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SEMI M55.2-0705 © SEMI 2005 4 Property Dimension Units FORMAT OF ID-STRING Option 1:”OCR Checksum Character” #2, #4 NNNNNNNNNNSSCC (14 characters total) NNNNNNNNNN: (10 characters) supplier defined ID of wafer, with a d …

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SEMI M55.2-0705 © SEMI 2005 3
Table 3 Polished Wafer Defect Limits
Item Characteristics Maximum Defect Limit Test Condition Note
Front Surface
1 visible scratches None high intensity, unaided eye 1
2 pits (number) 10 high intensity, unaided eye 1
3 orange peel (area) 10% diffuse, unaided eye 1
4 particles (number) 6 high intensity, unaided eye 1
5 edge chips and indents (number)
3 with maximum length and
width 1.0 mm
Back Surface
3
6 edge chips (number)
3 with maximum length and
width 1.0 mm
7 visible surface inhomogeneity defined by customer and supplier 2
Bulk
8 cracks (number) None diffuse, unaided eye
9 micropipes (mean density) defined by customer and supplier
10 planar defects,
spacing >2 mm (number)
15 diffuse, unaided eye 1
11 planar defects,
spacing 2 mm (affected area)
10% diffuse, unaided eye 1
12 crystallite (area) 5% diffuse, polarisers 1
13 foreign polytypes (area) 10% diffuse 1
Cumulative Defect Area
14 all listed defects of type “area” total 10% 1
#1
The Edge-Exclusion X (See Figure 1 of SEMI M55) is 1 mm.
#2
Dependant on backside finish.
#3
The back side finish properties are not specified.
Table 4 Laser Marking Requirements (see Figure 8 of SEMI M55)
Property Dimension Units
GEOMETRY
dimension A 0.5 mm
dimension B 2.0 mm
dimension C 10.0 mm
#1
MARKING DEPTH
100
µm target value 30µm
CHARACTER SET Defined by SEMI M12 character font and proportions (“SEMI OCR”), not
font size
CHARACTER DIMENSIONS
Option 1: “large”
#3, #4
dimensions according to SEMI M12, readable with
unaided eye
Character Height
1.624 0.025
mm
Character Spacing
1.420 0.025
mm
width and thickness are defined by the proportions
given in SEMI M12
Option 2: “small”
#2, #4
dimensions according to SEMI M13, readable with
unaided eye
Character Height
0.812 0.025
mm
Character Spacing
0.710 0.025
mm
width and thickness are defined by the proportions
given in SEMI M13
SEMI M55.2-0705 © SEMI 2005 4
Property Dimension Units
FORMAT OF ID-STRING
Option 1:”OCR Checksum
Character”
#2, #4
NNNNNNNNNNSSCC
(14 characters total)
NNNNNNNNNN: (10 characters)
supplier defined ID of wafer, with a dash as
separator. Unused characters are filled with dash
characters. Alphanumeric.
SS: (2 characters)
Supplier Identification Code as defined in SEMI
AUX1. Alpha only.
CC: (2 characters)
Checksum Characters generated by the algorithm
defined in SEMI M12.
The first character is alpha only, the second
numeric only.
Option 2: “manual reading”
#3, #4
NNNNSS to
NNNNNNNNNNSS
(6 to 12 characters total)
NNNNNNNNNN: (4 to 10 characters)
supplier defined ID of wafer, with a dash as
separator. Alphanumeric with a dash as fill
character.
SS: (2 characters)
Supplier Identification Code as defined in SEMI
AUX1. Alpha only.
#1
The total width of the marking window is twice dimension C.
#2
Option is intended for use with automated systems including OCR-techniques.
#3
Option is intended primarily for manual reading of the wafer ID and allows shorter ID-strings which are preferable for manual reading. A
Supplier Identification Code is mandatory as the last two characters.
#4
Size and format options may be used in any combination.
NOTICE: SEMI makes no warranties or representations as to the suitability of the standards set forth herein for any
particular application. The determination of the suitability of the standard is solely the responsibility of the user.
