Yield and Variability Optimization of Integrated Circuits - Tapa dura

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.

Yield and Variability Optimization of Integrated Circuits deals with the primary and theoretical and practical aspects of IC statistical design and covers the most important issues of IC statistical design and the relevant mathematical framework. It describes a spectrum of different statistical circuit design problems, such as parametric yield optimization, generalized on-target design, variability minimization, performance tuning, and worst-case design. It also covers such topics as device statistical and worst-case modeling, design of experiments and factor screening, together with some basic tenets of fuzzy set theory and multi-objective statistical optimization. Several practical examples are used to familiarize the reader with the concepts, and demonstrate the applicability of various statistical circuit design methodologies.
Yield and Variability Optimization of Integrated Circuits is intended as introductory reference material for various groups of IC designers, and the methodologies described provide an understanding of the complex problems of statistical circuit design, thus helping to enhance the overall quality of the ICs delivered to the customers.