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Article
Publication date: 17 April 2001

Ken Nishina

This paper considers a recent environment in the manufacturing process in which data in large amounts can be obtained on‐line in real‐time. Under this environment an on‐line…

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Abstract

This paper considers a recent environment in the manufacturing process in which data in large amounts can be obtained on‐line in real‐time. Under this environment an on‐line real‐time Statistical Process Control (SPC) scheme equipped with detection of a process change, change‐point estimation, and recognition of the change pattern is proposed. The proposed SPC scheme is composed of a Cusum chart, filtering methods and Akaike Information Criterion (AIC). We examine the performance of this scheme by Monte Carlo simulation and show its usefulness.

Details

Asian Journal on Quality, vol. 2 no. 1
Type: Research Article
ISSN: 1598-2688

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Article
Publication date: 15 June 2012

Hironobu Kawamura, Ken Nishina, Masanobu Higashide and Tomomichi Suzuki

This paper aims to clarify adequate control characteristics for using a control chart on the basis of a case study of the low‐pressure chemical vapor deposition (LPCVD) process…

293

Abstract

Purpose

This paper aims to clarify adequate control characteristics for using a control chart on the basis of a case study of the low‐pressure chemical vapor deposition (LPCVD) process, which is one of the semiconductor manufacturing processes.

Design/methodology/approach

The paper opted for a simulation study using the data generated by EWMA model and the real data obtained from the LPCVD process.

Findings

The paper provides adequate control characteristics for control charts. It suggests that it is desirable to employ both the quality characteristic and the process rate for monitoring when the process was modeled by the EWMA model. Furthermore, if only one control characteristic is employed, then the process rate is the most adequate characteristic.

Originality/value

This paper newly proposes the process rate as a control characteristic for control charts.

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