Efficient Spot Welding Sequence Optimization in a Geometry Assurance Digital Twin

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.

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EFFICIENT SPOT WELDING SEQUENCE SIMULATION IN COMPLIANT VARIATION SIMULATION

Journal of Manufacturing Science and Engineering ◽

10.1115/1.4049654 ◽

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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Efficient Spot Welding Sequence Simulation in Compliant Variation Simulation

Volume 2B: Advanced Manufacturing ◽

10.1115/imece2020-23798 ◽

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.

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

Volume 3: Design and Manufacturing, Parts A and B ◽

10.1115/imece2010-38471 ◽

2010 ◽

Cited By ~ 13

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.

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

Journal of Manufacturing Science and Engineering ◽

10.1115/1.4044254 ◽

2019 ◽

Vol 141 (11) ◽

Cited By ~ 3

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.

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Welding sequence optimisation in the automotive industry: A review

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1177/0954406219859909 ◽

2019 ◽

Vol 233 (17) ◽

pp. 5945-5952

Author(s):

Varshan Beik ◽

Hormoz Marzbani ◽

Reza Jazar

Keyword(s):

Automotive Industry ◽

Spot Welding ◽

Fast Rate ◽

Welding Process ◽

Future Research ◽

Automotive Body ◽

Welding Sequence ◽

Common Technique ◽

The Common

Spot welding is the most common technique used to join sheet metals in the automotive industry due to the fast rate of production. Optimising the welding process including the sequence, number and location of the welds would significantly improve the quality of the final product and production cost. This paper presents an overview on the available methods to plan and optimise various aspects of the welding process including welding sequence, weld quantity and location. Firstly, the welding concept in the automotive industry is briefly reviewed. Secondly, the welding process optimisation with emphasis on the welding sequence is discussed. The common gaps and challenges are identified and, lastly, future research to plan and optimise the welding sequence in the automotive body is outlined.

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EFFECT OF SPOT WELD POSITION VARIATION ON QUALITY OF AUTOMOBILE SHEET METAL PARTS

International Journal of Applied Research in Mechanical Engineering ◽

10.47893/ijarme.2013.1081 ◽

2013 ◽

pp. 170-174

Author(s):

M.P. MALI ◽

K.H. INAMDAR

Keyword(s):

Welding Process ◽

The Body ◽

Spot Weld ◽

Spot Welds ◽

Factors Affecting ◽

Sheet Metal Parts ◽

Geometrical Quality ◽

Welding Sequence ◽

Geometrical Factors

Resistance spot welding is the most preferred and widely used method for joining metal sheets in automotive and many other industrial assembly operations. The body of a car is typically joined by thousands of spot welds. One of the many geometrical factors affecting the final geometrical outcome of the metal part assemblies is the welding process considering welding sequence used when the parts are welded together. The spot welds guarantee the strength of the car, but their positions also affect the geometrical quality of subassemblies and the final product. In practice, the positions of the weld points often deviate from nominal position. By analyzing industrial scanning data, deviations of spot weld positions are found to be of magnitudes up to 19 mm. In this paper, the influence of variation in position of spot welds is investigated with respect to geometrical quality, by simulating and analyzing the geometrical variation of an A-pillar assembly.

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A new surrogate model–based method for individualized spot welding sequence optimization with respect to geometrical quality

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-019-04706-x ◽

2019 ◽

Vol 106 (5-6) ◽

pp. 2333-2346 ◽

Cited By ~ 6

Author(s):

Roham Sadeghi Tabar ◽

Kristina Wärmefjord ◽

Rikard Söderberg

Keyword(s):

Surrogate Model ◽

Spot Welding ◽

Fem Simulation ◽

Global Optimum ◽

Neural Network Approach ◽

Model Based ◽

Heuristic Search Algorithms ◽

Geometrical Quality ◽

Functional Quality ◽

Welding Sequence

AbstractIn an individualized shee metal assembly line, form and dimensional variation of the in-going parts and different disturbances from the assembly process result in the final geometrical deviations. Securing the final geometrical requirements in the sheet metal assemblies is of importance for achieving aesthetic and functional quality. Spot welding sequence is one of the influential contributors to the final geometrical deviation. Evaluating spot welding sequences to retrieve lower geometrical deviations is computationally expensive. In a geometry assurance digital twin, where assembly parameters are set to reach an optimal geometrical outcome, a limited time is available for performing this computation. Building a surrogate model based on the physical experiment data for each assembly is time-consuming. Performing heuristic search algorithms, together with the FEM simulation, requires extensive evaluations times. In this paper, a neural network approach is introduced for building surrogate models of the individual assemblies. The surrogate model builds the relationship between the spot welding sequence and geometrical deviation. The approach results in a drastic reduction in evaluation time, up to 90%, compared to the genetic algorithm, while reaching a geometrical deviation with marginal error from the global optimum after welding in a sequence.

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