditions and physical properties of the polymer system. This book discusses the recent scientific developments on the optimization of manufacturing engineering problems and applies them to polymer processing technologies

Contents:

Intro

OPTIMIZATION IN POLYMER PROCESSING

CONTENTS

PREFACE

Chapter 1 INTRODUCTION

OPTIMIZATION IN ENGINEERING

Chapter2ANINTRODUCTIONTOOPTIMIZATION

1Introduction

2MathematicalFormulation

3ContinuousandDiscreteOptimization

4GlobalandLocalOptimizationandConvexity

5OptimalityConditions

5.1Unconstrainedproblems

5.2Constrainedproblems

6HeuristicsandMetaheuristics

7Conclusion

References

Chapter3ANINTRODUCTIONTOMULTIOBJECTIVEOPTIMIZATIONTECHNIQUES

2NotionsofOptimalityinMOPs

3MathematicalProgrammingTechniques

3.1APrioriPreferenceArticulation

3.1.1GoalProgramming

3.1.2Goal-AttainmentMethod

3.1.3LexicographicMethod

3.2APosterioriPreferenceArticulation

3.2.1LinearCombinationofWeights

3.2.2NormalBoundaryIntersection

3.2.3e-ConstraintMethod

3.2.4MethodofWeightedMetrics

3.3InteractivePreferenceArticulation

3.3.1MethodofGeoffrion-Dyer-Feinberg(GDF)

3.3.2TchebycheffMethod

3.3.3ReferencePointMethods

3.3.4LightBeamSearch

4EvolutionaryAlgorithms

4.1MOGA

4.2NSGAandNSGA-II

4.3SPEAandSPEA2

4.4PAES

4.5PESA

4.6NewTrendsinMOEAs

4.7IncorporationofPreferencesinMOEAs

4.8NewTrendsintheIncorporationofPreferencesinMOEAs

5Conclusion

Chapter 4 EXTENDING OPTIMIZATION ALGORITHMS TO COMPLEX ENGINEERING PROBLEMS

1. INTRODUCTION

2. THE METHODOLOGY

2.1. Methodology Structure

2.2. Multi-Objective Evolutionary Algorithms

3. DECISION MAKING

3.1. Current Methods

2.2. Weighted Stress Function Method

3. ROBUSTNESS

4. MEMETIC ALGORITHMS

4.1. General Concepts

4.2. Coupling MOEAs to a Local Search Method

5. Application Examples

Decision Making

Robustness

Memetic Algorithm

CONCLUSION

REFERENCES

APPLICATION TO POLYMER PROCESSING.

Chapter 5 POLYMER EXTRUSION - SETTING THE OPERATING CONDITIONS AND DEFINING THE SCREW GEOMETRY

2.MODELING

2.1.Single Screw Extrusion

2.2.Co-Rotating Twin-Screw Extrusion

3. OPTIMIZATION METHODOLOGIES

3.1. Characteristics of the Optimization Problems

3.2. TSCP as a Sequencing Problem

4. RESULTS AND DISCUSSION

4.1. Introduction

4.2. Single Screw Extrusion

4.3. Co-Rotating Twin-Screw Extrusion

4.4. Decision Making Strategies

Chapter 6 REACTIVE EXTRUSION - OPTIMIZATION OF REPRESENTATIVE PROCESSES

2. REACTIVE EXTRUSION MODELING

2.1. Concepts

Flow in the Twin Screw Extruder

Chemical Reaction

Rheokinetics

Coupling the Various Modules

Open Challenges to Model Reactive Extrusion

2.2. ε-caprolactone Polymerization

2.3. Starch Cationization

3. EXAMPLES OF THE OPTIMIZATION OF REACTIVE EXTRUSION

3.1. Optimization Algorithm

3.2. ε-Caprolactone Polymerization

3.3. Starch Cationization

Chapter 7 THE AUTOMATIC DESIGN OF EXTRUSION DIES AND CALIBRATION/COOLING SYSTEMS

2. STATE-OF-THE-ART

3. OPTIMIZATION METHODOLOGY

3.1. Problem Setup

Extrusion dies

Calibration/cooling systems

3.2. Pre-processor

3.3. Flow and Thermal Field Calculation

3.4. Performance Evaluation

Calibration/cooling system

3.5. Optimization Technique

4. CASE STUDY

4.1 Extrusion Die Flow Channel Optimisation

4.2. Calibration/cooling System Layout Optimisation

ACKNOWLEDGMENTS

Chapter 8 ON THE USE OF REDUCED BASES IN OPTIMIZATION OF INJECTION MOLDING

1.1. Process Description - Injection Molding

1.2. The Injection Molding Equipment

1.3. Description of the Injection Molding Cycle.

1.4. Importance of the Cooling Step for Manufacturing Injected Parts

2. MOLD COOLING PPTIMIZATION

2.1. Introduction

2.2. BEM for Transient Heat Balance Equation

2.3 Coupling DRBEM with an Optimization Method

3. REDUCING MODELING

3.1. Introduction

3.2. Revisiting the Karhunen-Loève Decomposition

3.3. Reduced Modeling

3.4. Reduced Basis Adaptivity

3.5 Illustrating the Applicability of Reduced Bases

3.6 Discussion

4. APPLICATION OF THE DRBEM REDUCED MODEL TO MOLD COOLING OPTIMIZATION

4.1. Reduced Model Coupled with DRBEM

4.2 Overall Optimization Methodology

4.3. Application

Chapter 9 ESTIMATION AND CONTROL OF SHEET TEMPERATURE IN THERMOFORMING

2. ESTIMATION AND CONTROL OF SHEET TEMPERATURE USING THE 2D FOURIER TRANSFORM

2.1. Estimation of Temperature

2.2. Interpolation by Zero Padding Technique

2.3. Simulation Results for the Estimation of Temperature by 2D FFT

2.4. Incorporation of the FFT-based Temperature Estimate into the Design of the Controller

2.5. Simulation Results with the Fourier Controller

3. SOLVING THE INVERSE HEATING PROBLEM BYCONJUGATE GRADIENT METHOD

3.1. Modeling of Sheet Reheat Phase in Thermoforming

3.2. Solving the Direct Heating Problem

3.3. Solution to the Inverse Heating Problem

3.4. Sensitivity Matrix Calculation

3.5. Simulation Results of the Proposed Solution Method for the Inverse Heating Problem

INDEX.

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

Description based on print version record and CIP data provided by publisher.

ISBN:

1-61324-746-X

OCLC:

755611260