SEMI E89 - Guide for Measurement System Analysis (MSA) -

Abstract

NOTICE: This Standard or Safety Guideline has an Inactive Status because the conditions to maintain Current Status have not been met. Inactive Standards or Safety Guidelines are available from SEMI and continue to be valid for use.

NOTICE: This Document was reapproved with minor editorial changes.

The purpose of this Guide is to provide a consistent set of terminology and describe a simplified, but constructive, experimental approach to planning and performing a measurement system analysis (MSA).

The goal of an MSA is to characterize the performance capability of the measurement system (MS) as it is intended to be used in a manufacturing or laboratory setting.

Accurately identifying the MS bias and the size and nature of all sources of variability allows one to determine whether the MS is capable of performing its intended function. Moreover, a well-designed MSA can be used to identify and quantify areas that need the most improvement.

This Guide covers procedures for determining specific measures of MS capability including:

• measurement variability (i.e., reproducibility) under a variety of conditions, including:

• effects of repeatability,

• load-unload, and

• time, and

• bias, including bias-related

• linearity,

• stability, and

• matching tolerance.

This Guide also covers secondary metrics such as precision-over-tolerance (P/T) ratio and signal-to-noise ratio (SNR).

The primary focus of this Guide is on determining measurement capability of automated wafer MSs under normal operating conditions, but the definitions and methodologies are extendible to many other measurement situations involving automated measurements on units such as processed dice, packaged devices, flat panel displays, piece parts, etc.

While there is no universally accepted correct way to conduct an MSA, the approach described in this Guide is supported in the technical literature (see § 11) and congruent with practices advocated in ISO 5725-2. The procedures given in this Guide represent an approach to the conduct of an MSA and provide basic reference methods that should serve for a variety of applications. Other methods may be appropriate in certain circumstances.

The procedures in this Guide that are intended to separate the various sources of nonsystematic (i.e., random) errors are based on the use of factorial experiments and analysis of variance (ANOVA). Because the primary focus of this Guide is on evaluation of automated MSs, the variability introduced by different operators is expected to be minimal.

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