Virtual Distortion Engineering for Automotive BiW: Keysight Assembly Simulation Transforms Digital Assembly Validation

Introduction

Automotive manufacturing is undergoing rapid transformation as vehicle architectures evolve to accommodate electrification, lightweight design, and increasingly stringent safety standards. These changes have placed new demands on Body-in-White (BiW) structures, which form the structural backbone of a vehicle. Modern BiW systems integrate advanced high-strength steels, aluminium components, and complex multi-material joints while maintaining tight dimensional tolerances across large assemblies.

While this article focuses on automotive BiW applications, similar assembly challenges arise in other industries that use complex welded structures, such as heavy machinery and industrial equipment. Future developments of assembly simulation solutions are expected to address these broader applications.

At the same time, vehicle development cycles are shortening, putting pressure on manufacturing engineering teams to validate assembly processes earlier in the design phase. In this environment, even small geometric deviations introduced during component manufacturing can propagate through the assembly process, producing unexpected distortions in the final structure.

Historically, such distortions were detected during physical try-out phases, where engineers evaluated prototype assemblies and iteratively adjusted fixtures, clamps, and welding sequences. Although effective, this approach requires significant time, tooling resources, and access to production equipment. When issues emerge late in the development cycle, the resulting fixture modifications or process adjustments can introduce substantial delays and additional costs. To mitigate these risks, manufacturers are increasingly adopting simulation-driven approaches that enable analysis of assembly processes before physical prototypes are built. By digitally modelling fixture behavior, welding operations, and part deviations, engineers can predict and quantify distortions earlier and explore corrective strategies during the engineering phase.

One such approach is implemented in Keysight Assembly, part of Keysight’s CAE Manufacturing Suite, which enables engineers to simulate automotive assembly processes and evaluate distortion behavior in a virtual environment. Through virtual distortion engineering, manufacturers can better understand how part geometry, clamping forces, and welding sequences interact during assembly ^[1].

Assembly Challenges in Automotive Body-in-White Manufacturing

Deviation from Nominal Geometry

In digital product development environments, CAD models define the intended geometry of vehicle components with high precision. However, physically manufactured parts rarely match these idealised geometries exactly. Manufacturing processes such as stamping, trimming, and even handling introduce small deviations that alter the shape of individual components.

During sheet-metal forming operations, components often exhibit elastic springback, in which the material partially returns to its original shape once the forming forces are removed. This phenomenon becomes more pronounced in modern vehicle structures that rely heavily on high-strength steels or lightweight alloys. Even minor springback effects can lead to measurable differences between nominal CAD geometry and manufactured part geometry.

Because a typical vehicle body contains hundreds of sheet-metal components, these deviations accumulate across the structure. When multiple components and assembled different geometries are assembled, the resulting interactions can introduce internal stresses or dimensional inconsistencies.

Interaction Between Clamping and Welding

Assembly fixtures are designed to position components accurately before they are permanently joined. During production, clamps apply forces that align individual parts within the fixture system and keep them fixed in position. This process ensures that weld locations meet design specifications during joining operations.

However, when parts deviate from nominal geometry, clamps must compensate by forcing components into contact. This action introduces artificial stresses into the structure. While these stresses remain present during clamping, they become particularly significant once welding is complete.

Resistance spot welding, the most common joining technique in automotive BiW manufacturing, permanently connects the components while they remain constrained within the fixture system. When the clamps are subsequently released, the stresses introduced during clamping are partially relieved. Because the welded components are now connected, they cannot fully return to their original shapes.

In addition to geometric deviations, thermal effects from the welding process also contribute to distortion. Localised heating and cooling introduce residual stresses, which can further influence the final geometry.

The result is often distortion in the final welded assembly, which can manifest as dimensional variation, panel misalignment, or surface deformation. These distortions are influenced by multiple factors, including the sequence of welds, fixture configuration, material properties, and the initial geometry of the parts, ultimately influencing the overall geometrical quality of the assembly.

Late Discovery of Assembly Issues

Traditionally, distortion problems are detected during the physical pre-production phases. Engineers analyse prototype assemblies to identify dimensional deviations and adjust fixture configurations accordingly. These adjustments may involve repositioning clamps, modifying weld sequences, or redesigning portions of the fixture system.

While such corrections can eventually produce acceptable results, they require repeated iterations and significant engineering effort. In many cases, assembly problems are discovered late in the development timeline, when opportunities for major design changes are limited. In extreme cases, resolving these distortions may require modifications to individual components, particularly when stamping tools have already been finalised. As a result, manufacturers are increasingly seeking ways to predict assembly behavior earlier in the development process.