Users are cautioned to refer to manufacturer’s instructions, product labels, product data sheets, and other relevant
literature, respecting any materials or equipment mentioned herein. These standards are subject to change without
notice.
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Copyright by SEMI® (Semiconductor Equipment and Materials
International), 3081 Zanker Road, San Jose, CA 95134. Reproduction of
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consent of SEMI.
SEMI M56-1103 © SEMI 2003 1
SEMI M56-1103
PRACTICE FOR DETERMINING COST COMPONENTS FOR
METROLOGY EQUIPMENT DUE TO MEASUREMENT VARIABILITY
AND BIAS
This practice was technically approved by the Global Silicon Wafer Committee and is the direct
responsibility of the North American Silicon Wafer Committee. Current edition approved by the North
American Regional Standards Committee on September 3, 2003. Initially available at www.semi.org
October 2003; to be published November 2003.
1 Purpose
1.1 In silicon manufacturing product disposition is
typically contingent on metrology equipment output.
For example, a piece of work may be shipped,
scrapped, or reworked based on information from one
or more measured output characteristics. A cost model
provides a mechanism for estimating the costs
associated with operating metrology equipment under
certain sets of assumptions and conditions.
1.2 This practice provides a standard methodology for
metrology equipment suppliers and users to determine
the cost due to misclassification of product because of
measurement variability and bias during testing of the
product for conformance to a specification.
1.3 This practice is intended to be useful for pre-
purchase evaluation of measurement equipment with
different P/T (Precision/Tolerance) ratios. It is also
intended to be useful when comparing the operation of
a single measurement instrument in different
throughput modes where P/T ratio changes with the
throughput mode utilized or other equipment setup
factors. This practice can help users select the optimum
cost solution based on their specific process capability
and requirements.
1.4 Neither traditional cost elements (e.g., equipment,
maintenance, operational, and staffing cost) nor product
cost data are included in the practice; it is intended that
each user should utilize appropriate data based on the
applicable business model for the facility.
2 Scope
2.1 This practice covers a methodology to determine
the costs associated with misclassification of product
due to variability and bias of measurement equipment.
These costs are associated with failing product that
conforms with specifications and passing product that
does not conform with specifications.
2.2 This practice can be applied to make relative cost
comparisons between two or more measurement gauges
operating under conditions specified by the user. These
conditions may include any aspects of the measurement
system affecting the measurement results directly or
indirectly (e.g., ambient conditions, throughput, recipe).
This practice can also be used to compare the relative
costs of a single instrument under different operating
conditions.
2.2.1 A measurement gauge is defined by a specific
realization of systems and subsystems required to make
measurements. Gauges that differ in at least one system
or subsystem may be considered different for the
purpose of comparison.
2.3 This practice can be applied to any metrology
equipment or to the metrology portion of any
equipment that includes metrology.
2.4 This practice covers the case in which the
metrology equipment is used to make binary decisions
about the item being measured, that is, only two
outcomes are possible (e.g., pass/fail, go/no-go,
ship/scrap). Models for decisions with more than two
outcomes, such as the binning of data, are beyond the
scope of this practice.
2.5 To apply the formulae in this practice, the user
must estimate either the probability density function
(PDF) or cumulative distribution function (CDF) of the
process characteristic or characteristics of interest. The
distributions can be based on a theoretical model or on
empirical information obtained from manufacturing
data.
2.6 To apply the formulae in this practice, the user
must be able to estimate all biases and variances
associated with the equipment being compared under
the specified operating conditions and with respect to
the process characteristic(s) of interest. These values
can be obtained from a measurement system capability
analysis (see SEMI E89).
2.7 To apply the methodology of this practice, the user
must estimate the costs of classification and
misclassification due to decisions made as a result of
measurements. Estimates of such costs are obtained
from the business model used to describe the
manufacturing process in which the measurements are
performed. Consequently, different users may arrive at
different estimates of costs because their computations
may contain different elements.