One of the keys to success in the IC industry is getting a new product to market in a timely fashion and being able to produce that product with sufficient yield to be profitable. There are two ways to increase yield: by improving the control of the manufacturing process and by designing the process and the circuits in such a way as to minimize the effect of the inherent variations of the process on performance. The latter is typically referred to as "design for manufacture" or "statistical design." As device sizes continue to shrink, the effects of the inherent fluctuations in the IC fabrication process will have an even more obvious effect on circuit performance. And design for manufacture will increase in importance. We have been working in the area of statistically based computer aided design for more than 13 years. During the last decade we have been working with each other, and individually with our students, to develop methods and CAD tools that can be used to improve yield during the design and manufacturing phases of IC realization. This effort has resulted in a large number of publications that have appeared in a variety of journals and conference proceedings. Thus our motivation in writing this book is to put, in one place, a description of our approach to IC yield enhancement. While the work that is contained in this book has appeared in the open literature, we have attempted to use a consistent notation throughout this book.

Over the years there has been a large increase in the functionality available on a single integrated circuit. This has been mainly achieved by a continuous drive towards smaller feature sizes, larger dies, and better packing efficiency. However, this greater functionality has also resulted in substantial increases in the capital investment needed to build fabrication facilities. Given such a high level of investment, it is critical for IC manufacturers to reduce manufacturing costs and get a better return on their investment. The most obvious method of reducing the manufacturing cost per die is to improve manufacturing yield. Modern VLSI research and engineering (which includes design manufacturing and testing) encompasses a very broad range of disciplines such as chemistry, physics, material science, circuit design, mathematics and computer science. Due to this diversity, the VLSI arena has become fractured into a number of separate sub-domains with little or no interaction between them. This is the case with the relationships between testing and manufacturing. From Contamination to Defects, Faults and Yield Loss: Simulation and Applications focuses on the core of the interface between manufacturing and testing, i.e., the contamination-defect-fault relationship. The understanding of this relationship can lead to better solutions of many manufacturing and testing problems. Failure mechanism models are developed and presented which can be used to accurately estimate probability of different failures for a given IC. This information is critical in solving key yield-related applications such as failure analysis, fault modeling and design manufacturing.

Over the years there has been a large increase in the functionality available on a single integrated circuit. This has been mainly achieved by a continuous drive towards smaller feature sizes, larger dies, and better packing efficiency. However, this greater functionality has also resulted in substantial increases in the capital investment needed to build fabrication facilities. Given such a high level of investment, it is critical for IC manufacturers to reduce manufacturing costs and get a better return on their investment. The most obvious method of reducing the manufacturing cost per die is to improve manufacturing yield. Modern VLSI research and engineering (which includes design manufacturing and testing) encompasses a very broad range of disciplines such as chemistry, physics, material science, circuit design, mathematics and computer science. Due to this diversity, the VLSI arena has become fractured into a number of separate sub-domains with little or no interaction between them. This is the case with the relationships between testing and manufacturing. From Contamination to Defects, Faults and Yield Loss: Simulation and Applications focuses on the core of the interface between manufacturing and testing, i.e., the contamination-defect-fault relationship. The understanding of this relationship can lead to better solutions of many manufacturing and testing problems. Failure mechanism models are developed and presented which can be used to accurately estimate probability of different failures for a given IC. This information is critical in solving key yield-related applications such as failure analysis, fault modeling and design manufacturing.

One of the keys to success in the IC industry is getting a new product to market in a timely fashion and being able to produce that product with sufficient yield to be profitable. There are two ways to increase yield: by improving the control of the manufacturing process and by designing the process and the circuits in such a way as to minimize the effect of the inherent variations of the process on performance. The latter is typically referred to as "design for manufacture" or "statistical design." As device sizes continue to shrink, the effects of the inherent fluctuations in the IC fabrication process will have an even more obvious effect on circuit performance. And design for manufacture will increase in importance. We have been working in the area of statistically based computer aided design for more than 13 years. During the last decade we have been working with each other, and individually with our students, to develop methods and CAD tools that can be used to improve yield during the design and manufacturing phases of IC realization. This effort has resulted in a large number of publications that have appeared in a variety of journals and conference proceedings. Thus our motivation in writing this book is to put, in one place, a description of our approach to IC yield enhancement. While the work that is contained in this book has appeared in the open literature, we have attempted to use a consistent notation throughout this book.