semi合集-English.pdf - 第947页
SEMI E124-1103 © SEMI 2003 2 NOTICE: Unless ot herwise i ndicated, all docum ents cited shall be the latest published versions. 5 Terminology NOTE 1: All of the metrics defined below should be calculated with r espect to…
SEMI E124-1103 © SEMI 2003 1
SEMI E124-1103
PROVISIONAL GUIDE FOR DEFINITION AND CALCULATION OF
OVERALL FACTORY EFFICIENCY (OFE) AND OTHER ASSOCIATED
FACTORY-LEVEL PRODUCTIVITY METRICS
This provisional guideline was technically approved by the Global Metrics Committee and is the direct
responsibility of the North American Metrics Committee. Current edition approved by the North American
Regional Standards Committee on July 27, 2003 and September 3, 2003. Initially available at www.semi.org
September 2003; to be published November 2003. Originally published July 2003.
1 Purpose
1.1 This guide describes metrics that show how well a
factory is operating compared to how well it could be
operating (for the given product mix). These metrics
can be used for tracking factory performance (in value-
added production) in a way that rewards good
operational decisions and that is not easy to adversely
manipulate. They can be used in a process of ongoing
improvement that can be visible to all levels of a
semiconductor manufacturing organization.
1.2 The metrics in this guide are intended for
evaluating the relative efficiency of factory production
after the factory is in production, not for capacity
analysis while the factory is being designed or
redesigned. However, some of these metrics can be
used in factory simulations for choosing equipment sets
and scheduling policies.
2 Scope
2.1 To evaluate the overall effectiveness of a factory,
there are at least three things in need of measurement:
production, utilization of assets, and costs. This guide
focuses on evaluating production; utilization of assets
and costs (as well as other economic factors) are
outside its scope. See Section R3-1.1 in Related
Information 3 for a discussion of metrics in other areas.
2.2 This guide describes metrics for an entire
integrated production line. Multiple production lines in
the same factory may be evaluated separately if they do
not share resources (such as material handling or
production equipment).
2.3 This guide is provisional because overall factory
efficiency (OFE) is a new concept. Once the metrics
have been validated by collecting data in production
factories, computing the metrics, and evaluating their
sensitivity to the data, this guide should be modified
and upgraded from provisional status (as specified in
the SEMI regulations). Also, additional supplemental
metrics may be defined, and the metric definitions
given here may be expanded to truly comprehend
assembly operations.
NOTICE: This standard does not purport to address
safety issues, if any, associated with its use. It is the
responsibility of the users of this standard to establish
appropriate safety and health practices and determine
the applicability of regulatory or other limitations prior
to use.
3 Limitations
3.1 In the context of this guide, it is important to note
that factory-level productivity is impacted greatly by
factors beyond the factory itself, including material
availability, efficiency of product device designs, and
customer demand.
3.2 The metrics in this guide are intended for
evaluating the overall efficiency of factory production,
not for diagnosing problems (or opportunities for
improvement) in the factory, although some component
metrics can be used that way. See Section R3-1.2 in
Related Information 3 for a discussion of the
differences between the two kinds of metrics.
3.3 This guide provides metrics and calculations for
measuring the overall productivity only of
manufacturing environments (such as wafer fabs, flat
panel factories, and some disk-drive production
facilities) in which product substrates move through the
factory with no assembly or disassembly processes.
These metrics can be applied in a post-wafer back-end
chip production facility if the lead frames are
considered to be consumable materials (not units of
production in their own right). However, in the future
this guide may be extended to comprehend other, more
complex manufacturing environments (including
assembly operations).
4 Referenced Standards
4.1 SEMI Standards
SEMI E10 — Specification for Definition and
Measurement of Equipment Reliability, Availability,
and Maintainability (RAM)
SEMI E79 — Standard for Definition and Measurement
of Equipment Productivity
SEMI E124-1103 © SEMI 2003 2
NOTICE: Unless otherwise indicated, all documents
cited shall be the latest published versions.
5 Terminology
NOTE 1: All of the metrics defined below should be
calculated with respect to the period being measured.
