Industrial statistics applications in the semiconductor industry: some examples. (11th December 2012)

• Record Type: Journal Article
• Authors: Kenett, Ron S.; Zacks, Shelemyahu; Borgoni, Riccardo; Deldossi, Laura; Radaelli, Luigi; Zappa, Diego
• Is Part Of: Applied stochastic models in business and industry. Volume 29:Number 4(2013:Jul./Aug.)
• Page Start: 319
• Page End: 333
• Publication Date: 2012-12-11
• Subjects: Stochastic analysis -- Periodicals; Stochastic processes -- Periodicals; Business mathematics -- Periodicals; Finance -- Mathematical models -- Periodicals; Industrial management -- Mathematical models -- Periodicals; 338.00151923
• DOI: 10.1002/asmb.1959
• Languages: English
• ISSNs: 1524-1904

Abstract

<abstract abstract-type="main" id="asmb1959-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p id="asmb1959-para-0001">The semiconductor industry ranges from the design and production of semiconductors on silicon wafers to automatic placement robots that insert semiconductor devices on hybrid microcircuits.Wafers consist of electronic circuits or chips that are characterized by electrical and mechanical characteristics. Process modeling and simulations provide predictions of geometries and material properties of semiconductor devices and wafer structures and help design and improve manufacturing processes such as photolithography, etching, deposition, and ion implantation. In this paper, we focus on three application areas of industrial statistics to the semiconductor industry. These are: (1) process capability indices, (2) process monitoring, and (3) multivariate statistical process control. We refer to two case studies that set a context and provide examples to the presented techniques. Copyright © 2012 John Wiley &amp; Sons, Ltd.</p> </abstract>