160615 progress update wp3 (nils knofius)

SINTASWORK PACKAGE 3NILS KNOFIUS

Supervision:

Dr. Matthieu C. van der Heijden

Prof. dr. W. Henk M. Zijm

Motivation:

Most important benefit of AM for operations (Wohlers Report, 2014)

No quantitative insights available on total costs

Objective:

Quantify the total costs of consolidation

Study under which circumstances consolidation is beneficial

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PRINT ASSEMBLY STRUCTURE IN ONE PIECE PARTCONSOLIDATION WITH ADDITIVE MANUFACTURING

Print multiple

components in one

piece

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SIMPLE EXPERIMENTSEXPERIMENT 1

Part 1 Part 2 vs. Part 1+2

Segmented design Consolidated design

Parameters ValuesPart holding cost (ℎ𝑛) low, high

Part replenishment lead time (𝑙𝑛) low, high

Part demand rate (𝑚𝑛) low, high

Scaling factor holding costs (α) 0.5, 1, 1.5

Scaling factor replenishment lead time (β) 0.5, 1, 1.5

Scaling factor demand rate (γ) 0.5, 1, 1.5

Characteristics Experiment 1:

No hierarchy involved

Consolidation to monolithic design

Holding cost consolidated design ℎ = 𝛼σ𝑛 ℎ𝑛

Replenishment lead time consolidated design 𝑙 = 𝛽 σ𝑛𝑚𝑛

σ𝑚𝑝𝑙𝑛

Demand rate consolidated design 𝑚 = γσ𝑛𝑚𝑛

If scaling factor

is <1 then

improvement

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SIMPLE EXPERIMENTSEXPERIMENT 1

Part 1 Part 2 vs. Part 1+2

Segmented design Consolidated design

Parameters ValuesPart holding cost (ℎ𝑛) low, high

Part replenishment lead time (𝑙𝑛) low, high

Part demand rate (𝑚𝑛) low, high

Scaling factor holding costs (α) 0.5, 1, 1.5

Scaling factor replenishment lead time (β) 0.5, 1, 1.5

Scaling factor demand rate (γ) 0.5, 1, 1.5

Results Experiment 1:

91% segmentation design superior if no improvements (𝛼, 𝛽, 𝛾 = 1)

In remaining 9% of cases, total costs reduction marginal (at most 0.2%)

Even if all parameters improve (𝛼, 𝛽, 𝛾 = 0.5) in 2% of cases segmentation

design superior

In each case, all parameters unbalanced:

E.g.: ℎ1 = 𝑙𝑜𝑤 & ℎ2 = ℎ𝑖𝑔ℎ; l1 = 𝑙𝑜𝑤 & l2 = ℎ𝑖𝑔ℎ; m1 = 𝑙𝑜𝑤 &m2 = ℎ𝑖𝑔ℎ

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SIMPLE EXPERIMENTSEXPERIMENT 2

Part 1 Part 2 vs. Part 1+2

Segmented design Consolidated design

Parameters ValuesPart holding cost (ℎ𝑛) low, high

Part replenishment lead time (𝑙𝑛) low, high

Part demand rate (𝑚𝑛) low, high

Scaling factor holding costs (α) 0.5, 1, 1.5

Scaling factor replenishment lead time (β) 0.5, 1, 1.5

Scaling factor demand rate (γ) 0.5, 1, 1.5

Characteristics Experiment 2:

Assembly structure

Consolidation to monolithic design

Consolidation design parameters as Experiment 1

Assembly parameters obtained by setting (𝛼, 𝛽, 𝛾 = 1)

Failure assembly occurs due to Part 1 and Part 2 relative to demand rate

Failure solved by replacing failed part

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SIMPLE EXPERIMENTSEXPERIMENT 2

Part 1 Part 2 vs. Part 1+2

Segmented design Consolidated design

Parameters ValuesPart holding cost (ℎ𝑛) low, high

Part replenishment lead time (𝑙𝑛) low, high

Part demand rate (𝑚𝑛) low, high

Scaling factor holding costs (α) 0.5, 1, 1.5

Scaling factor replenishment lead time (β) 0.5, 1, 1.5

Scaling factor demand rate (γ) 0.5, 1, 1.5

Results Experiment 2:

Consolidation design always superior if parameters remain (𝛼, 𝛽, 𝛾 = 1)

Even if all parameters worsen (𝛼, 𝛽, 𝛾 = 1.5) in 6% of cases consolidation

is still superior

In each case assembly stock of segmented design equals total stock

of consolidation design

Additional stock for Part 1 and Part 2 leads to higher costs for

segmented design required to keep replenishment lead time short

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SIMPLE EXPERIMENTSEXPERIMENT 3

Part 1 Part 2 vs.

Segmented design

Characteristics Experiment 3:

Assembly structure

Partial integration on one hierarchy level

Consolidation design parameters as Experiment 1

Assembly parameters as in Experiment 2

Part 3 Part 1 Part 2+3

Consolidated design

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SIMPLE EXPERIMENTSEXPERIMENT 3

Part 1 Part 2 vs.

Segmented design

Results Experiment 3:

Consolidation is more often desirable than in Experiment 1 (no hierarchy,

monolithic design) but still only in 39% of cases

Partial consolidation offers more options for the stocking locations than

monolithic design

If Part 2 and Part 3 have identical parameters, consolidation design is in

7% more cases superior

Part 3 Part 1 Part 2+3

Consolidated design

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SIMPLE EXPERIMENTSCONCLUSIONS

1. On the same hierarchy level consolidation is more desirable between

parts with comparable parameters

2. If consolidation eliminates hierarchy it is desirable even if parameters

do not improve

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OUTLOOK

Identify case study (master project Thales)

New experiments

More detailed costs breakdown

More parameter ranges

More complex designs

Pooling effect

vs.

pooling

Part A Part B Part B Part BPart A+B

THANK YOU!

Nils Knofius

n.knofius@utwente.nl