5.1 Definitions
5.1.1 actual throughput rate — the finished units out
divided by the total time (shows how fast finished
wafers flow out of the factory). See Equation 19.
5.1.2 availability efficiency (time divided by time) —
the fraction of total time that the equipment is in a
condition to perform its intended function (SEMI E79).
5.1.3 average cycle time — the (unweighted) average
of cycle time over all of the units of production in
finished units out.
5.1.4 average work in process (WIP) — the average
cycle time multiplied by the actual throughput rate
(shows how many eventually finished units of
production fill the “pipeline” on average). See
Equation 15.
NOTE 2: This metric is not an average of the WIP over time,
since that would include units that are later scrapped before
finishing.
5.1.5 balance efficiency — the critical WIP divided by
the process capacity (measures how well the equipment
sets are balanced). See Equation 5.
5.1.6 best-case cycle time — the larger of the
theoretical cycle time and the quotient of the average
WIP divided by the bottleneck throughput rate (shows
the best cycle time that the factory can do given the
WIP loading). See Equation 18.
5.1.7 best-case throughput rate — the smaller of the
bottleneck throughput rate and the quotient of the
average WIP divided by the theoretical cycle time
(shows the best throughput rate that the factory can do
given the WIP loading). See Equation 20.
5.1.8 bottleneck throughput rate (R
max
) — the upper
bound on the factory throughput rate imposed by the
current bottleneck equipment set. If a process change
for a product causes this metric to change, it should be
considered a different product for the purposes of
performing these computations. See Equation 17.
NOTE 3: This metric is similar to (but not the same as) the
theoretical unit throughput by recipe metric (see Section
5.1.32) from SEMI E79.
NOTE 4: This metric is not an average over the bottleneck
throughput rates of each product.
5.1.9 critical WIP (W
0
) — the theoretical cycle time
multiplied by the bottleneck throughput rate (gives the
WIP level that theoretically allows the factory to have
the highest throughput rate with the shortest cycle
time). See Equation 10.
5.1.10 cycle time — the amount of time a unit of
production spends as WIP in the factory.
5.1.11 finished units out — the number of units of
production that finish processing and testing during the
period being measured.
5.1.12 good unit equivalents (GUE) out — the
(possibly non-integer) number of units of production
required to contain all of the good product that exits the
factory during the period being measured. See
Equation 12.
5.1.13 line yield — the fraction of units leaving the
factory that have finished processing (measures relative
material losses such as scrapped units). See Equation 6.
5.1.14 normalized production efficiency — the
production efficiency to the power of the normalizing
exponent (measures the normalized efficiency of the
process with respect to factory dynamics). See
Equation 4.
5.1.15 normalizing exponent — power that normalizes
the production efficiency so that a value of ½ for
normalized production efficiency indicates that the
factory is performing at the level of the threshold case
(which divides a well run factory from one badly
operated). See Equation 9. See Sections R1-1.7 and
R1-1.8 in Related Information 1 for a discussion of the
meaning of the threshold case and a derivation of
mathematical expression for the normalizing exponent.
5.1.16 operational efficiency (time divided by time) —
the fraction of equipment uptime that the equipment is
processing actual units (SEMI E79).
5.1.17 overall equipment efficiency (OEE) (time
divided by time) — a metric of equipment performance,
expressing the theoretical production time for the
effective unit output divided by the total time (SEMI
E79).
5.1.18 overall factory efficiency (OFE) — the volume
efficiency multiplied by the yield efficiency (shows how
well a factory is operating compared to how well it
could be operating for the given product mix). See
Equation 1.
5.1.19 process capacity — the maximum number of
units of production that can be processed
simultaneously throughout the factory (including units
being transported by material handling vehicles). See
Equation 11.
5.1.20 production efficiency — the throughput-rate
and cycle-time efficiency multiplied by the WIP
SEMI E124-1103 © SEMI 2003 3
efficiency (measures the efficiency of production with
respect to factory dynamics). See Equation 8.
5.1.21 quality efficiency (time divided by time) — the
theoretical production time for effective units divided
by the theoretical production time for actual units
(SEMI E79).
