Yield and Variability Optimization of Integrated Circuits

Author:   Jian Cheng Zhang ,  M.A. Styblinski
Publisher:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 1995
ISBN:  

9781461359357


Pages:   234
Publication Date:   02 November 2012
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Yield and Variability Optimization of Integrated Circuits


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Overview

Traditionally, Computer Aided Design (CAD) tools have been used to create the nominal design of an integrated circuit (IC), such that the circuit nominal response meets the desired performance specifications. In reality, however, due to the disturbances ofthe IC manufacturing process, the actual performancesof the mass produced chips are different than those for the nominal design. Even if the manufacturing process were tightly controlled, so that there were little variations across the chips manufactured, the environmentalchanges (e. g. those oftemperature, supply voltages, etc. ) would alsomakethe circuit performances vary during the circuit life span. Process-related performance variations may lead to low manufacturing yield, and unacceptable product quality. For these reasons, statistical circuit design techniques are required to design the circuit parameters, taking the statistical process variations into account. This book deals with some theoretical and practical aspects of IC statistical design, and emphasizes how they differ from those for discrete circuits. It de­ scribes a spectrum of different statistical design problems, such as parametric yield optimization, generalized on-target design, variability minimization, per­ formance tunning, and worst-case design. The main emphasis of the presen­ tation is placed on the principles and practical solutions for performance vari­ ability minimization. It is hoped that the book may serve as an introductory reference material for various groups of IC designers, and the methodologies described will help them enhance the circuit quality and manufacturability. The book containsseven chapters.

Full Product Details

Author:   Jian Cheng Zhang ,  M.A. Styblinski
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 1995
Dimensions:   Width: 15.50cm , Height: 1.30cm , Length: 23.50cm
Weight:   0.397kg
ISBN:  

9781461359357


ISBN 10:   146135935
Pages:   234
Publication Date:   02 November 2012
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1 Introduction.- 1.1 Design for Quality and Manufacturability.- 1.2 Notation.- 1.3 Interpretation of Basic Concepts.- 1.4 Summary.- 2 Overview of IC Statistical Modeling.- 2.1 Introduction.- 2.2 Process Variations.- 2.3 Environmental Variations.- 2.4 Statistical Macromodeling.- 2.5 Summary.- 3 Design of Experiments.- 3.1 Introduction.- 3.2 Experiment Analysis.- 3.3 Orthogonal Arrays.- 3.4 Main Effect Analysis.- 3.5 Interaction Analysis.- 3.6 Taguchi Experiments.- 3.7 Summary.- 4 Parametric Yield Maximization.- 4.1 Introduction.- 4.2 Yield Estimation.- 4.3 Indirect Yield Improvement.- 4.4 Direct Yield Optimization Methods.- 4.5 Generalized and Orthogonal Array-Based Gradient Methods for Discrete Circuits.- 4.6 Gradient Methods for Integrated Circuits.- 4.7 Examples.- 4.8 Summary.- 5 Variability Minimization and Tuning.- 5.1 Introduction.- 5.2 Principles of Discrete Circuit Variability Minimization.- 5.3 Principles of IC Variability Minimization.- 5.4 Factor Screening.- 5.5 Taguchi’s on-target Design.- 5.6 Two-Stage Design Strategy.- 5.7 Example 4: CMOS Delay Circuit.- 5.8 Example 5: CMOS Clock Driver.- 5.9 Summary.- 6 Worst-Case Measure Reduction.- 6.1 Introduction.- 6.2 The ±? Transistor Modeling.- 6.3 Worst-Case Measure Minimization.- 6.4 Comments on the ±? Model.- 6.5 Creation of Worst-Case Models From the Statistical Model.- 6.6 Summary.- 7 Multi-Objective Circuit Optimization.- 7.1 Introduction.- 7.2 Multiple-Objective Optimization: An Overview.- 7.3 Fuzzy Sets.- 7.4 Multiple-Performance Statistical Optimization.- 7.5 Multiple-Performance Variability Minimization.- 7.6 Summary.- References.

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