Decision-Making Platform for Design Optimization by Integrating Linear Programming and House of Quality

This study presents an integrated approach combining the House of Quality (HoQ) and Linear Programming (LP) to optimize the design and manufacturing of consumer beverage packaging, ensuring alignment between customer expectations and engineering capabilities.The methodology focuses on translating user needs into functional characteristics, while minimizing production costs and material waste to support sustainability efforts.Linear Programming (LP) is utilized to systematically evaluate various design alternatives, helping designers strike an optimal balance between performance, usability, and cost-efficiency.Additionally, Finite Element Analysis (FEA) is applied to simulate mechanical behaviors, addressing structural concerns like handling convenience and base stability.Special attention is given to design elements, the ergonomically contoured body and cap, with an emphasis on single-handed operation and force distribution.The final design incorporates a sleek, minimalist aesthetic, enhancing both user interaction and manufacturing feasibility.This integrated framework not only enhances development efficiency but also aligns with changing market trends, especially among younger consumers who value functional aesthetics and responsible design.By bridging customer insights with engineering analysis, this study offers a strategic pathway for creating innovative and sustainable packaging solutions.

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Institutions

Publication Details

Journal
Engineering Journal
Published
2025-06-30
DOI
https://doi.org/10.4186/ej.2025.29.6.95
Citations
1
Primary Topic
Quality Function Deployment in Product Design
Type
article
Field-Weighted Citation Impact
2.76

Funders

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article

Decision-Making Platform for Design Optimization by Integrating Linear Programming and House of Quality

Suchada Rianmora, Wichapol Chanchiewvichai, Phum Pinthanon
1 citations
Engineering Journal
Quality Function Deployment in Product Design
2.76
article

Decision-Making Platform for Design Optimization by Integrating Linear Programming and House of Quality

Suchada Rianmora, Wichapol Chanchiewvichai, Phum Pinthanon
article en
1 citations

Abstract

This study presents an integrated approach combining the House of Quality (HoQ) and Linear Programming (LP) to optimize the design and manufacturing of consumer beverage packaging, ensuring alignment between customer expectations and engineering capabilities.The methodology focuses on translating user needs into functional characteristics, while minimizing production costs and material waste to support sustainability efforts.Linear Programming (LP) is utilized to systematically evaluate various design alternatives, helping designers strike an optimal balance between performance, usability, and cost-efficiency.Additionally, Finite Element Analysis (FEA) is applied to simulate mechanical behaviors, addressing structural concerns like handling convenience and base stability.Special attention is given to design elements, the ergonomically contoured body and cap, with an emphasis on single-handed operation and force distribution.The final design incorporates a sleek, minimalist aesthetic, enhancing both user interaction and manufacturing feasibility.This integrated framework not only enhances development efficiency but also aligns with changing market trends, especially among younger consumers who value functional aesthetics and responsible design.By bridging customer insights with engineering analysis, this study offers a strategic pathway for creating innovative and sustainable packaging solutions.

Engineering JournalVol. 29(6)
Thammasat University (TH)
Thammasat University, Sirindhorn International Institute of Technology, Thammasat University
Openalex Percentile: Top 9%
Quality Function Deployment in Product Design
2.76
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Decision-Making Platform for Design Optimization by Integrating Linear Programming and House of Quality — Suchada Rianmora, Wichapol Chanchiewvichai, et al. · Engineering Journal (2025) | TGRS Research Map | TGRS