5.1.22 scrapped units out — the number of units of
production (including broken units, external rework,
etc.) that exit the factory without finishing production
during the period being measured.
5.1.23 set of bottleneck equipment (F
e*
) — the
collection of production equipment of the same type
that has the highest average operational efficiency in
the factory during the period being measured. Elements
of this set are indicated by “f”, and the equipment type
is indicated by “e*”.
NOTE 5: This set of bottleneck equipment might not be the
equipment set (often the expensive lithography exposure
equipment) that was planned to be the bottleneck in the
factory, but rather the equipment set with the highest average
operational efficiency (the fraction of time in use when
available) during the period being measured. If another
equipment set experiences significantly lower availability
than expected, it might become the bottleneck. Thus, the sets
of bottleneck equipment may be different between two
adjacent time periods, and the set of bottleneck equipment for
the period combining the two adjacent periods may be
different from the other two sets.
5.1.24 set of equipment of type e (F
e
) — the collection
of production equipment of type e∈E in the factory.
Elements of this set are indicated by “f”.
5.1.25 set of equipment types (E) — the collection of
the different types of production equipment in the
factory, including metrology equipment and material
handling vehicles and conveyors. Elements of this set
(which are the different types of equipment) are
indicated by “e”.
NOTE 6: If units are transported manually between process
steps, then the human transporters (and any carts or
mechanized vehicles that they operate to perform the
movement) should be considered a type of equipment for the
purpose of computing the metrics in this guide. This is not
intended to dehumanize people, but to ensure that the manual
transport time is included in such metrics as theoretical cycle
time.
5.1.26 set of process steps of product type p on
equipment type e (S
pe
) — the collection of the different
process steps (including metrology inspection and
material handling transport) planned for a unit of
production of product type p on equipment of type e in
the factory. Elements of this set are indicated by “s”.
5.1.27 set of product types (P) — the collection of the
different types of products manufactured in the factory.
Elements of this set are indicated by “p”.
5.1.28 test yield — the fraction of units leaving the
factory that have finished processing and have passed
final testing (measures relative losses due to parametric
or functional failure). See Equation 7.
5.1.29 theoretical cycle time (T
min
) — the minimum
time required to process a unit of production through
the factory (including material handling transport time)
if the unit never has to wait for equipment or a vehicle
to become available and if sequence-dependent set-ups
never have to be performed. This is also known as the
raw process time. If a process change for a product
causes this metric to change, it should be considered a
different product for the purposes of performing these
computations. If more than one product (or process
flow) is represented in the output, an average is taken
over each of the products’ theoretical cycle time
weighted by the fraction of that product found in
finished units out. See Equation 16.
NOTE 7: This metric is similar to (but not the same as) the
theoretical production time per unit (THT) metric (see Section
5.1.30) used in SEMI E79 from CSM 21 and 42
1
.
5.1.30 theoretical production time per unit (THT) (time
per unit) — for a given production recipe performed by
a given processing module, the minimum time to
complete processing on one unit of production
assuming no efficiency losses are present. The
determination of theoretical production time per unit is
based on continuous operation of the processing
module, where the module is assumed to operate in an
ideal condition. For equipment cycles that
simultaneously process more than one unit, theoretical
production time per unit is the minimum time to
perform the cycle on an equipment load whose size is
optimized for throughput divided by the number of
units in that optimized load (CSM 21 and 42).
5.1.31 theoretical throughput rate — the smaller of the
bottleneck throughput rate and the quotient of the WIP
capacity divided by the theoretical cycle time (gives an
unreachable upper bound on the factory throughput
rate). See Equation 21.
5.1.32 theoretical unit throughput by recipe (units per
time) — for a given production recipe, the number of
units per period of time that theoretically could be
processed by the equipment. For each recipe,
1 CSM 21: Closed-Loop Measurement of Equipment Efficiency &
Capacity, 1995: and CSM 42: Productivity Metrics for Flexible-
Sequence Cluster Tools, 1998; Engineering Systems Research Center,
University of California, Berkeley
http://esrc.berkeley.edu/csm/csmreports.html.