The most advanced thermal barrier coating (TBC) systems for aircraft engine and power generation hot section components consist of EBPVD applied yttria stabilized zirconia and platinum modified diffusion aluminide bond coating. Thermally-sprayed ceramic and MCrAlY bond coatings, however, are still used extensively for combustors and power generation blades and vanes. This paper highlights the key features of plasma spray and HVOF, diffusion aluminizing and EBPVD coating processes. The coating characteristics of thermally sprayed MCrAlY bondcoat as well as low density and dense vertically cracked (DVC) Zircoat TBC are described. Essential features of a typical EBPVD TBC coating system, consisting of a diffusion aluminide and a columnar TBC, are also presented. The major coating cost elements such as material, equipment and processing are explained for the different technologies, with a performance and cost comparison given for selected examples.

High volume products in manufacturing require fast yield learning, root cause identification, and verification that process or tool problems are fixed. Yield losses of 1% correspond to very large dollar losses. Therefore, it is important to have sophisticated data analysis tools that handle large volumes of data to drive higher yields. This paper will present our methodology for defining yields, assessing wafer yield signatures, and using data analysis tools to determine tools or processes which drive yield loss. A SAS based data analysis tool will be shown which can identify tool or process related problems causing abnormalities in parametrics and impacting yield. Case studies illustrating the usefulness of the tool are shown for a Synchronous Dynamic Random Access Memory (SDRAM) product from our wafer fab. In the final analysis, it is clear that an efficient data analysis approach utilizes resources most effectively and pinpoints yield problems with minimal cycle time.

Evaluation of Scanning Electron Microscopes (SEMs) was initiated for the purpose of purchasing a SEM that would improve the productivity of scanning electron microscopy during the cycle of analysis and deprocessing of semiconductor devices in a failure analysis lab. In addition to the need for high image resolution at low electron acceleration voltages, an accurate motorized stage is a major evaluation factor. It is necessary for the analyst to drive directly to a known location such as a memory cell with a high assurance that the site of interest was found. There are two main areas of focus in this paper. First, our SEM evaluation methodology will be presented along with the results of our evaluation. Second, the technology associated with motorized stages will be discussed in light of our requirements for a motorized, highly accurate stage. As a byproduct of this evaluation, this paper is presented so as to push the SEM industry to offer a SEM with an accurate stage for subhalfmicron products at reasonable cost.