Maximize Your Manufacturing
Efficiency: Gain Insight into theThree Fundamental Drivers of Fab
Cycle TimeJennifer Robinson

Cycle Time Evangelist for INFICONINFICON/FabTime Star Webinar for FOA

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Why is cycle time improvement worthwhile?
Cost/revenue drivers include:

Reducing Time to Market​

Increasing Fab Utilization​

Cutting cycle time getscustomer qual lots out thedoor faster.​Cutting cycle time allows you
to run closer to full capacity.

Cutting Costs​

Cutting cycle time may
reduce scrap and rework.​

Cutting cycle time decreases
WIP and carrying cost. ​Cutting cycle time provides
more R&D cycles of learning.​

What other reasons are there to improve CT?
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Cutting cycle time decreases
obsolete inventory risk.​2

Other reasons to improve cycle time include…

Happier customers• Shorter cycle times are usually also more predictable cycle times,
resulting in better on-time delivery performance.
Happier managers• A leaner fab with less WIP is more flexible and ready for market
changes.
• A fab carrying less WIP is easier to manage in general.
Anyone or anything else?

So, why don’t all fabs have great cycle time?
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Why are CTs high? Short answer: cost, complexity, and change• Wafer fab equipment is expensive and tends to be highly
loaded.
• Wafer fab process flows are long and complex.
• Product and technology mix change rapidly (so we don’t
qualify new recipes on tools, and the tools can be unreliable).
• And lots more that we’ll discuss…

What specific factors in the fab do you think contribute to high CT?
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Other challenges keeping fabs from getting great CT include…
• Downtime (scheduled and unscheduled)• Operator unavailability• Product mix• Scheduling/dispatching• Bottlenecks/utilization• Engineering use of tools• One-of-a-kind tools/single path operations• Running development lots
in a production fab• Holds• Hot lots

• Setups• Reentrant flow

• Process variation• Soft dedication/operator preferences for
tools• Time constraints between process steps• Lot release• Scrap / Rework• Manual lot transport between steps (via carts or
runners)• Batch processing

Given these challenges, what should we do to improve fab CT?
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How to improve fab cycle time: a three-step process

Fundamentals•

Help your team tounderstand where
to look forproblems and why.

•

Use this webinar
and the FabTime CT
newsletter.

•

A four-hour virtual
class is alsoavailable.

Data
•

•

Collect and analyze
data to identify
current problems
in the fab,highlighting themost important andactionable
opportunities.
INFICON products,
including FabTime
and the FPS
dashboard can help.

INFICON/FabTime Star Webinar for FOA

Action•Act usingfundamentals andactual data from thefab.

•

Implement control
technologies likethe INFICON FPS
Scheduler.

•Make
improvements thatwill help future CT.

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The 3 fundamental drivers of CT can help you improve profitability by…
Reducing forced idle time on key tools (allowing
increased loading of the fab).

We’ll use operating curves to illustrate impacts on CT• Driver 1: Utilization
Reducing variability, especially from downtime, andthus allowing fabs to get good cycle time at a higher
utilization.
• Driver 2: Variability
Improving cycle time of new products by demonstratingwhere “soft dedication” or insufficient tool qualification
is occurring.
• Driver 3: Number of Qualified Tools
These drivers apply at the tool group level, and roll up to impact overall CT.
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Cycle Time and Utilization
At the tool group level, utilization is the biggest driver of cycle time.

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We’ll use the SEMI E10 tool state definition of utilization
Utilization = (Productive Time) /(Manufacturing Time)​
where Manufacturing Time =Productive + Standby​ (time the tool isavailable manufacturing)and Productive Time = time spentworking on products

Utilization = 15/20= 75%

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When a tool group has no variability, CT is low regardless of utilization• Operation CT = Queue Time + Process Time (+ Hold, Travel, etc.)• Suppose we have a tool where lots arrive at a regular interval (gray bars), with no variability, and process
time (blue bars) is always one hour, again with no variability.
• Whether the utilization is 50% or 80% (or anything < 100%), queue time will always equal zero and CT (redline) will always equal the process time.

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It’s variability that causes lots to wait, and drives up cycle time
• Suppose now average process time is still an hour, but process times and times between arrivals bothhave moderate variability.​• Now, we see some queueing even at low utilization (50%).​• Lots 10 + 11 had longer process times, while Lots 11-13 had short times between arrivals. A small WIP
bubble built up. Long arrival times for Lots 14 and 16 allowed catch-up time.​

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Once there’s variability, cycle time increases as utilization increases
At 80% utilization (same avg. process time, less time between arrivals), WIP bubbles are likely to be larger.​• Long process time for Lot 10 is followed by a series of short times between arrivals. Just as CT
starts to dip after Lots 23 and 24, Lot 25 has another long process time. ​• The double-whammy of more lots to process and less idle time for the tool to recover leads to a
non-linear CT increase.

