Rapid sequence optimization of spot welds for improved geometrical quality using a novel stepwise algorithm

Abstract

Joining sequence optimization is a combinatorial problem, requiring extensive computational time. The significance of determination of an optimal sequence for improved geometrical quality is substantial. Previously, genetic algorithms have been studied for defining the optimal sequence. However, these algorithms are highly dependent on the internal parameters, requiring additional computational analysis and thereby extended evaluation time. In this article, a novel robust stepwise algorithm is introduced to determine the optimal weld sequence. Application of the proposed algorithm leads to drastic time improvements for defining the optimal weld sequence of each assembly. Three industrial assemblies are evaluated. Comparison with the previously applied population-based optimization algorithms indicates that the optimization time can be reduced drastically with the proposed stepwise algorithm. The stepwise algorithm is intended to be applied in a geometry assurance digital twin, where the assembly parameters are being optimized for each individual assembly.

Digital Twin-Based Clamping Sequence Analysis and Optimization for Improved Geometric Quality

“…In the twin, the critical welding points are being identified, and the sequence is deterministically decided for the existing error after fixturing [37]. A rapid sequence optimization approach has been specifically developed for this purpose [38]. In the geometry assurance twin, the clamping step has been considered to take place simultaneously with the locating step.…”

“…To solve the optimization problem (10), a stepwise algorithm introduced in [38] for welding sequence optimization is adapted to the clamping sequence problem. The algorithm is based on a greedy search with the backward propagation of the sequence element while spanning the state-space tree at each decision step.…”

Metrology of Sheet Metal Distortion and Effects of Spot-Welding Sequences on Sheet Metal Distortion

“…In general, sheet metal distortion and the residual stresses produced by a sheet metal assembly process are critical challenges to address since they cause unfavorable stresses and unwanted structural variations in aircraft assemblies. Researchers studied sheet metal distortion and the residual stresses produced by riveting [26,27] and resistance spot welding [28,29] using finite element methods. Riveting is a standard joining method in aircraft manufacturing with well-established industrial standards [30].…”

Critical joint identification for efficient sequencing

“…Using the neural networks, a surrogate modeling approach has been introduced, representing the sequence-deformation relationship of the assembly [22]. A new stepwise algorithm has also been introduced to identify the optimal welding sequence with the minimum number of evaluations with the method presented above [23]. In most of the studies, the aim is to present a complete sequence that results in the minimum assembly deformations after joining.…”

“…Other integer programming methods for joining sequence optimization, require recursive cost matrices (assembly deviation with FEM) for each element of the sequence. Based on this aspect, a stepwise algorithm is introduced for complete sequence optimization [23]. Since the focus on this paper is on sequence evaluation and identification of the critical weld points, the previous critical weld point identification method, presented in [20] is compared to the proposed approach.…”