An Intelligent Design for Manufacturability System for Sheet-metal Parts

Author:

de Sam Lazaro Anthony1,Engquist David T.1,Edwards Dean B.2

Affiliation:

1. Department of Mechanical and Materials Engineering, Washington State University, Pullman, Washington 99164-2920, USA

2. Department of Mechanical Engineering, University of Idaho, Moscow, Idaho, USA

Abstract

A knowledge-based system used for the design of sheet-metal parts is described in this paper. The system is called Sheet Metal Advisor and Rule Tutor (SMAART) and acts as an advisor to engineers designing sheet-metal parts for high volume—low cost production using progressive dies. SMAART uses a commercial object-oriented development environment and has been designed to interface with different CAD systems. It also integrates a feature-based CAD module. When SMAART discovers the violation of a design rule, the engineer is alerted via an advisory window and then has the opportunity to change that part of the design to improve its manufacturability.

Publisher

SAGE Publications

Subject

Computer Science Applications,General Engineering,Modelling and Simulation

Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Intelligent template based die face design method for process reuse of automotive panel;IOP Conference Series: Materials Science and Engineering;2022-12-01

2. A systematic method for automated manufacturability analysis of machining parts;The International Journal of Advanced Manufacturing Technology;2022-07-20

3. Near net shape manufacturing of metal: A review of approaches and their evolutions;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2017-05-12

4. Feature Extraction and Manufacturability Assessment of Sheet Metal Parts;AI Applications in Sheet Metal Forming;2016-10-28

5. Feature-based metal stamping part and process design. Part I: stampability evaluation;International Journal of Production Research;2007-06-15

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3