scholarly journals Efficient Spot Welding Sequence Simulation in Compliant Variation Simulation

2020 ◽  
Author(s):  
Roham Sadeghi Tabar ◽  
Samuel Lorin ◽  
Christoffer Cromvik ◽  
Lars Lindkvist ◽  
Kristina Wärmefjord ◽  
...  
Keyword(s):  
Sheet Metal ◽  
Spot Welding ◽  
Traditional Approach ◽  
Optimal Sequence ◽  
Sequence Optimization ◽  
Welding Operation ◽  
Welding Sequence ◽  
Geometric Variation ◽  
Inspection Fixture ◽  
Assembly Fixture

Abstract Geometric variation is one of the sources of quality issues in a product. Spot welding is an operation that impacts the final geometric 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 geometric deformations of the assembly. Finding the optimal sequence that results in the minimum geometric deformation is a combinatorial problem that is experimentally and computationally expensive. For an assembly with N number of welds, there are N! possible sequences to perform the spot welding operation. Traditionally, spot welding optimization strategies have been to simulate the geometric variation of the spot-welded assembly after the assembly has been positioned in an inspection fixture, using an appropriate measure of variation. In this approach, the calculation of deformation after springback is one of the most time-consuming steps. In this paper, the cause of variation in the deformations after the springback, between different sequences is identified. The relative displacements of the weld points in the assembly fixture, when welded in a sequence, is the source of such behavior. Capturing these displacements leads to large time savings during sequence optimization. Moreover, this approach is independent of the inspection fixture. The relative weld displacements have been evaluated on two sheet metal assemblies. The sequence optimization problem has been solved for the two assemblies using this approach. The optimal sequence, the corresponding final assembly deformations, and the time-consumption have been compared to the traditional approach. The results show a significant correlation between the weld relative displacements in the assembly fixture, and the assembly deformation in the inspection fixture. Considering the relative weld displacement makes each assembly evaluation less time-consuming, and thereby, sequence optimization time can be reduced up to 30%, compared to the traditional approach.

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.

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.

Strategies for Optimization of Spot Welding Sequence With Respect to Geometrical Variation in Sheet Metal Assemblies

2010 ◽  
Author(s):  
Kristina Wa¨rmefjord ◽  
Rikard So¨derberg ◽  
Lars Lindkvist
Keyword(s):  
Case Studies ◽  
Sheet Metal ◽  
Spot Welding ◽  
Optimal Sequence ◽  
Factors Affecting ◽  
Critical Dimensions ◽  
Sheet Metal Parts ◽  
Geometrical Quality ◽  
Welding Sequence ◽  
Geometrical Variation

During the assembly process of sheet metal parts, a lot of factors affect the final geometrical quality. It is important to have knowledge about the characteristics of as many as possible of those factors, not only to be able to reduce their effect, but also to be able to include those factors in variation simulations. Those tolerance simulations are crucial tools in early stages in automotive industry in order to predict the outcome in critical dimensions and it is of course important to have as good accuracy as possible in the simulations. One of the factors affecting the final geometry is the spot welding sequence. In this paper it is shown how the spot welding sequence affects the amount of geometrical variation in a sheet metal assembly. A method for including the welding sequence in tolerance simulations is described. Of course, it is desirable to find an optimal sequence, i.e. a sequence that minimizes the geometrical variation in the final assembly. Since this is a fast growing problem — the number of possible sequences for N welding points is N!, it is not practicable to test all possible sequences. In this work some different strategies for finding an optimal sequence are tested on several industrial case studies. The tested strategies are based on general guidelines, on minimizing variation in each welding step respectively calculations of the movements in unwelded points in each step. The strategies based on general guidelines was not successful, neither was the one based on minimization of the variation in each step. The strategy based on movements in the unwelded points seems however promising. It resulted in the best or one of the better sequences for all of the eight tested industrial case studies.

