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Other Abstracts
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FabTime Cycle Time Management
Newsletter Abstracts - Volume 8 (10 Issues)
In this month’s newsletter we are pleased to announce
a FabTime case study that was published by one of our
suppliers. Our software tip of the month is about displaying
chart data tables directly on FabTime home page tabs. We
have a plethora of subscriber discussion in this issue,
including a response to an ongoing topic about modeling
cluster tool behavior, two responses to a question about
managing combined production and development fabs, and
two detailed responses to last month’s article about
cycle time benchmarking.
In our main article this month, written by Frank
Chance, we propose a fab cycle time improvement checklist.
The idea is to help codify cycle time improvement practices,
so that they become repeatable. The seven items in the
checklist include identifying baseline cycle time metrics,
finding metrics that indicate current and future cycle
time problems, and looking for root causes. These, and
other steps, are discussed.
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In this issue we have a brief followup to an earlier
announcement, to remind you about the upcoming launch of
the Fab Engineering & Operations Magazine, as well as a
job change announcement from V.A. Ames. Our FabTime tip
of the month is about the use of new formatting controls
to enable smaller home page charts. We have subscriber
discussion about managing production and development
activities in the same fab, loading and managing batch
tools, and varying lot sizes in the fab.
Because we have quite a bit of subscriber discussion
this month, we bring you a relatively short main article.
We discuss some of the challenges of calculating cycle
time benchmark data. Specifically, we review the two
primary metrics currently used for benchmarking across
fabs and technologies, X-factor and days per mask layer
(DPML), and discuss specific computational issues that
apply to each one. We also discuss the conversion ratio
between the two metrics. Our hope is that this article
will spur further discussion, which will in turn help
people who are looking to benchmark and improve their
cycle times.
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This month we have community announcements about a
FabTime demo offer and some upcoming industry meetings.
Our FabTime software tip of the month is about using
FabTime to predict when lots will complete processing
in the fab. We also have some subscriber discussion
regarding batch tools, a continuation of an earlier
topic.
In our main article this month, written by Professor Scott
Mason, we discuss the impact that the way lots are
released into a wafer fab can have on performance.
We provide an overview of workload (flow) control
terminology, and then briefly discuss both push- and
pull-based methods. Finally, after discussing recent
results from case studies, we conclude by returning to
last month’s newsletter topic, dispatching in wafer fabs,
to discuss advanced dispatching strategies for linked
process steps. We conclude with three recommendations for
evaluating lot release policies used in fabs.
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In this issue, we have a community announcement about a
new electronic publication that we think will be of particular
interest to subscribers of this newsletter. It’s targeted to
established fabs, rather than focusing only on the bleeding
edge of technology. Our FabTime user tip of the month
concerns exploiting the archive of past FabTime tips from
inside the software. We have two subscriber responses to
last montht’s issue – one about holding batch tools idle,
and the other about cluster tools.
Our main article this month comes from our esteemed guest
contributor (introduced last month), Professor Scott Mason
of the University of Arkansas. Professor Mason is a national
expert on dispatching, scheduling and manufacturing performance
improvement for wafer fabs. This month, Professor Mason
discusses scheduling and dispatching. He provides an overview
of scheduling and dispatching terminology, discusses the
state of the practice with respect to fab dispatching,
briefly outlines FabTimet’s dispatching functionality, and
then presents some case study results from across the industry
describing the positive impact that effective dispatching can
have on a fab. We hope that you find this article useful,
and we welcome your feedback.
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In our community news section this month, we summarize information
about four upcoming conferences that have relevance for
fab manufacturing performance improvement. Our FabTime
software tip of the month is about restricting FabTime
data access for individual users. We also have a subscriber
discussion topic, introduced by Walt Trybula, related to
last month’s question about fab utilization. This
month’s main article, about cluster tools, was written by Professor Scott
Mason of the University of Arkansas, a national expert on
dispatching, scheduling and manufacturing performance
improvement for wafer fabs. He provides an overview of
cluster tools, including a discussion of some of their
pros and cons, and then discuss approaches (both academic
and practical) for modeling and analyzing cluster tools
in order to develop estimates of tool capacity and cycle
time. He also shows, by example, the way that adding a
chamber can sometimes increase capacity, while decreasing
cycle time, for a cluster tool, by reducing blocking.