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Looking at a range of utilizations, over a longer period (230 arrivals) …

Random numbers are simulated using an
Excel spreadsheet tool. Contact Jennifer
Robinson for a copy of the spreadsheet.
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… We build an operating curve
Operating curve is a graph showing cycle time (or X-Factor, which is CT/Theoretical CT) vs. utilization
for a fab or a tool group.​• Usually generated from simulation or mathematical models.
• Can generate from actual data and fit a curve to the data​.
• Useful for exploring trade-offs in cycle time goals.​• Another Excel spreadsheet tool (FabTime Operating Curve Generator) uses queueing models toshow tool-level behavior.​
For a one-of-a-kind tool, the queueing formula is:
X-Factor = 1 / (1 – Utilization)(This formula is “exact” under certain assumptions.)
Mimics real fabs – once utilization rises above 85%,
cycle time starts to increase rapidly. This issometimes called the “hockey stick effect.”

INFICON/FabTime Star Webinar for FOA

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The relationship between CT and utilization creates a Core Conflict for fabs
Utilization is the largest driver of CT at the toollevel.​To reduce costs, fabs need to increase toolutilization.​
To improve CT, fabs need to decrease toolutilization.​
Some standby time is needed on the tools, tokeep cycle times reasonable.
We want to stay away from the steep part of theoperating curve.
The more standby time that can be provided, thebetter cycle times will be.

How can fabs resolve this conflict?
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There are several ways that fabs can resolve the Core Conflict
1.

Improve equipment uptime, thus
extracting standby time from current
unavailable time.

2.

Eliminate forced idle time (converting
wasted time, recorded as standby-WIPwaiting time, into true standby time).

3.

Reduce process times, so that lessproductive time is needed for the same
number of wafers.

4.

Reduce fab variability. The impact of thiswill be shown in the next section.​

But first, let’s talk more about forced idle time.
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Food for Thought: Which is the biggest source of forced idle time in your fab?

Operator
Unavailability

Holding Tools
for Hot Lots

Dispatching

INFICON/FabTime Star Webinar for FOA

Lot Transport

Something
else…

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How can fabs reduce forced idle time to improve productivity?
1. Minimize the number of distinct tools for which each operator is
responsible, and stagger break schedules.
• This is to reduce time that tools spend with WIP, waiting for
operators. ​2. Reduce the number of hot lots in the fab, especially hand-carrylots that cause setup changes / force idle capacity.​
3. Make smart dispatching and scheduling decisions to keep critical
downstream tools from starving. ​4. Make sure lots aren’t sitting on hold when they could be inprocess.
• This can happen especially with future holds. Designate aback-up engineer to be alerted for any future hold.

Ideas to keep tools from the steep
part of the operating curve

These are covered in more detail in our four-hour CT class.
INFICON/FabTime Star Webinar for FOA

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Cycle Time and Variability
Variability (in arrivals or process times) shifts the operating
curve up and to the left. Variability makes it impossible toachieve theoretical cycle time in any real fab

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CT increases with variability in both process times and time between arrivals
Contributors to process time variability:​

Contributors to interarrival time variability:• Different recipes on the same machine /
different process times. ​• Setups ​• Equipment failures​• Rework lots​• All the above​• Transfer batching/automated material handling​• Batch processing (multiple lots in a machine at
one time)​• Lot release• Yield loss (scrap)​• Operators ​• ...

Which do you think has a greater impact, process time variability or arrival variability?
See FabTime Newsletters 8.04, 16.05
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Food for Thought: Which of these is the biggest source of variability in yourfab?

Extended
Downtimes

Hot Lots

Batch
Processing

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Time Links
and Rework

Somethingelse...

