Cost Optimization of Product Families Using Solution Spaces: Application to Early-Stage Electric Vehicle Design

S. Rötzer; V. Berger; M. Zimmermann

doi:10.1017/pds.2022.60

Cost Optimization of Product Families Using Solution Spaces: Application to Early-Stage Electric Vehicle Design

S. Rötzer
, V. Berger
, M. Zimmermann

Chair of Product Development and Lightweight Design

Research output: Contribution to journal › Conference article › peer-review

5 Scopus citations

Abstract

Companies offer products in different variants to reach more customers. This increases internal variety and cost. However, reducing those cost is difficult due to complexity. Complexity arises from: combinatorics; many design variables interacting with each other; coupling of technical and economical perspectives. This paper presents an approach based on (1) building a complex system model of modular models; (2) identifying the potential for standardization from a technical perspective; (3) cost-optimizing the degree of standardization. A product family of electric vehicles was optimized.

Original language	English
Pages (from-to)	583-592
Number of pages	10
Journal	Proceedings of the Design Society
Volume	2
DOIs	https://doi.org/10.1017/pds.2022.60
State	Published - May 2022
Event	17th International Design Conference, DESIGN 2022 - Virtual, Online, Croatia Duration: 23 May 2022 → 26 May 2022

Keywords

complexity
data-driven design
optimisation
product families
solution space engineering

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10.1017/pds.2022.60

Cite this

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title = "Cost Optimization of Product Families Using Solution Spaces: Application to Early-Stage Electric Vehicle Design",

abstract = "Companies offer products in different variants to reach more customers. This increases internal variety and cost. However, reducing those cost is difficult due to complexity. Complexity arises from: combinatorics; many design variables interacting with each other; coupling of technical and economical perspectives. This paper presents an approach based on (1) building a complex system model of modular models; (2) identifying the potential for standardization from a technical perspective; (3) cost-optimizing the degree of standardization. A product family of electric vehicles was optimized.",

keywords = "complexity, data-driven design, optimisation, product families, solution space engineering",

author = "S. R{\"o}tzer and V. Berger and M. Zimmermann",

note = "Publisher Copyright: {\textcopyright} The Author(s), 2022.; 17th International Design Conference, DESIGN 2022 ; Conference date: 23-05-2022 Through 26-05-2022",

year = "2022",

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doi = "10.1017/pds.2022.60",

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T1 - Cost Optimization of Product Families Using Solution Spaces

T2 - 17th International Design Conference, DESIGN 2022

AU - Rötzer, S.

AU - Berger, V.

AU - Zimmermann, M.

N1 - Publisher Copyright: © The Author(s), 2022.

PY - 2022/5

Y1 - 2022/5

N2 - Companies offer products in different variants to reach more customers. This increases internal variety and cost. However, reducing those cost is difficult due to complexity. Complexity arises from: combinatorics; many design variables interacting with each other; coupling of technical and economical perspectives. This paper presents an approach based on (1) building a complex system model of modular models; (2) identifying the potential for standardization from a technical perspective; (3) cost-optimizing the degree of standardization. A product family of electric vehicles was optimized.

AB - Companies offer products in different variants to reach more customers. This increases internal variety and cost. However, reducing those cost is difficult due to complexity. Complexity arises from: combinatorics; many design variables interacting with each other; coupling of technical and economical perspectives. This paper presents an approach based on (1) building a complex system model of modular models; (2) identifying the potential for standardization from a technical perspective; (3) cost-optimizing the degree of standardization. A product family of electric vehicles was optimized.

KW - complexity

KW - data-driven design

KW - optimisation

KW - product families

KW - solution space engineering

UR - https://www.scopus.com/pages/publications/85131379862

U2 - 10.1017/pds.2022.60

DO - 10.1017/pds.2022.60

M3 - Conference article

AN - SCOPUS:85131379862

SN - 2732-527X

VL - 2

SP - 583

EP - 592

JO - Proceedings of the Design Society

JF - Proceedings of the Design Society

Y2 - 23 May 2022 through 26 May 2022

ER -

Cost Optimization of Product Families Using Solution Spaces: Application to Early-Stage Electric Vehicle Design

Abstract

Keywords

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