Mathematical Modeling Approach for the FAB Design Process ...xs3d.kaist.ac.kr/ismi2015/Presentations/ismi2015... · 1 Mathematical Modeling Approach for the FAB Design Process in

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Mathematical Modeling Approach for the FAB Design

Process in Semiconductor Manufacturing

Gwangjae Yu

Junghoon Kim

Young Jae Jang

Dept. of Industrial and Systems Eng.

KAIST

[email protected]

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1. Research Motivation

• Two current practice- Trial & error by human experience Optimality not guaranteed- Decision by the consensus of the different field-experts Significant time & effort needed

Layout designer Simulation expert

Product engineer Facility manager

2. Tool allocation

3. Simulation Test

1. Bay layout design

4. Finallayout design

ManyIterations

Trial & error

Trial & error

• Each Trial & Error requires consensus• Very difficult to reach on consensus

Trial & error Over 3 months!

Copyright © Young Jae JANG

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1. Research Motivation

• Two current practice- Trial & error by human experience Optimality not guaranteed- Decision by the consensus of the different field-experts Significant time & effort needed

• New practice- Analytical method by optimization theory Optimality or sub-optimality

guaranteed- Decision by the math and computer technology Significant time & effort saved

+

Over 3 months! Total less than a few hours!


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2. Research

• Introducing the 2 STEP fab layout design procedure

STEP 1 : Designing the optimal bay layout (process level design)

STEP 2 : Allocating the tools (tool level design)

<STEP 1> <STEP 2>


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3. Research Objective

• How to find a better layout design?- in terms of certain decision criteria

• What does it mean by better?- Several criteria considering the material handling (distance, time, cost, congestion, etc.)

• Our objective- Find a layout design with the minimum material flow distance


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4. Research Idea

• Semiconductor manufacturing process- Repetitive process, thus re-enters the same bays and tools many times

• Major issue in the bay layout design process- Wrong bay layout can cause an inefficient material handling (in terms of time, distance, cost, etc.)

EX) Process flow: DRY

<Bad>

Ex) Comparison of the material handling efficiency of the 2 different bay design of 2X2 layout

WET PHO IMP DRY

DRY PHO

IMP WET

AMHS

<Good>

DRY WET

IMP PHO

AMHS2 cycles 1 cycle


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4. Research Idea

• Semiconductor manufacturing process- Repetitive process, thus re-enters the same bays and tools many times

• Major issue in the tool allocation process- Wrong tool allocation can cause an inefficient material handling (in terms of time, distance, cost, etc.)

Ex) Comparison of the material handling efficiency by the 2 different tool allocation scenario

Assuming that the bay layout design is in optimal

EX) Material flow: T001 T002 T003 T004 T005

<Bad>

DRY WET

WET PHO

AMHS

<Good>

DRY WET

WET PHO

AMHS

T001 T002

T005

T003

T004

T002

T003

T001

T005 T004

1.75 cycles 0.75 cycles


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Case Study

<Settings>

• 4 product types

• 18 bay locations (in rectangular space)

• One directional loop with shortcuts

• 212 tool choices (8 types : PVD, CVD, PHO, WET, DIF, DRY, CMP, IMP)

• Around 300 steps per each product type

• Production plan (40,000 wfr/month 10,000 wfr/wk)

Product-ID Plan (wfr/wk)

Prod A 1,000

Prod B 4,500

Prod C 1,000

Prod D 3,500

Total 10,000

<Weekly production plan data (Time 1)>


1 4 5 8 9 12 13 16

AMHS

2 3 6 7 10 11 14 15

1) Bay layout2) Tool allocation

MathematicalModeling

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<Basic layout format>

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STEP 1Optimal Bay Layout Design


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STEP 1: Optimal Bay Layout Design Using the Flow Matrix

• Flow matrix (From-To chart) is a step to step process transition matrixthat demonstrates the manufacturing steps.


<Monthly From-To frequency among the process types (40,000 wafers/month)>

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• Objective- minimize the total travel distance of the wafer flow

• Constraints

1. all the tools must be allocated based on the space capacity of each bay2. Conservation of the material flow3. bays of the same process types are located next to each other


Model 1: Bay layout design model (MIP)

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AMHS


• Constraints1. All the tools must be allocated based on the space capacity of each bay2. Conservation of the material flow3. Bays of the same process types are located next to each other

WET𝑻𝒐𝒐𝒍𝑾𝑬𝑻:

𝑻𝒐𝒐𝒍𝑫𝑹𝒀:

WET WET WET

DRY DRY

𝑻𝒐𝒐𝒍𝑫𝑰𝑭: DIF

7 Tools to be allocated4 WET, 2 DRY, 1 DIF(1 unit space each)

3 bays of 4 unit spaces each

Bay 1 Bay 2 Bay 3

IN & OUT4 unit (by 4 tools)

Material flow occurs

IN & OUT3 unit (by 3 tools)


NO IN & OUT0 unit (by 0 tools)



To

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AMHS


• Constraints1. All the tools must be allocated based on the space capacity of each bay2. Conservation of the material flow3. Bays of the same process types are located next to each other

Bay 1 Bay 2 Bay 3

If IN flow = 100Bay 4 Bay 5 Bay 6

OUT flow = 100IN = OUT

100 100=


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AMHS


• Constraints1. All the tools must be allocated by the space capacity of the bay2. Conservation of the material flow3. Bays of the same process types are located next to each other

DRY DRY WET DIF …

DRY WET WET DIF ...

