FAILURE MODES AND MECHANISMS

The reliability of an adhesive and its impact on the performance of an electronic assembly should be considered in the initial selection of the adhesive and the design of the system. The function that the adhesive must perform for a specific application, the environment it is expected to encounter, and its duration are all important. Various approaches may be used to predict and assure reliability. Key among these approaches is abasic understanding of possible failure modes and mechanisms. Most failure modes attributed to adhesives are now well imderstood and documented so that they can be avoided in the initial selection and qualification of the adhesive and in its processing. 

Secondly, accelerated tests can be used to qualify adhesives for specific applications, and the data from them can sometimes be extrapolated to longterm, real-time performance. Accelerated tests are also valuable as screen tests and as acceptance tests and are specified in material-procurement documents or in hardware acceptance specifications. Adherence to material and process specifications and their quality-control provisions is an essential element in assuring reliability. Life prediction throughmodeling is yet another approach, but it is outside the scope of this chapter. 

Lastly, there are extensive databanks of real-time performance for adhesives that have been used in numerous applications, various environments, and for extended periods of time— the so-called heritage data. 

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EIS has played an important role in fuel cell technology development, as one of the most important research tools for fuel cell diagnosis. EIS can help to identify the contributions from different components or processes to the total impedance of a PEM fuel cell. Such information is very helpful for understanding the fundamental processes within the fuel cell, the performance-structure relationships, and the contributions of various components to performance loss, as well as the associated failure modes and mechanisms EIS thus assists with fuel cell design optimization and selection of the most appropriate fuel cell operating conditions. In this chapter, we will present some typical examples of the applications of EIS in PEM fuel cell research, and an overview of EIS spectra analysis. 

It should be noted that in using MIL-HBK-217, the rehability predictions are based on empirical data for different component types and do not necessarily take into account the rehabihty of adhesive attached and interconnected components. The effect of the adhesive and its various possible failure modes and mechanisms on the reliability of devices under both operating conditions and long-term accelerated conditions should be considered a part of the equation. 

Besides an understanding of the basic failure modes and mechanisms, important in the initial selection of adhesives, qualification and strict adherence to materials and processes specifications and work instructions are an integral part of the rehability process. The process begins with the design guidelines and requirements for a specific application. Qualification criteria and test specifications must then be generated and the adhesives selected must be qualified. In addition, materials specifications or... 

Conventional layer classification is the first step for product analysis. Then, the related failure mode and mechanism, environmental and load conditions, and other information should be determined to conduct performance simulation in component level. Through the transfer function between system and component levels, performance simulation in system level can be carried out, collecting simulated performance data varying with time under specific conditions. Finally, modelling the degradation process with consideration of the failure threshold is to produce the model set M,. Noting that theoretically physical model can be established for product with simple failure mechanism, while modem engineering tools should be used for complicated products. Thus, the model set M, can be analytical functions or data-driven models. 

He has authored or co-authored over 85 publications in the areas of microelectronics packaging and a book on Failure Modes and Mechanisms in Electronic Packages published by Chapman and Hall. He has seven patents and 15 invention disclosures. He received the Third IBM Invention Achievement Award, an Excellence Award, and a Fourth Level Author Recognition Award. During 1974-1978, he was on the faculty of Ohio Dominican College, Columbus, Ohio, as assistant professor. He is currently an adjunct faculty at the University of Texas at Arlington in the Mechanical and Aerospace Engineering Department. 

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