Description
Maximize your chance of first-time success when designing any communication system with this new book and CD-ROM. It introduces a graphical design method that allows you to center or adjust the specifications of your designs to achieve the best overall system performance. The book helps you improve the speed, cost-effectiveness, and quality of your designs using the mu-sigma graph technique, a new design method that shows you how to use computer simulation to identify internal system requirements and relate a parameter 's mean value to its allowed standard deviation. It also presents a methodology for determining failure rates for non-Gaussian distributions, explores various computer modeling techniques and process capability indices, and examines the relationship between mu-sigma graphs and the conventional Taguchi methods of quality improvement. Design engineers easily pinpoint conflicting system requirements, evaluate different architectures, and make better, more informed choices of which circuits to include in a particular design.
Table Of Contents
1. Design Centering Methodologies: Differences Between Device and System Design Centering. Optimization Techniques. 2. Overview of Statistical Design Methods: Reasons for Using Statistical Design. Device and System Design Approaches. Definition of Cpk. Taguchi Methods. Practical Concerns and the Mu-Sigma Graph. 3. A New Look at Statistical Design: A Change of Viewpoint. The Mu-Sigma Graph. Description of Improved Statistical Design Method. Benefits of the New Statistical Method. Example of New Design Centering Method. Interpreting Mu-Sigma Graphs. 4. Importance of System Simulations: Customer Requirements. Single-Ended Specifications. Estimating the Starting Point. System Simulation Software. The Challenge of High Quality. 5. Electrical Engineering Applications of the Mu-Sigma Graph Method: Product Support. Product Architecture. Product Development. 6. Other Applications of the Mu-Sigma Graph Method: Mechanical Tolerance Analysis. Manufacturing. Financial Modeling. 7. Basic Statistical Concepts: Failure-Rate Estimation. Statistical Distributions. Bounded and Unbounded Distributions. Statistical Formulas. Confidence Intervals. Appendices