FabTime Cycle Time Management
Newsletter Abstracts - Volume 5 (10 Issues)
Because we have extensive subscriber discuss this month,
our main article is relatively short. We turned for
inspiration to the responses to our cycle time issues
survey (in which we have been asking people “What is
the biggest cycle time problem in your fab?”). We
noticed a number of responses pointing towards management
behaviors that influence variability in the fab, at least
from the perspective of people working in the fab.
We’ve chosen to highlight these responses, and
discuss their impact on our “Traffic Cop”
cycle time management style recommendations.
In this issue we have an announcement about the
latest version of the software, as well as a short
recap of a recent industry conference. Our software
user tip of the month concerns methods for updating
home page chart data. In the subscriber discussion
forum we have several responses to last month’s
questions about paperless cleanrooms and the effect of
linked tools on 300mm cycle times, as well as a new
question about benchmarking for “single strand”
toolsets. (
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In our main article this month, we discuss using
data from the fab manufacturing execution system (MES)
to perform static capacity analysis. FabTime is in the
business of taking data from the MES, and using it to
provide information to the people who manage wafer fabs.
Our software takes updates from the MES in near real-time,
and stores the data in a separate database, making a
digital dashboard of charts available via web browser.
Recently, we have been working with our customers to
use this data to help them plan capacity. The primary
advantage of this approach is that most of the data is
already available and automatically updated to reflect
current fab conditions. This lets planners spend their
time generating and running scenarios, rather than
performing data entry to keep standalone capacity
models up to date.
This month we have an announcement related to past
issue abstracts (to make it easier for you to find
references to topics previously discussed in the
newsletter). Our software user tip of the month is
about generating a list of hot lots. We also have
subscriber discussion related to 300mm cycle times
(in response to last month’s issue) and paperless
cleanrooms. (
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In our main article this month, we discuss real-time
alerts sent to semiconductor wafer fab users to notify
them of particular conditions in the fab. We review pros
and cons of using these types of alerts at all, and then
describe several examples in detail (including hot lot
queue delay, early warning of lots due to reach time
limit, and critical tool idle with wip available).
Finally, we solicit subscriber feedback on the general
usefulness of alerts, and on other types of these
warning messages that might be useful in semiconductor
fabs.
This month we have several announcements, as well
as a considerable amount of subscriber discussion. Our
FabTime user tip of the month describes how to add a
chart from a shared home page tab to a user’s own home
page. Subscriber discussion topics include: capacity
planning for time links between process steps,
understanding 300 mm cycle time performance, assessing
the impact of downtime on fab performance, setting
targets for WIP and turns, and defining fab loading
in the presence of multiple near-bottlenecks. We also
have several responses to our question about the oldest
continuously operating wafer fab. (
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In our main article this month, we discuss metrics
for measuring the effect of tool downtime. If we
could eliminate downtime from our semiconductor
wafer fabs, we could increase throughput (where
the constraint tools have any downtime at all),
and improve cycle time at the same time. In this
article, we make a first pass at quantifying this
impact more formally, by measuring the increased
operation-level cycle time for lots that are in
queue when a tool goes down. We believe that better
understanding the cycle time cost from specific
downtime events could be helpful for fabs in deciding
where to focus tool improvement efforts.
This issue includes subscriber discussion related
to capacity planning, Dynamic X-Factor, WIP Utilization,
and metrics for measuring the effect of tool downtime.
Our FabTime user tip of the month concerns setting a
default time of day for newly generated interval-based
charts. (
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In our main article this month, we discuss increasing
semiconductor wafer fab throughput through improvements
in cycle time constrained capacity. The idea is that fabs
always have a buffer of planned idle time on tools,
designed to keep cycle times from getting out of control.
Through variability reduction, fabs can sometimes squeeze
this buffer, without increasing cycle time. In an up
market, this can lead to increased sales, from the same
equipment set. The financial benefit from this can be
substantial, and provides a clear justification for
variability reduction / cycle time improvement efforts.
In this issue’s subscriber discussion forum, we have
discussion concerning several previously introduced
topics: WIP Utilization Percentage, Dynamic X-Factor,
and the Closest-to-Completion-Time Dispatch Rule. Our
FabTime user tip of the month concerns setting filter
defaults. (
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In our main article this month, we propose a new wafer fab
metric for tracking shift-level use of individual tools by
operators, called WIP Utilization%. This metric was developed
jointly by Frank Chance of FabTime and Jimmy Martin of Analog
Devices. We define WIP Utilization% as Productive Time /
(Productive Time + Standby WIP Waiting Time). This is similar
to our definition of Utilization, which is Productive Time /
(Productive Time + Standby Time). However, in the denominator,
we only include the standby time in which WIP is waiting for
the tool. WIP Utilization% will approach 100% if, whenever
WIP is waiting, and a qualified tool is available, the WIP
is processed as soon as possible. Driving WIP utilization to
100% generally minimizes per-visit cycle times through the
tool, and helps to maximize shift-level throughput. This metric
overcomes several shortcomings of the standard utilization
definition as a shift-level metric for operators in semiconductor
wafer fabs.
WIn this issue’s subscriber discussion forum, we have several
responses to last month’s subscriber discussion question, about
breaking up standby time according to whether or not WIP is
available. We also have a new subscriber discussion question
about the closest-to-completion-time dispatch rule. (
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In our main article this month, we discuss ideas for presenting
semiconductor wafer fab performance data. These ideas are based in
part on concepts proposed by Edward Tufte, author of “The Visual
Display of Quantitative Information”. Tufte’s suggestions include
using quantitative metrics for data graphics and integrating text
with graphical data in charts. We have included a detailed
FabTime-generated example of improving an Excel-generated chart,
and summarized a few recommendations from both FabTime and Edward
Tufte. We hope that you find it interesting.
We have no new subscriber contributed discussion topics this month.
However, we have included a sample of responses to our newsletter sign-up
question: “What is the biggest cycle time problem in your fab?” and we
have posed a topic ourselves for future discussion. (
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In our main article this month, we revisit the topic of
dynamic x-factor, a metric for semiconductor wafer fabs that
we first described back in issue 4.08. Dynamic x-factor is a
point estimate that looks at the total wafers that you have
in your fab, divided by the wafers that are currently being
processed on tools. In this article, we look further into
what dynamic x-factor can tell us about how a fab is operating,
with emphasis on evaluation of shift change coverage policies and
comparison of relative performance across modules.
Community announcements in this issue include two calls for papers for conference
sessions related to semiconductor manufacturing applications.
Subscriber discussion topics include wafer holds, cycle time
and yield, operator utilization, and dynamic x-factor. (
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Subscriber discussion topics for this month include nine responses
to last month’s topic of Cycle Time and Yield. These responses
point out some significant omissions in our article. Therefore,
instead of introducing a new main article, we’ve chosen to revisit
the topic of cycle time and yield, and very briefly summarize the
additional points made by contributing subscribers. This article
is a companion article to Issue 5.01, and we recommend reading
the two of them together. (
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This month’s main article is about
the interaction between cycle time and yield. We’ve always cited yield improvement
as a potential benefit from cycle time improvement, and people we talk with
about this generally agree. However, because the actual data tends to be
proprietary in nature, references on this topic are scarce. Therefore,
we’ve decided to open the topic for discussion here, and summarize a few
references that are available. We hope that you’ll find the discussion interesting.
Subscriber discussion topics for this month include responses to Issue 4.09
(WIPHours Metric) and Issue 4.11 (Cycle Time and Factory Size). (
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