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We can expand the queueing formula to account for variability
Recall the single-tool X-Factor estimate:​• X-Factor ~= 1 / (1 – Utilization)​• Assumes medium variability in arrivals and process times
More generally (again under certain assumptions)• X-Factor ~= 1 + [Utilization/(1-Utilization)] * [Variability Factor]
Variability Factor• Sum of arrival variability + process time variability​• Factor = (CVa2+ CVp2)/2​• CVa = Coefficient of variation for inter-arrival times​•

CVp = Coefficient of variation for process times​

Coefficient of Variation (CV)​• Statistical measure: (Standard deviation) / (Average)​• Standard deviation measures how widely values are dispersed from the average value. ​INFICON/FabTime Star Webinar for FOA

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Changing the CV of arrival OR process time variability changes the shape of the curve

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So which type of variability has more of an impact?
Variability Factor = (CVa2 + CVp2)/2​
With equal amounts of arrival and process time variability, the impact will be equal.
In practice:• Process time variability will be high on some tools (like implanters) and low on others (like furnaces).
• Arrival variability will be higher in a fab with carts than one with dedicated runners, and higher in a fab withmore large batch processes than one with fewer.
• It depends…

What matters is that you can improve CT by reducing arrival or process time variability.
• There are many ways to reduce variability in any fab.
• PM scheduling is one way to impact effective process time variability (and downstream arrival variability).

INFICON/FabTime Star Webinar for FOA

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Food for Thought: Your maintenance team proposes grouping daily PMs into
one long weekly PM for efficiency. Should you support the change?

Yes!

No!

Maybe…

Why or
why not?

More simply, for the same amount of scheduled downtime, is it better to have short/frequent
PMs or long/infrequent PMs?
Should you group your PMs?
INFICON/FabTime Star Webinar for FOA

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Consider the impact of longer vs. shorter PM events on a one-of-a-kind tool
Suppose the tool is down for maintenance 20% of the time
under moderate variability.​
For the same total amount of scheduled downtime (4.8hours/day), consider taking the tool down for maintenance:• Once every 8-hour shift for 1.6 hours• Once every 24 hours for 4.8 hours• Once every 3 days for 14.4 hours
The longer period of unavailable time (the upper red curve)
is MUCH worse for cycle time.
• We could spend more than 10% of time in extra quals
before the red curve would be better than the green.
• The longer PMs also send more variability downstream.
Take home message: for the same amount of unavailable time, avoid grouping PMs for better CT.
INFICON/FabTime Star Webinar for FOA

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Any type of variability shifts the operating curve up and to the left
Anything that can be done to reduce variability in the fab will shift
the operating curve downward and will improve things. ​Variability reduction gives the fab a choice:​
1.Reduce cycle time, while maintaining the same throughput rate(by moving straight down to a different operating curve).​
2.Increase the throughput rate, while maintaining the same cycle
time (by moving across horizontally to a different operating
curve).

(these are best illustrated graphically)

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If we reduce variability, we can get a better CT at the same throughput rate

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If we are constrained by a CT target, then reducing CT can increase throughput

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Variability impairs performance for any manufacturing system
Variability is bad!
Decreasing variability in arrivals or process times or fromdowntime will improve cycle times.​
Because you don’t have to reduce starts, or purchaseadditional tools, variability reduction is a relatively
inexpensive way to improve cycle time and reduce work inprocess. ​Measure arrival and process time CVs, as well asavailability variability, to identify areas for cycle time
improvement.​

CT

CT
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How can fabs reduce variability to improve profitability/performance?
Systematically monitor (using CVs and control charts) and reduce variability:••

In process times.
In tool availability (or Green-to-Green time).​• Separate maintenance events instead of grouping them.​• Ensure sufficient MTs and spare parts.
• In starts (if possible) and between steps (via changes in lot transportand via dispatching and scheduling).​

Also:
•
•
•

Consider greedy policy for lightly loaded batch tools and using
smaller carts.
Reduce setup and rework. ​Reduce the number of hot lots in the fab.

More details about these in our newsletter and 4-hour CT class.
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Cycle Time and Number of Qualified Tools
The number of qualified tools in a tool group has a major
impact on cycle time. This impact increases with higher levelsof utilization and variability.​

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Going from one to two qualified tools cuts CT per visit roughly in half

FabTimeOperatingCurveGeneratorCourse.xlsx​
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As we increase the number of qualified tools/recipe, the benefit levels off

Tool group is 90% utilized, levelof cross-qualification varies.
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The intuitive explanation is that we need a backup in case of variability
When there’s only one tool, a lot is subject to all the variability associated with that tool (long process times,
downtimes, etc.).
When there are two tools, the probability of both tools being hit by a long delay at the same time is muchsmaller. The lot can be processed on the second tool.​• With 3 tools, the probability of all 3 being impacted at the same time is even smaller.
Real-World Examples:• Shared line vs. dedicated lines at stores or the airport. Shared line
is much faster, on average.
• Single lane road vs. multi-lane road. We will end up behind theslow car(s) on the single lane road.

