Modeling and Simulation in Industrial Engineering (eBook)

Preface 6
Acknowledgements 7
Contents 8
Editors and Contributors 10
1 Optimization of Forming Processes for Gelled Propellant Manufacturing 13
1 Introduction to the Gelled Propellant Manufacturing 13
1.1 Manufacturing of Nitrocellulose-Based Colloidal Propellants 15
1.2 Manufacturing Processes Associated with the Rheological Behaviour of Gelled Propellants 17
1.2.1 Batch Mixing of Nitrocellulose Gels 17
1.2.2 Ram Extrusion of Gelled Propellant Doughs 18
2 Process and Material Parameters for Propellant Production Controlling 20
2.1 Process Parameters to Control During the Propellant Production 20
2.1.1 Process Parameters in Batch Mixing 20
2.1.2 Process Parameters in Ram Extrusion 21
2.2 Material Parameters to Control During the Propellant Production 23
2.2.1 Rheological Parameters 23
2.2.2 Physical Parameters 26
3 Self-controlling Measuring Path for Propellant Production 27
4 Measuring Devices for Process and Material Parameters 28
5 Procedures and Registers for Propellant Production Controlling 30
6 Example of Industrial Application of This Production Control Methodology 32
7 Conclusions 39
References 39
2 Random Excitation Technique for Measurement of Acoustic Properties 41
1 Introduction 41
2 Acoustic Waves 42
2.1 Plane Waves 42
2.1.1 Waves in Absorptive Stationary Medium 47
3 Acoustic Waves 48
3.1 Set-up Selection 48
3.1.1 Sliding Microphone Probe Experiment (SME) 48
3.1.2 Fixed Two Microphone Impedance Tube Experiment (FME) 49
3.1.3 Transfer Matrix Method (TMM) 50
3.1.4 Comparison 50
3.2 Theory 50
3.2.1 Spectral Density 51
3.2.2 Evaluation of Attenuation Constant 52
3.2.3 Normalized Impedance and Reflection Coefficient 54
4 Measurement (Microphones and Transducers) 57
4.1 Sensitivity 58
4.2 Frequency Response 58
4.3 Dynamic Range 59
5 Pre-amplification 59
6 Analog to Digital Conversion 59
6.1 Flash ADC 60
6.2 Sigma-Delta ADC 60
6.3 Dual Slope ADC 61
6.4 Successive Approximation Converter 62
7 Analysis 62
8 Precautions 62
8.1 Deviation from Assumptions 63
8.2 Environmental Effects 64
8.3 Special Anomalies 64
8.4 Methods to Enhance Accuracy 66
References 67
3 Optimal Inspection Intervals for Multi-One-Shot Systems 68
1 Introduction 68
2 Inspection Schedule for Multi One-Shot Systems Under Limited Maintenance Resources 71
2.1 Inspection Schedule for Multi One-Shot Systems 71
2.2 Inspection Schedule Model of Multi One-Shot Systems 74
3 Optimization Method for Inspection Schedule of Multi One-Shot Systems 75
3.1 Simulation-Based Optimization Procedure with a Hybrid Genetic Algorithm 75
3.2 Hybrid Genetic Algorithm with Heuristic Method in Phase 1 79
3.3 Hybrid Genetic Algorithm with Heuristic Method in Phase 2 82
3.4 Heuristic Method in Phase 2 84
4 Numerical Examples 85
4.1 CASE 1: Different Target Interval Availability 86
4.2 CASE 2: Decreasing the Scale Parameters of the Failure Distribution of Type 1 Units 89
4.3 CASE 3: Increasing the Failure Thresholds of Type 2 Units 90
5 Conclusions 92
Acknowledgements 93
References 93
4 Industrial System Performance Under Multistate Failures with Standby Mode 95
1 Introduction 95
2 Problem Statement 96
3 Mathematical Formulation and Solution 97
4 Numerical Computations 103
4.1 Availability Analysis 103
4.2 Reliability Analysis 104
4.3 Mean Time to Failure (MTTF) Analysis 104
4.4 Sensitivity Analysis 106
4.4.1 Sensitivity of Reliability 106
4.4.2 MTTF Sensitivity 106
5 Conclusion 108
References 108
5 An Insight into the Coanda Flow Through Mathematical Modeling 111
1 Introduction 111
2 Problem Formulation 112
3 Mathematical Modeling 113
4 Solution Methodology 115
5 Results and Discussion 118
6 Conclusion 123
Acknowledgements 123
References 123
6 Preliminary CDF Assessment of an Innovative Propelled Wing with Enhanced Performances by Coanda Effect 125
1 Introduction 125
2 The New Propelled Wing Concept 128
3 Preliminary Model 131
4 Thrust and Lift Behavior 132
5 Numerical Activity 132
6 Results and Discussions 134
7 Conclusions 138
Acknowledgements 138
References 138
7 Stochastic Modeling in Industry and Management 141
1 Basics of Probability 141
2 Discrete Random Variables and Discrete Probability Distribution Functions 143
3 Moment and Probability Generating Function 145
4 Selected Standard Discrete Distribution Functions 146
4.1 Bernoulli Probability Distribution Function 146
4.2 Binomial Probability Distribution Function 147
4.3 Geometric Probability Distribution Function 147
4.4 Poisson Probability Distribution Function 148
5 Continuous Random Variables and Continuous Probability Distribution Functions 149
6 Selected Standard Continuous Distribution Functions 150
6.1 Uniform Probability Distribution Function 150
6.2 (Negative) Exponential Probability Distribution Function 150
7 Stochastic Processes 152
8 Generating Functions and Their Application in Solution of Difference Equations 159
9 Queueing Processes 160
9.1 Mechanism of a Queue 160
10 Certain Stochastic Models in Industry and Management 161
10.1 M/M/1 Queueing Model 161
10.2 A Multiserver Queueing System with Balking and Reneging 165
10.2.1 The Model 167
10.2.2 Analysis 167
10.3 A Stochastic Hiring Model 170
10.3.1 The Model 170
10.3.2 The Analysis of the First Stage (FS), Initial Processing 171
10.3.3 Number of Batches in the FS at a Departure of a Batch 180
10.4 A Queueing System with Delayed Feedback 183
10.4.1 The Model 184
10.4.2 Analysis 185
References 187
8 A Study on Optimal Preventive Maintenance Policies for Cumulative Damage Models 189
1 Introduction 189
2 Preventive Maintenance Policies for a Cumulative Damage Model with a Continuous Distribution 190
2.1 Model and Assumptions 190
2.2 Analysis and Theorems 191
2.3 Remarks 193
3 Preventive Maintenance Policies for a Cumulative Damage Model with a Discrete Distribution 193
3.1 Model and Assumptions 193
3.2 Analysis and Theorems 194
3.3 Remarks 196
4 Concluding Remarks 197
References 197
9 Elevator System Analysis in Deliberation of Dependability, Cost Under Coverage, and Copula Approaches 199
1 Introduction 199
2 Problem Descriptions 201
3 Assumptions and Nomenclature 204
4 Formulation of the Model 205
5 Solution of the Model 206
6 State Transition Probability 207
7 Probability of the System in Upstate and Downstate 209
8 Particular Cases and Numerical Examples 209
8.1 Availability Analysis 209
8.2 Reliability Analysis 215
8.3 Expected Profit 215
9 Results Interpretation 217
10 Conclusion 222
References 222
Index 224