Methodology for capturing and formalizing DFM Knowledge

被引：26

作者：

Ferrer, I. ^{[1
]}

Rios, J. ^{[2
]}

Ciurana, J. ^{[3
]}

Garcia-Romeu, M. L. ^{[3
]}

机构：

[1] Univ Girona, Dept Business Adm Management & Prod Design, Girona 17071, Spain

[2] Tech Univ Madrid, Dept Mech Engn & Mfg, Madrid, Spain

[3] Univ Girona, Dept Mech Engn & Ind Construct, Girona 17071, Spain

来源：

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING | 2010年 / 26卷 / 05期

关键词：

Design for manufacturing (DFM); Manufacturing knowledge; Integration of design and manufacturing; Axiomatic Design; DESIGN PROCESS; PROCESS SELECTION; MODEL;

D O I：

10.1016/j.rcim.2009.12.003

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Design for manufacturing (DFM) practices lead to more competitive products from the point of view of cost, development time and quality. However, the success of considering manufacturing issues during design process would be higher if manufacturing information was more readily available and designers needed less experience to select information relevant to DFM. This paper presents a method for identifying and formalizing the relevant manufacturing information that designer should have available for DFM. The method is based on the Axiomatic Design theory W. It helps the designer capture the relationship between design and manufacturing information. The information related to obtaining the design parameters that achieve product functionalities is the most relevant DFM information. A case study where the method is applied to the design of a connecting rod for an alternative internal combustion engine is presented. The manufacturing processes considered were hot closed die forging and powder metallurgy. (C) 2009 Elsevier Ltd. All rights reserved.

引用

页码：420 / 429

页数：10

共 50 条

[1] Knowledge capturing methodology in process planning
Park, SC
[J]. COMPUTER-AIDED DESIGN, 2003, 35 (12) : 1109 - 1117
[2] FORMALIZING THE SOCIAL EXPERTS KNOWLEDGE
CARLEY, K
[J]. SOCIOLOGICAL METHODS & RESEARCH, 1988, 17 (02) : 165 - 232
[3] A Methodology for Formalizing Different Types of Norms
Roshankish, Soheil
Fornara, Nicoletta
[J]. MULTI-AGENT SYSTEMS, EUMAS 2022, 2022, 13442 : 348 - 363
[4] A methodology for formalizing GDMO behavior descriptions
Hasselmeyer, P
[J]. INTEGRATED NETWORK MANAGEMENT VI: DISTRIBUTED MANAGEMENT FOR THE NETWORKED MILLENNIUM, 1999, : 431 - 445
[5] A Design Thinking Process Model for Capturing and Formalizing Design Intents
Sun, Zhaoyang
Liu, Jihong
[J]. PROCEEDINGS OF THE 2008 INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN, VOL 2, 2008, : 330 - 333
[6] APPLICATIONS OF CIRCUMSCRIPTION TO FORMALIZING COMMONSENSE KNOWLEDGE
MCCARTHY, J
[J]. ARTIFICIAL INTELLIGENCE, 1986, 28 (01) : 89 - 116
[7] Robust PPC and DFM methodology for exposure tool variations
Kotani, Toshiya
Nakajima, Fumiharu
Mashita, Hiromitsu
Sato, Kazuya
Tanaka, Satoshi
Inoue, Soichi
[J]. OPTICAL MICROLITHOGRAPHY XXI, PTS 1-3, 2008, 6924
[8] A Methodology for Formalizing Model-Inversion Attacks
Wu, Xi
Fredrikson, Matthew
Jha, Somesh
Naughton, Jeffrey F.
[J]. 2016 IEEE 29TH COMPUTER SECURITY FOUNDATIONS SYMPOSIUM (CSF 2016), 2016, : 355 - 370
[9] Towards a Methodology for Formalizing Legal Texts in LegalRuleML
Nazarenko, Adeline
Levy, Francois
Wyner, Adam
[J]. LEGAL KNOWLEDGE AND INFORMATION SYSTEMS, 2016, 294 : 149 - 154
[10] A reuse oriented representation model for capturing and formalizing the evolving design rationale
Liu, Jihong
Hu, Xujie
[J]. AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING, 2013, 27 (04): : 401 - 413

← 1 2 3 4 5 →