High Performance Instrumentation and Automation 1st Edition by Patrick Garrett ISBN 0849337763 978-0849337765

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ISBN 10: 0849337763
ISBN 13: 978-0849337765
Author: Patrick Garrett

Improvements in process control, such as defined-accuracy instrumentation structures and computationally intelligent process modeling, enable advanced capabilities such as molecular manufacturing. High Performance Instrumentation and Automation demonstrates how systematizing the design of instrumentation and automation leads to higher performance through more homogeneous systems, which are frequently assisted by rule-based, fuzzy logic, and neural network process descriptions.

Incorporate Advanced Performance Enhancements into Your Automation Enterprise

The book illustrates generic common core process-to-control concurrent engineering linkages applied to a variety of laboratory and industry automation systems. It outlines:

• Product properties translated into realizable process variables
• Axiomatic decoupling of subprocess variables for improved robustness
• Production planner model-driven goal state execution
• In situ sensor and control structures for attenuating process disorder
• Apparatus tolerance design for minimizing process variabilities
• Production planner remodeling based on product features measurement for quality advancement

Coverage also includes multisensor data fusion, high-performance computer I/O design guided by comprehensive error modeling, multiple sensor algorithmic error propagation, robotic axes volumetric accuracy, quantitative video digitization and reconstruction evaluation, and in situ process measurement methods.

High Performance Instrumentation and Automation reflects the experience of engineer and author Patrick Garrett, including his role as co-principal investigator for an Air Force intelligent manufacturing initiative.

You can download Analysis Suite.xls, computer-aided design instrumentation software, available in the book’s description on the CRC Press website.

High Performance Instrumentation and Automation 1stTable of contents:

Chapter 1 Thermal, mechanical, quantum, and analytical sensors

1.0 Introduction

1.1 Instrumentation error interpretation

1.2 Temperature sensors

1.3 Mechanical sensors

1.4 Quantum sensors

1.5 Analytical sensors

Bibliography

Chapter 2 Instrumentation amplifiers and parameter errors

2.0 Introduction

2.1 Device temperature characteristics

2.2 Differential amplifiers

2.3 Operational amplifiers

2.4 Instrumentation amplifiers

2.5 Amplifier parameter error evaluation

Bibliography

Chapter 3 Instrumentation filters with nominal error

3.0 Introduction

3.1 Bandlimiting instrumentation filters

3.2 Active filter networks

3.3 Filter error analysis

Bibliography

Chapter 4 Signal acquisition, conditioning, and processing

4.0 Introduction

4.1 Low-level signal acquisition

4.2 Signal quality in random and coherent interference

4.3 DC, sinusoidal, and harmonic signal conditioning

4.4 Analog signal processing

Bibliography

Chapter 5 Data conversion devices and errors

5.0 Introduction

5.1 Analog multiplexers

5.2 Sample-holds

5.3 Digital-to-analog converters

5.4 Analog-to-digital converters

Bibliography

Chapter 6 Sampled data and recovery with intersample error

6.0 Introduction

6.1 Sampled data theory

6.2 Aliasing of signal and noise

6.3 Sampled data intersample and aperture errors

6.4 Output signal interpolation functions

6.5 Video sampling and reconstruction

Bibliography

Chapter 7 Advanced instrumentation systems and error analysis

7.0 Introduction

7.1 Integrated instrumentation design

7.2 Multisensor error propagation

7.3 Robotic axes volumetric error

Bibliography

Appendix A

Chapter 8 Automation systems concurrent engineering

8.0 Introduction

8.1 Concurrent engineering common core

8.2 Product property apparatus variables

8.3 Robust process axiomatic design

8.4 Automated production ex situ planner

8.5 Molecular in situ subprocess control

8.6 System variability tolerance analysis

8.7 Product features remodeling for quality maturity

Bibliography

Chapter 9 Molecular beam epitaxy semiconductor processing

9.0 Introduction

9.1 Molecular beam epitaxy concurrent engineering

9.2 MBE material property modeling

9.3 Robust process design and PID tuning

9.4 MBE in situ ellipsometry

9.5 Instrumentation and control tolerance analysis

Bibliography

Chapter 10 Aerospace composites rule-based manufacturing

10.0 Introduction

10.1 Composite manufacturing concurrent engineering

10.2 Composite cure properties and apparatus

10.3 Computational qualitative reasoning

10.4 Rule-based ex situ planner

10.5 In situ sensor fusion cure control

10.6 Temperature control tolerance analysis

Bibliography

Chapter 11 Fuzzy logic laser deposition superconductor production

11.0 Introduction

11.1 Superconductor processing concurrent engineering

11.2 Material property modeling

11.3 Robust axiomatic process decoupling

11.4 Observer remodeled ex situ planner

11.5 Spectrometer in situ fuzzy control

11.6 Process data tolerance evaluation

11.7 Superconductor Raman quality analysis

Bibliography

Chapter 12 Neural network directed steel annealing

12.0 Introduction

12.1 Steel annealing concurrent engineering

12.2 Recrystallization annealing physical properties

12.3 ANNEAL NET ex situ planner

12.4 Steel annealing in situ control

Bibliography

Chapter 13 X-Ray controlled vapor infiltration ceramic densification

13.0 Introduction

13.1 Ceramic matrix composite concurrent engineering

13.2 Combustor product property modeling

13.3 Microwave densification ex situ planner

13.4 X-Ray and infrared in situ control

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