Economic optimization in product design

Ronald G. Askin, Jeffrey B Goldberg

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

Worldwide competition and rapid technological innovation have revitalized interest in efficient techniques for product design for quality and manufacturability. The Japanese approach, popularized by G. Taguchi, uses outcomes of statistical experiments to select settings for design parameters which yield desirable process mean and variance. In this paper we present mathematical models for incorporating the results of statistical performance models along with production costs into product design models. The objective of the models is to minimize the sum of quality loss, material and production costs. Costs are assumed to be functions of the design parameters. Statistical experiments are employed to aid in the development of quality performance models. Pertinent constraints include limits on the bias of the process mean and variance. The proposed approach permits a more general environment and utilizes a more direct, economic objective as compared to the Taguchi method. A product design example is presented.

Original languageEnglish (US)
Pages (from-to)139-152
Number of pages14
JournalEngineering Optimization
Volume14
Issue number2
DOIs
StatePublished - Nov 1 1988

Fingerprint

Product Design
Product design
Process Mean
Economics
Performance Model
Parameter Design
Optimization
Costs
Taguchi Method
Statistical Model
Taguchi methods
Experiment
Mathematical Model
Minimise
Innovation
Experiments
Mathematical models
Model
Process mean
Production cost

Keywords

  • Manufacturing
  • product design
  • quality control

ASJC Scopus subject areas

  • Computer Science Applications
  • Industrial and Manufacturing Engineering
  • Management Science and Operations Research
  • Applied Mathematics
  • Control and Optimization

Cite this

Economic optimization in product design. / Askin, Ronald G.; Goldberg, Jeffrey B.

In: Engineering Optimization, Vol. 14, No. 2, 01.11.1988, p. 139-152.

Research output: Contribution to journalArticle

Askin, Ronald G. ; Goldberg, Jeffrey B. / Economic optimization in product design. In: Engineering Optimization. 1988 ; Vol. 14, No. 2. pp. 139-152.
@article{799f5e21ddc14ab3b40e01faaca8bc7a,
title = "Economic optimization in product design",
abstract = "Worldwide competition and rapid technological innovation have revitalized interest in efficient techniques for product design for quality and manufacturability. The Japanese approach, popularized by G. Taguchi, uses outcomes of statistical experiments to select settings for design parameters which yield desirable process mean and variance. In this paper we present mathematical models for incorporating the results of statistical performance models along with production costs into product design models. The objective of the models is to minimize the sum of quality loss, material and production costs. Costs are assumed to be functions of the design parameters. Statistical experiments are employed to aid in the development of quality performance models. Pertinent constraints include limits on the bias of the process mean and variance. The proposed approach permits a more general environment and utilizes a more direct, economic objective as compared to the Taguchi method. A product design example is presented.",
keywords = "Manufacturing, product design, quality control",
author = "Askin, {Ronald G.} and Goldberg, {Jeffrey B}",
year = "1988",
month = "11",
day = "1",
doi = "10.1080/03052158808941207",
language = "English (US)",
volume = "14",
pages = "139--152",
journal = "Engineering Optimization",
issn = "0305-215X",
publisher = "Taylor and Francis Ltd.",
number = "2",

}

TY - JOUR

T1 - Economic optimization in product design

AU - Askin, Ronald G.

AU - Goldberg, Jeffrey B

PY - 1988/11/1

Y1 - 1988/11/1

N2 - Worldwide competition and rapid technological innovation have revitalized interest in efficient techniques for product design for quality and manufacturability. The Japanese approach, popularized by G. Taguchi, uses outcomes of statistical experiments to select settings for design parameters which yield desirable process mean and variance. In this paper we present mathematical models for incorporating the results of statistical performance models along with production costs into product design models. The objective of the models is to minimize the sum of quality loss, material and production costs. Costs are assumed to be functions of the design parameters. Statistical experiments are employed to aid in the development of quality performance models. Pertinent constraints include limits on the bias of the process mean and variance. The proposed approach permits a more general environment and utilizes a more direct, economic objective as compared to the Taguchi method. A product design example is presented.

AB - Worldwide competition and rapid technological innovation have revitalized interest in efficient techniques for product design for quality and manufacturability. The Japanese approach, popularized by G. Taguchi, uses outcomes of statistical experiments to select settings for design parameters which yield desirable process mean and variance. In this paper we present mathematical models for incorporating the results of statistical performance models along with production costs into product design models. The objective of the models is to minimize the sum of quality loss, material and production costs. Costs are assumed to be functions of the design parameters. Statistical experiments are employed to aid in the development of quality performance models. Pertinent constraints include limits on the bias of the process mean and variance. The proposed approach permits a more general environment and utilizes a more direct, economic objective as compared to the Taguchi method. A product design example is presented.

KW - Manufacturing

KW - product design

KW - quality control

UR - http://www.scopus.com/inward/record.url?scp=0001567797&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0001567797&partnerID=8YFLogxK

U2 - 10.1080/03052158808941207

DO - 10.1080/03052158808941207

M3 - Article

VL - 14

SP - 139

EP - 152

JO - Engineering Optimization

JF - Engineering Optimization

SN - 0305-215X

IS - 2

ER -