Task 879.2: Integration of Demand Planning and Manufacturing - - PowerPoint PPT Presentation

Task 879.2: Integration of Demand Planning and Manufacturing Planning

Task leader: Yon-Chun Chou Co-PI: Argon Chen National Taiwan University 2001.10.29 SRC Project 879 Progress report

Y-C Chou

Product Variety Granularity

Time (month) Product Variety 3 6 9 Generic products Specific products

L1 L2 L3

1, 2, 3, ... γ β α , ,

H1 H2 H3

(horizon) (product hierarchy level)

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Multi-granular Capacity Planning

k : R t i p : d

p t , k p t , i

tool

• f

ts requiremen capacity derive in time product for at time made forecast demand ⇓

1 4 , k

R

2 3 , k

R

1 2 , k

R

1 1 , k

R

2 2 , k

R

2 1 , k

R

1 2 Planning time (p) Tool require. (k) Time (t) H2 H1 Based on level 2 information Based on level 1 information uncertainty They are estimates for capacity requirement

• f the same time period.

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Research Needs and Objectives

• Needs: To develop capacity plans based on demand

forecasts for aggregate products (such as α).

(It may be too late to wait for level 1 demand information.)

Objectives:

• Develop a quantitative model for the uncertainty in

capacity requirements

• Identify the tools that are sensitive to changes in

demand scenarios

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The Envelope of Capacity Requirements

Tool 1 Tool 2 E1 E2 1 a , a : E a , 1 a : E ) a , a ( : scenarios demand 1 a a and 1 a , a d a d d a d ) d , d ( d

2 1 2 2 1 1 2 1 2 1 2 1 2 2 1 1 2 1

= = = = = + ≤ ≤    ⋅ = ⋅ = →

α α α

The envelope of capacity requirements

• f all scenarios

This envelope has been proven mathematically.

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A Numerical Example

• Total demand dα = 20,000 wpm, dα = d7 + d8

E1 E2 Product Group Products α 7, 8

Demand Scenario

1 2 3 4 5 6 7 8 9 10 11 Product 7 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 Product 8 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 * Process flow data is provided by TSMC.

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Tool Requirements of All Tool Sets

• Tools 15, 18, 33, 46, and 54 are sensitive to demand scenario.

2 4 6 8 10 12 14 20 40 60 80 100

Tool ID Tool requirement

Scenario1 Scenario2 Scenario3 Scenario4 Scenario5 Scenario6 Scenario7 Scenario8 Scenario9 Scenario10 Scenario11

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Tool Requirements of Sensitive Tool Sets

• Scenarios 1 and 11 are the extremes, their tool

requirements enclose those of all other scenarios.

2 4 6 8 10 12 14 16 10 20 30 40 50 60 Tool ID Tool requirement

Scenario1 Scenario2 Scenario3 Scenario4 Scenario5 Scenario6 Scenario7 Scenario8 Scenario9 Scenario10 Scenario11

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Validating the Envelope of Capacity Requirements

1 2 3 4 5 6 7 5 10 15 Tool 46 Tool 33

E2 E1

scenarios

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The Number of Extreme Demand Scenarios = 3

Tool 1 Tool 2 E1 E2

The envelope is a region.

) a , a , a ( : scenarios 1 a a a and 1 a , a , a d a d d a d d a d ) d , d , d ( d

3 2 1 3 2 1 3 2 1 3 3 2 2 1 1 3 2 1

= + + ≤ ≤      ⋅ = ⋅ = ⋅ = →

α α α α

E3

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Numerical Example: 3 Extreme Scenarios

Scenario

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Product 7 1.00 0.75 0.75 0.50 0.50 0.50 0.25 0.25 0.25 0.25 0.00 0.00 0.00 0.00 0.00 Product 8 0.00 0.25 0.00 0.50 0.00 0.25 0.75 0.00 0.50 0.25 1.00 0.00 0.50 0.25 0.75 Product 9 0.00 0.00 0.25 0.00 0.50 0.25 0.00 0.75 0.25 0.50 0.00 1.00 0.50 0.75 0.25

Product Group Products α 7, 8, 9

E1 E2 E3

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Validating the Capacity Envelope: 3 Extremes

2 4 6 8 10 12 5 10 15

Tool 33 Tool 46

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Two Product Groups, 5 Products

2 4 6 8 10 12 5 10 15

Tool 33 Tool 46

Product Group Products α 7, 8, 9 β 25, 28

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The Number of Tool Sets = 3

Tool 1 Tool 2 Tool 3

The envelope is a convex hull.

Assuming 4 extreme demand scenarios

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A Confidence Model of Capacity

Tool 1 Tool 2 Tool requirements covered by all scenarios Provisioned Capacity = tool portfolio (n1, n2) 1

A

2

A

3

A

4

A

n1 n2 Total area = A A A A A

confidence

) 4 2 ( 5 . 1 + +

=

Insufficient Tool 2

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Work in Progress

• Constructing the convex hull (in n-D space)
• Computing the “volume” of convex hull
• Decomposing the convex hull

Will be able answer these questions:

• If the quantity of tool set x is increased by 1, what is the

improvement in “confidence”?

• Which tool set is the most sensitive to demand scenario?

confidence capacity R d → → → scenario demand and hierarchy product ts requiremen tool

α α

algorithms

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Questions

• In the above analysis, demand scenarios are continuous.

An alternative approach is to model demand scenarios as discrete.

• Improving the confidence model?