.png){kind=icon}
返回
Methodology for capturing and formalizing DFM Knowledge
.png){kind=icon}
PRE
AI
DOI：10.1016/j.rcim.2009.12.003.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
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.
Keyword:
Design for manufacturing (DFM)
Manufacturing knowledge
Integration of design and manufacturing
Axiomatic Design
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
R
IF:
11.4
论文数:
3.3K
被引数:
1.3W
机构
引用论文
Manufacturing process selection in engineering design. Part 2: a methodology for creating task-based process selection procedures.png)
MATERIALS & DESIGN
MATERIALS & DESIGNIF7.9
PREAI
分享收藏Thermoelectric properties of Cr-doped higher manganese silicides prepared using spark plasma sinteringMRS Advances
MRS AdvancesIF0
PREAI
分享收藏A model for integrating process planning and production planning and control in machining processes在加工过程中集成工艺计划和生产计划与控制的模型
PREAI
分享收藏分享收藏Axiomatic design as support for decision-making in a design for manufacturing context:: A case study
PREAI
分享收藏
查看更多内容