Design evaluation of sheet metal joints for dimensional integrity

被引:38
作者
Ceglarek, D [1 ]
Shi, J
机构
[1] Univ Michigan, Dept Mech Engn & Appl Mech, Ann Arbor, MI 48109 USA
[2] Univ Michigan, Dept Ind & Operat Engn, Ann Arbor, MI 48109 USA
来源
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME | 1998年 / 120卷 / 02期
关键词
D O I
10.1115/1.2830146
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The design of joints between parts is one of the most critical issues in the design of sheet metal assemblies. This paper presents a new part-to-part joint design evaluation index developed for dimensional control of sheet metal assemblies. The proposed index provides a new analytical tool to address the; dimensional capabilities of an assembly process in the early product design stage. It covers the three basic types of joints, which encompass the whole domain of joints used in sheet metal assembly. The part-to-part interactions for each type of joint are studied, and an analytical model is provided. Two evaluation indices, (1) product joint design evaluation and (2) critical part determination are developed. The developed methodology is demonstrated using two industrial design examples of sport-utility automotive bodies.
引用
收藏
页码:452 / 460
页数:9
相关论文
共 31 条
[11]  
CEGLAREK DJ, 1994, THESIS U MICHIGAN AN
[12]  
ELGIZAWY AS, 1990, MANUFACTURING REV, V3, P178
[13]  
GADH R, 1993, P 19 ANN ASME DES AU, V65, P273
[14]  
HIMBERT M, 1996, MANAGING DIMENSIONAL
[15]   Sensor location optimization for fault diagnosis in multi-fixture assembly systems [J].
Khan, A ;
Ceglarek, D ;
Ni, J .
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 1998, 120 (04) :781-792
[16]  
KRAMER GA, 1990, PROCEEDINGS : EIGHTH NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOLS 1 AND 2, P708
[17]  
LEE S, 1995, P 1995 IEEE INT S AS, P94
[18]  
LEE S, 1995, P 1995 IEEE INT C IN, V3, P256
[19]  
LIU Y, 1990, PROCEEDINGS : EIGHTH NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOLS 1 AND 2, P1038
[20]  
Medoff S. M., 1989, (AI EDAM) Artificial Intelligence for Engineering Design, Analysis and Manufacturing, V3, P71, DOI 10.1017/S0890060400001128