A Novel Rule-Based Method For Individualized Spot Welding Sequence Optimization With Respect to Geometrical Quality
Journal article, 2019

Spot welding is the predominant joining process for sheet metal assemblies. The assemblies, during this process, are mainly bent and deformed. These deformations along with single part variations are the main sources of aesthetic and functional geometrical problems in an assembly. The sequence of welding has a considerable effect on the geometrical variation of the final assembly. Finding the optimal weld sequence for geometrical quality can be categorized as a Hamiltonian graph search problem which is of combinatorial non-deterministic polynomial acceptable problems. Exhaustive search to find the optimum, using the FEM simulations in computer-aided tolerancing tools, is a time-consuming and thereby infeasible task. Applying the genetic algorithm to this problem can considerably reduce the search time but finding the global optimum is not guaranteed and still, a large number of sequences need to be evaluated. The effectiveness of these type of algorithms is dependent on the quality of the initial solutions. Previous studies have attempted to solve this problem by random initiation of the population in the genetic algorithm. In this paper, a rule-based approach for initiating the genetic algorithm for spot-weld sequencing is introduced. The optimization approach is applied to three automotive sheet metal assemblies for evaluation. The results show that the proposed method improves the computation time and effectiveness of the genetic algorithm.

assembly

inspection and quality control

control and automation

modeling and simulation

welding and joining

Author

Roham Sadeghi Tabar

Chalmers, Industrial and Materials Science, Product Development

Kristina Wärmefjord

Chalmers, Industrial and Materials Science, Product Development

Rikard Söderberg

Chalmers, Industrial and Materials Science

Lars Lindkvist

Chalmers, Industrial and Materials Science, Product Development

Journal of Manufacturing Science and Engineering, Transactions of the ASME

1087-1357 (ISSN)

Vol. 141 11 111013

Smart Assembly 4.0

Swedish Foundation for Strategic Research (SSF), 2016-05-01 -- 2021-06-30.

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Manufacturing, Surface and Joining Technology

Control Engineering

Areas of Advance

Production

DOI

10.1115/1.4044254

More information

Latest update

12/3/2019