Statistical process control in semiconductor manufacturing
Article Abstract:
Traditionally, research on integrated circuits (IC) has focused on improving product performance rather than on improving efficiency of production. Standard scientific manufacturing processes are finally being implemented in IC production. Statistical process control (SPC) is a key part of this trend. Introduced in the 1930s by Walter Shewhart, SPC uses a control chart to transfer responsibility to the factory floor operator. SPC gauges production performance by flagging statistically significant deviations from historical norms. SPC postulates an assignable, or special, cause behind any significant deviation. Contemporary SPC techniques make substantial use of computers. In IC manufacturing, SPC techniques are used for such tasks as monitoring wafer thicknesses. SPC in IC manufacturing is discussed in detail.
Publication Name: Proceedings of the IEEE
Subject: Electronics
ISSN: 0018-9219
Year: 1992
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Discrete-index Markov-type random processes
Article Abstract:
Markov-type process models are useful in characterizing the 'state' in physical systems of various types, including discrete-state queues and continuous-state dynamical systems. The processes can also be used to represent spatial continuity in statistical image models, and Markov-type two-dimensional random processes, or random fields, have been used often for image modeling. Here the random process and field models themselves are studied rather than how they can be fitted to data. The three major classes examined are strict-sense Markov models, wide-sense Markov models and simultaneous autoregressive models. Among the special classes investigated are Markov-P, Markov random field, Gibbs random field, Markov mesh random field, causal, unilateral and bilateral Markov models.
Publication Name: Proceedings of the IEEE
Subject: Electronics
ISSN: 0018-9219
Year: 1989
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