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Our FabTime software tip of the month this issue
is about using FabTime’s new tool qualification charts
to identify single-path operations in the fab. In our
subscriber discussion forum, we have an extended discussion
with Dov Kotlar of Tower Semiconductor about metrics for
measuring fab utilization. In our main article this month
we tackle the subject of WIP bubbles. People ask us occasionally:
“how do I manage WIP bubbles in the fab?”. A WIP bubble is a
large pile of WIP, usually in queue at a particular tool-group
or small set of tool-groups. WIP bubbles occur due to a
variety of causes, the most notable of which is extended
downtime on a one-of-a-kind tool. In this article, we
discuss common causes of WIP bubbles, methods for avoiding
them, early WIP bubble indicators, and potential methods
for mitigating their effect. Several of the latter involve
making dispatching decisions that encompass information
about downstream operations. We hope that yo’ll find
this article useful, and we would love to hear your feedback.
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In this issue we have a software user tip of the month
about copying user accounts, and two subscriber responses
to last month’s issue about estimating operation-level
cycle times. In our main article this month, we address sources
of variability in wafer fabs. Variability is one of the
main causes of fab cycle time. Variability affects the
shape of the operating curve of cycle time vs. tool
utilization. By reducing variability, we can move the
knee of the operating curve for a fab, achieving a lower
cycle time at the same throughput rate. Variability
reduction is a relatively inexpensive way to improve
cycle time, because it does not require the purchase
of capital equipment, or any reduction in starts. However,
in order to reduce variability in your fab, you need to
be able to identify the specific sources of variability.
In this article, we review some of the major sources of
variability in fabs, and suggest several general
methods for reducing it. We then discuss in detail
metrics that you can use for quantifying and identifying
specific variability problems in your fab.
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This month we have two community announcements and
one response to last month’s article about making morning
meetings more effective. Our FabTime software user tip of
the month is about tracking cumulative hold time across
lots. In our main article this month we discuss the
reasons for needing planned operation-level cycle time
values, and review several potential methods for
generating them. Methods discussed include using a
straight multiple of theoretical, across all steps,
using queueing or simulation models to estimate step-specific
values, and using actual historical data. We then discuss
some technical issues related to the use of actual data,
specifically the selection of using mean or median value
from a set of actual observations. We hope that you will
find this discussion useful.
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In our main article this month, written by Frank Chance,
we discuss the ever-popular, but rarely examined in the
literature, fab morning meeting. Nearly all fabs that we
know hold a daily morning production meeting. Our
hypothesis is that fabs that hold effective morning
meetings are also likely to be effective at achieving
their manufacturing goals. A morning meeting is effective
if it routinely achieves it stated purpose, whether that
is to distribute information, hold individuals accountable,
make decisions, brainstorm solutions, or another purpose
specified by fab management. In this article, we examine
the purposes for morning meetings, and explore behaviors
that may make meetings ineffective. Our goal is to
motivate you to examine and improve the effectiveness
of your morning production meetings.
In this issue we also have a call for papers for the
2007 MASM conference, to be held in Scottsdale, Arizona in
September. Our software user tip of the month involves
using FabTime to track on-time delivery performance. We
have no subscriber discussion, though we have been having
some informal discussions with people about wafer size
transitions and benchmarking, which may be reflected in
future issues.
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In our main article this month we address a problem
that we’ve heard mentioned at several companies.
The issue is that new, low volume products often incur
long cycle times, because the traditional performance
measures in fabs allow them to slip through the cracks.
We present a series of recommendations for mitigating
this effect. We welcome your feedback.
Our software tip of the month is about how to cross-slice
move and WIP data in a single chart data table (to look at,
for example, WIP by priority within each area on the same
page). We have several subscriber discussion topics. Anonymous
subscribers wrote in with new questions concerning justifying
additional capacity to management, and identifying and
analyzing your own fab’s top three cycle time problems.
We also have a response from David Jimenez of WWK to a
question posed last month about labor modeling for fabs.
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