Welding sequence optimization for the fabrication of Box Girder

2016 ◽  
Author(s):  
Muhammad Faiq ◽  
Rizwan Alim Mufti
Keyword(s):  
Box Girder ◽  
Sequence Optimization ◽  
Welding Sequence

A Reinforcement Learning Based Approach for Welding Sequence Optimization

2017 ◽  
pp. 33-45 ◽  
Author(s):  
Jesus Romero-Hdz ◽  
Baidya Saha ◽  
Gengis Toledo-Ramirez ◽  
Ismael Lopez-Juarez
Keyword(s):  
Reinforcement Learning ◽  
Sequence Optimization ◽  
Welding Sequence

Efficient Spot Welding Sequence Optimization in a Geometry Assurance Digital Twin

2020 ◽  
Vol 142 (10) ◽  
Author(s):  
Roham Sadeghi Tabar ◽  
Kristina Wärmefjord ◽  
Rikard Söderberg ◽  
Lars Lindkvist
Keyword(s):  
Spot Welding ◽  
Welding Process ◽  
Combinatorial Problems ◽  
Optimal Sequence ◽  
Sequence Optimization ◽  
Digital Twin ◽  
Final Assembly ◽  
Geometrical Quality ◽  
Welding Sequence ◽  
The Individual

Abstract A digital twin for geometry assurance contains a set of analyses that are performed to steer the real production for securing the geometry of the final assembly. In sheet metal assemblies, spot welding is performed to join the parts together. The sequence of the welding has a considerable influence on the geometrical outcome of the final assembly. In industry, the sequence of welding to secure the geometry is mainly derived by tacit manufacturing knowledge. Including such knowledge to mimic the production process requires extensive knowledge management, and the result might be just a good enough solution. Theoretically, spot welding sequence optimization for the optimal geometrical quality is among NP-hard combinatorial problems. In a geometry assurance digital twin, where assembly parameters are selected for the individual assemblies, time constraints define the quality of the optimal sequence. In this paper, an efficient method for spot welding sequence optimization with regards to the geometrical quality is introduced. The results indicate that the proposed method reduces 60–80% of the time for the sequencing of the spot welding process to achieve the optimal geometrical quality.

An Elitism Based Genetic Algorithm for Welding Sequence Optimization to Reduce Deformation

2016 ◽  
Vol 121 (1) ◽  
pp. 17-36 ◽  
Author(s):  
Jesus Romero-Hdz ◽  
Sinai Aranda ◽  
Gengis Toledo-Ramirez ◽  
Jose Segura ◽  
Baidya Saha
Keyword(s):  
Genetic Algorithm ◽  
Sequence Optimization ◽  
Welding Sequence

scholarly journals EFFICIENT SPOT WELDING SEQUENCE SIMULATION IN COMPLIANT VARIATION SIMULATION

2021 ◽  
pp. 1-13
Author(s):  
Roham Sadeghi Tabar ◽  
Samuel Lorin ◽  
Christoffer Cromvik ◽  
Lars Lindkvist ◽  
Kristina Wärmefjord ◽  
...  
Keyword(s):  
Spot Welding ◽  
Traditional Approach ◽  
Combinatorial Problem ◽  
Optimal Sequence ◽  
Sequence Optimization ◽  
Influence Coefficients ◽  
Assembly Simulation ◽  
Welding Sequence ◽  
Geometrical Variation ◽  
Inspection Fixture

Abstract Geometrical variation is one of the sources of quality issues in a product. Spot welding is an operation that impacts the final geometrical variation of a sheet metal assembly considerably. Evaluating the outcome of the assembly, considering the existing geometrical variation between the components, can be achieved using the Method of Influence Coefficients (MIC), based on the Finite Element Method (FEM). The sequence with which the spot welding operation is performed influences the final geometrical deformations of the assembly. Finding the optimal sequence that results in the minimum geometrical deformation is a combinatorial problem that is experimentally and computationally expensive. Traditionally, spot welding sequence optimization strategies have been to simulate the geometrical variation of the spot-welded assembly after the assembly has been positioned in an inspection fixture. In this approach, the calculation of deformation after springback is one of the most time-consuming steps. In this paper, a method is proposed where the springback calculation in the inspection fixture is bypassed during the sequence evaluation. The results show a significant correlation between the proposed method of weld relative displacements evaluation in the assembly fixture and the assembly deformation in the inspection fixture. Evaluating the relative weld displacement makes each assembly simulation less time-consuming, and thereby, sequence optimization time can be reduced by up to 30%, compared to the traditional approach.

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