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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
