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World Abstracts on Microelectronics and Reliability
large compared to two-state device systems, availability is not obtained within a reasonable computation time. So here we have considered some simple models of three-state device systems to obtain availabilities.
A statistical approach to quality control of non-normal lithographical overlay distributions. R. M. BOOTH, JR, K. A. TALLMAN,T. J. WILTSHIRE and P. L. YEE. IBM Journal o f Research and Development, 36(5), 835 (1992). To achieve the high reliability and performance required by integrated circuit (IC) chips in IBM Enterprise System/900 tm processors, lithography tool centerline overlay variations between masking levels were specified at +0,3 pm, and circuit design images were transferred with 5 × step-and-repeat photolithography tools. In contrast to data obtained from 1 x lithography tools, the level-to-level overlay data which characterize deviations from circuit design rules did not fit a normal distribution, and quality control was not achieved with traditional statistical procedures. A methodology was empirically developed which transformed measured data into worst-case overlay points and approximated the data by a gamma distribution. More than 80% of the worst-case distributions were fit by the gamma distribution. The transformation of chip worst-case overlay data and the quality control testing application to 5 × step-and-repeat lithography tool processes are described in this paper.
governing its implementation. In particular, by the lack of statistical training of the experts and the high demands on their time. The use of a discretized life distribution provides more flexibility, is more comprehendible by the experts in the elicitation stage, and greatly reduces the computation in the combination and updating stages. The methodology is Bayes, using the Dirichlet distribution as the prior distribution for the elicited discrete lifetime distribution. Methods are described for incorporating information concerning the expertise of the experts into the analysis.
Deterministic reliability-modeling of dynamic redundancy. KLAUS D. HEIDTMANN. IEEE Transactions on Reliability, 41(3), 378 (1992). As more sophisticated systems are developed, powerful techniques for modeling their reliability are necessary. This paper-• applies temporal logic, an extension of the traditional Boolean logic, to deterministic reliability modeling and probabilistic analysis of systems with dynamic redundancy. • demonstrates the usefulness of the new method for solving the stated problems.
Temporal logic has been proposed as a useful tool for reasoning about computer software and hardware. Temporal logic expresses logical operators corresponding to time-dependent concepts such as always and sometimes. This recognized and versatile formalOn the introduction of fuzzy inference to reliability analysis method. TADASH! MURATO and EISAKU ism can describe dynamic behavior in a simple and SHIMABUKURO.Proceedings o f the 22nd Symposium on elegant fashion; it supports reliability modeling and Reliability and Maintainability, Tokyo, Japan. Union probabilistic reliability analysis, and, in particular, it of Japanese Scientists and Engineers, 57 (June 1992). provides a reasonable means for describing redunThere are many fuzzy data in reliability analysis, so dancy forms in dynamic systems. Hence, this new that we sometimes get a qualitative calculation un- approach fits best for many applications of reliability willingly. Recently, a lot of the controlled equipment modeling and analysis. with a fuzzy inference are produced, for example home-electronic equipment, cameras and so on. In A generalization of consecutive-k-out-of-n : F systems. this paper, the fuzzy inference technique is introduced THOMAS K. BOEHME, ANDREAS KOSSOW and to some reliability analysis methods, for example WOLFGANGPREUSS. IEEE Transactions on Reliability, F M E A method, FTA method and Weibull analysis. 41(3), 451 (1992). A linear (m, n)-Iattice system conUsefulness and some problems in those methods are sists of m . n elements arranged like the elements of described in this paper. a (m, n)-matrix, i.e., each of the m rows includes n elements, and each of the n columns includes m Expert judgement in maintenance optimization. JAN M. elements. A circular (m, n)-lattice system consists of VAN NOORTWIJK, ROMMERT DEKKER, ROGER M. m circles (centred at the same point) and n rays. The COOKEand THOMASA. MAZZUCm. IEEE Transactions intersections of the circles and the rays represent the on Reliability, 41(3), 427 (1992). This paper proposes elements, i.e., each of the circles includes n elements a comprehensive method for the use of expert opinion and each of the rays has m elements. A (linear or for obtaining lifetime distributions required for main- circular) (m, n)-lattice system is a (linear or circular) tenance optimization. The method includes pro- connected-X-out-of -(m, n ) : F lattice system if it fails cedures for the elicitation of discretized lifetime whenever at least one subset of connected failed distributions from several experts, the combination of components occurs which includes failed components the elicited expert opinion into a consensus distri- connected in the meaning of connected-X. The paper bution, and the updating of the consensus distri- presents some practical examples and the reliability bution with failure and maintenance data. The formulas of simple systems using results of consecumethod was motivated by the practical circumstances tive-k-out-of-n : F systems.