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We highly recommend keeping single-path operations visible in fab reports
The FabTime chart on the left shows, for all route-step combinations that have WIP waiting, the number oftools qualified to run that step. Steps with more than two tools are not displayed.
The FPS Dashboard chart on the right shows which implant tools are qualified for which processes.

INFICON/FabTime Star Webinar for FOA

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It’s also useful to identify where “soft dedication” is occurring• Soft dedication is when
operators have preferences
for certain tools (layout,
speed, etc.)• Graphing availability
efficiency and moves bytool for a tool group canshow where a tool has
higher or lower moves thanavailability would predict.
• 5xStep02 has extra
moves in this example.

INFICON/FabTime Star Webinar for FOA

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How should fabs manage tool qualification to improve performance?
Education:
Teach team members (especially process engineers) the
impact of tool qualification on cycle time curve​.

Systematically monitor and reduce:
Active constraints (especially complex constraints!)​.
Do all constraints have an expiration date?​
Impaired recipes / disabled tool capabilities​.
Single-path operations​.
Soft-dedication due to preferences / inconvenient tool location.​

Take home message: If you’re going to do one thing to improve fab cycle time, qualify asecond tool everywhere you can.
INFICON/FabTime Star Webinar for FOA

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Wrapping Up
Utilization, Variability, and Tool Qualification issues all drive
cycle time higher. Understanding the cycle time impact of thesefactors helps your organization identify and prioritize
opportunities for cycle time reduction (= profitability
improvement).

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Recap: The 3 fundamental drivers of fab cycle time
Utilization = Productive / (Productive + Standby)​• For single tools, operating curve shaped like X-Factor = 1 / (1 – Utilization). When utilization approaches
100%, CT gets very high.​• Converting unavailable time and forced idle time to true standby time improves CT.
Variability changes the shape of the operating curve• X-Factor ~= 1 + [Utilization/(1-Utilization)] * [Variability Factor]​• Reducing variability (arrival, process, downtime) reduces cycle time.
• Opportunities to reduce fab variability abound, especially around tool downtime and PM scheduling.
Number of qualified tools is the 3rd core driver of CT​• Increasing number of qualified tools and decreasing soft dedication can improve CT for new products.
• Moving from one qualified tool to two can cut operation cycle time by 50%, with smaller increases as
more tools are qualified.​

Which of these do you think would be most useful for you?
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For more ideas: subscribe to the FabTime Cycle Time Newsletter
If the content in this webinar seems useful to you, consider subscribing to the FabTime Cycle Time Management
Newsletter (now distributed by INFICON)• Bi-monthly email publication, currently sent as PDF attachment, 2800+ subscribers, 180+ past issues• Articles about improving fab productivity, with subscriber discussion, community and industry news, andcycle time tips
Recent Topics:​• Cycle Time and Holds• Forward-Looking Cycle Time Metrics• What Makes an Effective Daily Fab Status Meeting?
• Managing Operators during a Staffing Shortage
Next topic: Improving communication about fab equipment reliability

Email jennifer.robinson@inficon.com to subscribe or message me on LinkedIn:
https://www.linkedin.com/in/jenniferrobinsoncycletime/
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Focusing on the fundamental drivers of CT can help fabs improve profitability​Cycle time can be reduced with $$$ (tools and staffing).​• This is often infeasible for various reasons.
Cycle time can also be reduced with education and behavior changes.
•

Step 1: Use operating curve concepts to understand theimplication of operational decisions on cycle time (PM strategies,
tool dedication policies, etc.)​•

Step 2: Use actual data to pinpoint problem areas, especiallywhere cycle time is worse than goal. Knowing where theproblems are is the first step to improving them.​•

Step 3: Take action in your fab. Make some changes andmeasure their impact. Use software and control tools like afactory scheduler to help.

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INFICON can help via our course and complete portfolio of Smart Solutions

Learning data warehouse andfactory physics engine

Optimized maintenance timing
and labor

Smart DigitalTwin

Real-time factory priorities,
flexible user-customized reporting

FabTime &Factory
Dashboard

Factory
Scheduling, Team
Optimizer

FabRecover,
SmartMMSINDUSTRY 4.0
SMART
FACTORY

Process aware sensing
solutionsSensors &SmartSensing

Tool & process monitoring for
reduced scrap

FabGuard®
FDC, SmartFDC& Subfab

Metrology
Sampling
Optimizer

NextMove
Location
Tracking

Global optimization of Returnon Assets

Optimized Scheduler based
WIP movement

Intelligent integrated sampling
for reduced risk at lower cost

Please reach out to jennifer.robinson@inficon.com for more information.
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Connect with us!

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