Anorectal Malformations in Children: Embryology, Diagnosis, Surgical Treatment, Follow-Up

The 2 nd edition of defect oriented testing has been extensively updated. New chapters on Functional, Parametric Defect Models and Inductive fault Analysis and Yield Engineering have been added to provide a link between defect sources and yield. The chapter on RAM testing has been updated with focus on parametric and SRAM stability testing. Similarly, newer material has been incorporated in digital fault modeling and analog testing chapters. The strength of Defect Oriented Testing for nano-Metric CMOS VLSIs lies in its industrial relevance.

datamining And Diagnosing Integrated Circuit Fails Addresses The Problem Of Obtaining Maximum Information From (functional) Integrated Circuit Fail Data About The Defects That Caused The Fails. It Starts At The Highest Level From Mere Sort Codes, And Drills Down Via Various Data Mining Techniques To Detailed Logic Diagnosis. The Various Approaches Discussed In This Book Have A Thorough Theoretical Underpinning, But Are Geared Towards Applications On Real Life Fail Data And State Of The Art Ics. This Book Brings Together A Large Number Of Analysis Techniques That Are Suitable For Ic Fail Data, But That Are Not Available Elsewhere In A Single Place. Several Of The Techniques, In Fact, Have Been Presented Only Recently In Technical Conferences.

datamining And Diagnosing Integrated Circuit Fails Begins With A Discussion Of Sort Codes And Yield Analysis. It Then Discusses Various Data Mining Techniques Centered On Fail Syndrome Commonalities And The Statistics Of Embedded Object Fails. It Gives A Thorough Discussion Of The Area Dependence Of The Yield And Of The Recognition Of Spatial Patterns Of Failing Die Or Embedded Objects. Next, It Gives A Detailed Analysis Of The Relationship Between Defect Coverage And Yield. It Ends With A Description Of State Of The Art Logic Diagnosis Techniques.

the Purpose Of The Book Is To Bring Together In One Place A Large Number Of Analysis, Data Mining And Diagnosis Techniques That Have Proven To Be Useful In Analyzing Ic Fails. The Descriptions Of The Techniques And Analysis Routines Is Sufficiently Detailed That Profession Manufacturing Engineers Can Implement Them In Their Own Work Environment. There Are Many Techniques For Analyzing Ic Fails, But They Are Scattered Over The Professional Ic Test And Diagnosis Literature, And In Various Statistics And Data Mining Handbooks. Moreover, Many Data Mining Techniques That Are Standard In Other Data Analysis Environments, And That Are Appropriate For Analyzing Ic Fails, Have Not Yet Been Employed For That Purpose. There Is A Clear Need For A Single Source For All These Analysis Techniques, Suitable For Professional Ic Manufacturing And Test Engineers.

Data Mining and Diagnosing IC Fails addresses the problem of obtaining maximum information from (functional) Integrated Circuit fail data about the defects that caused the fails. It starts at the highest level from mere sort codes, and drills down via various data mining techniques to detailed logic diagnosis. The various approaches discussed in this book have a thorough theoretical underpinning, but are geared towards applications on real life fail data and state of the art ICs. This book brings together a large number of analysis techniques that are suitable for IC fail data, but that are not available elsewhere in a single place. Several of the techniques, in fact, have been presented only recently in technical conferences.Data Mining and Diagnosing IC Fails begins with a discussion of sort codes and yield analysis. It then discusses various data mining techniques centered on fail syndrome commonalities and the statistics of embedded object fails. It gives a thorough discussion of the area dependence of the yield and of the recognition of spatial patterns of failing die or embedded objects. Next, it gives a detailed analysis of the relationship between defect coverage and yield. It ends with a description of state of the art logic diagnosis techniques.The purpose of the book is to bring together in one place a large number of analysis, data mining and diagnosis techniques that have proven to be useful in analyzing IC fails. The descriptions of the techniques and analysis routines is sufficiently detailed that profession manufacturing engineers can implement them in their own work environment. There are many techniques for analyzing IC fails, but they are scattered over the professional IC test and diagnosis literature, and in various statistics and data mining handbooks. Moreover, many data mining techniques that are standard in other data analysis environments, and that are appropriate for analyzing IC fails, have not yet been employed for that purpose. There is a clear need for a single source for all these analysis techniques, suitable for professional IC manufacturing and test engineers. front-matter......Page 1 01-Introduction......Page 19 02-Functional and Parametric Defect Models......Page 41 03-Digital CMOS Fault Modeling......Page 86 04-Defects in Logic Circuits and their Test Implications......Page 128 05-Testing Defects and Parametric Variations in RAMs......Page 168 06-Defect-Oriented Analog Testing......Page 241 07-Yield Engineering......Page 304 08-Conclusion......Page 331 back-matter......Page 339 "The purpose of the book is to bring together in one place a large number of analysis, data mining and diagnosis techniques that have proven to be useful in analyzing IC fails. The descriptions of the techniques and analysis routines is sufficiently detailed that profession manufacturing engineers can implement them in their own work environment."--Jacket