*If 3 DRY, 3 WET, and 2 DIF bays are required,


Bypass bridge

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Result: Bay Layout Design

<18-bay layout design, specifying the process types for each bay>


Bay 1

DRY DRY

AMHS: IMHS (Inter-bay Material Handling System)

Bay 4

DRY DRY

Bay 5

DRY DRY

Bay 8

IMP IMP

Bay 9

WET WET

Bay 12

WET WET

Bay 13

WET DIF

Bay 16

CMP CVD

Bay 17

CVD CVD

DRY DRY

Bay 2

DRY DRY

Bay 3

DRY PHO

Bay 6

PHO IMP

Bay 7

WET WET

Bay 10

WET WET

Bay 11

DIF DIF

Bay 14

CMP PVD

Bay 15

CVD CVD

Bay 18

: Stocker : Intra-bay Material Handling System

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STEP 2Optimal Tool Allocation


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STEP 2: Optimal Tool Allocation Using the Mfg. Step Sequence

• Manufacturing step sequence is a very specific process flow informationthat demonstrates the manufacturing system in the tool level. (recipe sequence)

<Actual mfg. step sequences>


Total around 300 steps !!

<Recipe sequence data sample of product type A>

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• Objective- Minimize the travel distance of the wafer flows

• Constraints1. Conservation of step to step material flow2. Tool capacity of one bay ≥ flow in that bay3. Tools are assigned by the bay space capacity


Model 2: Tool allocation model (MIP)

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• Constraints

1. Conservation of step to step material flow2. Tool capacity of one bay ≥ flow in that bay3. Tools are assigned based on the bay space capacity

AMHS

STEP1 STEP3 STEP3

STEP2 STEP4 STEP4

EX) If 4 step process of hourly production rate 100,1 2 3 4

100 30

70 3010 60

𝑓𝑙𝑜𝑤𝑠𝑡𝑒𝑝1 = 𝑓𝑙𝑜𝑤𝑠𝑡𝑒𝑝2= 𝑓𝑙𝑜𝑤𝑠𝑡𝑒𝑝3= ⋯ = 𝑓𝑙𝑜𝑤𝑠𝑡𝑒𝑝 𝑛


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• Constraints

1. Conservation of step to step material flow2. Tool capacity of one bay ≥ flow in that bay3. Tools are assigned based on the bay space capacity

1𝑪𝑽𝑫𝟏:

𝑪𝑽𝑫𝟐:

1 1 1

2 2

𝑪𝑽𝑫𝟑: 3

<Pre-determined tool plan>

Bay 1 (CVD) Bay 2,3,4,⋯

STEP1: 100

: Each capa 15 for step 1



15 + 2*20 + 50 = 105 ≥ 100

Total tool capacity ≥ req. production (step 1)


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• Constraints

1. Step to step material flow is conserved2. Tool capacity of one bay ≥ flow in that bay3. Tools are assigned based on the bay space capacity

1𝑪𝑽𝑫𝟏:

𝑪𝑽𝑫𝟐:

1 1 1

2 2

𝑪𝑽𝑫𝟑: 3

<Pre-determined tool plan with 2 bays with 4 slots each>

Bay 1 (CVD) Bay 2 (CVD)


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Result: Optimal Tool Allocation


<Tool allocation result for 18-bay layout (sample data)>

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Analysis of the layout designSimulation


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Simulation of the FAB Layout


<FAB layout>

< Simulation >

< From/To matrix >

0

20

40

60

80

100

0

20

40

60

80

100

120

140

30

90

15

0

21

0

27

0

33

0

39

0

45

0

51

0

57

0

63

0

69

0

75

0

81

0

87

0

93

0

The

nu

mb

er o

f m

ove

s

Delivery time (sec.)

Cu

mu

lati

ve (

%)

< Determination of number of OHTs in AMHS>

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Simulation Model


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Comparison of the resultant layout design performance

• Returning to our original purpose of study,

Q. “Would the analytical approach result a better performance over current practice of trial & error approach?”

• We compared 3 different layout designs1) Layout design from the analytical model2) Layout design by trial & error method referring a technical report,

SEMATECH 300mm Factory Layout and Material Handling Modeling: Phase II Report3) Layout design by trial & error method referring a journal paper,

Chen, J. C., Dai, R. D., & Chen, C. W. (2008). A practical fab design procedure for wafer fabrication plants. International Journal of Production Research, 46(10), 2565-2588

• Performance measure- Transport time- Waiting time- Average OHT-util.- Average WIP in the STKs


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Analysis Result


<Comparison Result of the simulation test for 3 different layout designs>

PerformanceCriteria

LayoutDesigns

Transport time Waiting timeAverageOHT-util.

Average WIP in the STKs

Optimalby our method

55.41 sec 271.15 sec 50.03 % 4.35 lots

Reference 1(SEMATECH)

65.17 sec 297.93 sec 56.26 % 4.57 lots

Reference 2(Journal Paper)

64.68 sec 291.88 sec 54.87 % 4.40 lots

About 14~15% decrease in transportation time, 7~9 % decrease in waiting time,5~6% decrease in avg. OHT utilization, 1~5% decrease in avg. WIP.

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Conclusion


• Analytical approach with mathematical modeling can be an effective way in layout design process of a semiconductor FAB.

• The resultant layout can be used as an initial layout of a good quality to start minor changes using trial & error method by the experience of the experts.

• Finally, it can reduce a significant amount of time that more time can be spent on testing different designs and decision making process for final decision.

Documents

Mathematical Modeling Approach for the FAB Design Process ...xs3d.kaist.ac.kr/ismi2015/Presentations/ismi2015... · 1 Mathematical Modeling Approach for the FAB Design Process in