A Novel Rule-Based Method for Individualized Spot Welding Sequence Optimization With Respect to Geometrical Quality

2019 ◽  
Vol 141 (11) ◽  
Author(s):  
Roham Sadeghi Tabar ◽  
Kristina Wärmefjord ◽  
Rikard Söderberg ◽  
Lars Lindkvist
Keyword(s):  
Genetic Algorithm ◽  
Sheet Metal ◽  
Spot Welding ◽  
Search Time ◽  
Search Problem ◽  
Optimization Approach ◽  
Hamiltonian Graph ◽  
Rule Based ◽  
Geometrical Quality ◽  
Welding Sequence

Abstract Spot welding is the predominant joining process for the sheet metal assemblies. The assemblies, during this process, are mainly bent and deformed. These deformations, along with the single part variations, are the primary sources of the 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 the geometrical quality can be categorized as a combinatorial Hamiltonian graph search problem. Exhaustive search to find the optimum, using the finite element method simulations in the 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 types 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.

scholarly journals Optimization of Spot Welding of An Assembly Like B-pillar of a Car For Minimum Distortion, By Sequencing Technique

2013 ◽  
pp. 295-300
Author(s):  
K. D. Hardikar ◽  
K. H. Inamdar ◽  
D. J. Nidgalkar
Keyword(s):  
Sheet Metal ◽  
Spot Welding ◽  
Spot Welds ◽  
Sequence Change ◽  
Welding Sequence ◽  
Sequencing Technique ◽  
Sheet Metal Assembly ◽  
Minimum Distortion

The aim of this paper is to achieve optimisation of spot welding sequence to minimise the distortion of a sheet metal assembly. The distortion of the assembly involving number of spot welds is different for different sequences of welding The assembly consists of sheet metal components which are joined by using various welding sequence schemes. The components are manufactured in quantity and welding with various sequences. After welding the distortions in an assembly due to welding sequence change are worked out and compaired. The sequence with minimum distortion is suggested a solution for the quality manufacturing with minimum distortion induced in it.

A Method to Define the Best Weld Sequence Using a Limited Number of Welding Simulation Analysis

2015 ◽  
Author(s):  
Mahyar Asadi ◽  
Ghazi Alsoruji
Keyword(s):  
Simulation Model ◽  
Surrogate Model ◽  
Simulation Analysis ◽  
Combinatorial Problem ◽  
Fem Analysis ◽  
Simulation Models ◽  
Computational Time ◽  
Optimal Sequence ◽  
Welded Structure ◽  
Welding Sequence

Weld sequence optimization, which is determining the best (and worst) welding sequence for welding work pieces, is a very common problem in welding design. The solution for such a combinatorial problem is limited by available resources. Although there are fast simulation models that support sequencing design, still it takes long because of many possible combinations, e.g. millions in a welded structure involving 10 passes. It is not feasible to choose the optimal sequence by evaluating all possible combinations, therefore this paper employs surrogate modeling that partially explores the design space and constructs an approximation model from some combinations of solutions of the expensive simulation model to mimic the behavior of the simulation model as closely as possible but at a much lower computational time and cost. This surrogate model, then, could be used to approximate the behavior of the other combinations and to find the best (and worst) sequence in terms of distortion. The technique is developed and tested on a simple panel structure with 4 weld passes, but essentially can be generalized to many weld passes. A comparison between the results of the surrogate model and the full transient FEM analysis all possible combinations shows the accuracy of the algorithm/model.

Investigation of friction stir spot welding of high density polyethylene and polypropylene sheets

2021 ◽  
pp. 009524432110015
Author(s):  
Mustafa Kemal Bilici
Keyword(s):  
High Density Polyethylene ◽  
Spot Welding ◽  
Friction Stir Spot Welding ◽  
Polymer Materials ◽  
Weld Strength ◽  
Tool Rotational Speed ◽  
Friction Stir ◽  
Welding Operation ◽  
Stirring Time ◽  
Welding Materials

In this study, two different polymer materials were used. In the joints made with friction stir spot welding, firstly (PP/PP and HDPE/HDPE) and then different materials (PP/HDPE, HDPE/PP) joining processes were carried. The influence of the tool rotational speed and the stirring time on joint formation and weld strength were determined. The temperature of the liquid welding materials varies according to the materials to be combined. High weld strengths were obtained at the friction stir spot welding of similar plastic sheets. The highest weld strengths were obtained in PP-PP welds. Low weld strengths were obtained at the friction stir spot welding of dissimilar plastic sheets because of immiscible and incompatible blends formed during the welding operation. The lowest weld strengths were obtained in PP-HDPE welds. The chemical composition and the phase morphology of the blends, the mechanical scission occurrence and the welding residual stresses determine the strength of the welds.

Path planning of spot welding robot based on multi-objective grey wolf algorithm

2021 ◽  
pp. 1-9
Author(s):  
Yun-Tao Zhao ◽  
Lei Gan ◽  
Wei-Gang Li ◽  
Ao Liu
Keyword(s):  
Path Planning ◽  
Density Estimation ◽  
Spot Welding ◽  
Teaching Method ◽  
Grey Wolf ◽  
Pareto Solution ◽  
Multi Objective ◽  
Operation Rules ◽  
Welding Sequence ◽  
Body In White

The path planning of traditional spot welding mostly uses manual teaching method. Here, a new model of path planning is established from two aspects of welding length and welding time. Then a multi-objective grey wolf optimization algorithm with density estimation (DeMOGWO) is proposed to solve multi-object discrete problems. The algorithm improves the coding method and operation rules, and sets the density estimation mechanism in the environment update. By comparing with other five algorithms on the benchmark problem, the simulation results show that DeMOGWO is competitive which takes into account both diversity and convergence. Finally, the DeMOGWO algorithm is used to solve the model established of path planning. The Pareto solution obtained can be used to guide the welding sequence of body-in-white(BIW) workpieces.

Evaluating Genetic Algorithms on Welding Sequence Optimization With Respect to Dimensional Variation and Cycle Time

2011 ◽  
Author(s):  
Johan Segeborn ◽  
Johan S. Carlson ◽  
Kristina Wa¨rmefjord ◽  
Rikard So¨derberg
Keyword(s):  
Genetic Algorithms ◽  
Significant Influence ◽  
Cycle Time ◽  
Spot Welding ◽  
Fitness Function ◽  
Welding Robot ◽  
Single Criterion ◽  
Welding Sequence ◽  
Dimensional Variation ◽  
Welding Sequences

Spot welding is the predominant joining method in car body assembly. Spot welding sequences have a significant influence on the dimensional variation of resulting assemblies and ultimately on overall product quality. It also has a significant influence on welding robot cycle time and thus ultimately on manufacturing cost. In this work we evaluate the performance of Genetic Algorithms, GAs, on multi-criteria optimization of welding sequence with respect to dimensional assembly variation and welding robot cycle time. Reference assemblies are fully modelled in 3D including detailed fixtures, welding robots and weld guns. Dimensional variation is obtained using variation simulation and part measurement data. Cycle time is obtained using automatic robot path planning. GAs are not guaranteed to find the global optimum. Besides exhaustive calculations, there is no way to determine how close to the actual optimum a GA trial has reached. Furthermore, sequence fitness evaluations constitute the absolute majority of optimization computation running time and do thus need to be kept to a minimum. Therefore, for two industrial reference assemblies we investigate the number of fitness evaluations that is required to find a sequence that is optimal or a near-optimal with respect to the fitness function. The fitness function in this work is a single criterion based on a weighted and normalized combination of dimensional variation and cycle time. Both reference assemblies involves 7 spot welds which entails 7!=5040 possible welding sequences. For both reference assemblies, dimensional variation and cycle time is exhaustively calculated for all 5040 possible sequences, determining the optimal sequence, with respect to the fitness function, for a fact. Then a GA that utilizes Random Key Encoding is applied on both cases and the performance is recorded. It is found that in searching through about 1% of the possible sequences, optimum is reached in about half of the trials and 80–90% of the trials reach the ten best sequences. Furthermore the optimum of the single criterion fitness function entails dimensional variation and cycle time fairly close to their respective optimum. In conclusion, this work indicates that genetic algorithms are highly effective in optimizing welding sequence with respect to dimensional variation and cycle time.

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