Virtual Distortion Engineering

Simulation-based manufacturing methods offer a way to analyse assembly processes before physical tooling is available. By replicating the sequence of operations used in real production environments, engineers can evaluate how distortion in component geometry influences the overall geometrical quality.

This methodology, also known as virtual distortion engineering, combines digital models of parts, fixtures, and welding operations to simulate the mechanical interactions that occur during assembly.

Within this context, Keysight Assembly provides a simulation environment initially focused on automotive assembly engineering, with future expansion planned across industries and joining technologies. The platform allows engineers to replicate real production workflows digitally, enabling early analysis of distortion behavior and process optimisation.

Overview of the Assembly Simulation Environment

Purpose and Scope

Keysight Assembly was developed as a domain-specific simulation environment for automotive Body-in-White assembly. Rather than functioning as a general finite-element tool, it is structured around the realities of production-line workflows ^[2].

The software has been developed in close collaboration with industrial partners and early adopters worldwide, ensuring alignment with real production workflows and integration with existing CAD, PLM, and simulation ecosystems.

The first release focuses specifically on resistance spot welding, reflecting its dominant role in automotive structural assembly. By integrating spot weld modelling as the initial supported joining process, the platform enables detailed analysis of weld sequencing, clamp interaction, and distortion behavior. While the current implementation focuses on automotive Body-in-White applications, the platform is designed as a scalable solution to support a broader range of industries, materials, and assembly processes as additional capabilities are introduced.

A central design objective during the software development has been usability for assembly practitioners. The workflow mirrors real shop-floor operations, making the software intuitive to use and allowing assembly engineers to work within familiar manufacturing concepts without requiring expertise in numerical simulation or finite element methods, as underlying numerical complexity is not exposed to the user.

Supported Assembly Activities

The platform enables modelling of key assembly operations, including:

• Fixture and jig definition

• Clamp positioning and sequencing

• Resistance spot welding placement and order

• Robot-based weld assignment

• Clamp release and resulting distortion prediction

By replicating the physical sequence of loading, clamping, welding, and unclamping, the software allows engineers to analyse assembly distortion within a digital environment before tooling is finalised.

Workflow-Driven Assembly Modelling

Multi-Station and Multi-Cell Assembly Representation

Automotive Body-in-White production typically involves multiple stations and cells, where subassemblies are progressively joined to form larger structural modules. Floor panels, side frames, roof structures, and cross-members are often assembled in stages before being integrated into the complete vehicle body.

Keysight Assembly reflects this production logic through a workflow-driven modelling environment. Engineers can define assembly operations using a structured station-based approach that mirrors real manufacturing lines. Fixtures, clamps, and welding operations are organised within virtual stations that correspond to physical production cells. Assembly processes can be quickly configured using intuitive drag-and-drop operations, making the workflow efficient and easy to use

Subassemblies created at one stage can be reused as inputs for downstream stations. This allows distortion effects introduced early in the process to propagate naturally through subsequent assembly steps, enabling realistic prediction of cumulative geometric variation.

By aligning the simulation workflow with actual production logic, the environment allows assembly engineers to work within a familiar conceptual framework rather than constructing abstract numerical models.

Progressive Data Evolution

Assembly simulation does not begin with perfect manufacturing data. At early stages of vehicle development, only nominal CAD geometry may be available. However, real assembly behavior depends on the geometry of manufactured parts within production tolerances.

In some cases, additional data may be available from previous vehicle programs, particularly when components are reused. Simulation results or scan data from earlier projects can sometimes provide useful geometric references during early development phases.

However, in many programs, detailed stamping simulations are not yet completed when assembly engineering begins. Even when forming simulations exist, fully compensated geometry may not yet be available. This creates a gap between design intent and realistic assembly input data.

To address this, the workflow integrates an automatic stamping capability that generates realistic as-stamped geometry early in the process. This enables engineers to move beyond purely nominal CAD data and incorporate expected forming-induced deviations into assembly simulations from the outset.

This approach reduces dependency on specialised stamping expertise in early phases and allows assembly engineers to work more independently, reducing iteration time between teams and accelerating early-stage validation. As development progresses, geometry data can be updated using refined simulation results or scans of physically manufactured parts, without rebuilding the entire assembly workflow. This continuity ensures that simulation models evolve alongside the program lifecycle while preserving the integrity of previously defined assembly logic.

Virtual Inspection and Analysis

In addition to simulating assembly operations, the software provides tools to evaluate assembly quality at various stages of the process. After each operation, engineers can analyse the assembly’s structural behavior using virtual inspection checkpoints.

These analyses allow engineers to examine:

• Distortion before and after clamp release

• Residual gaps between components

• Contact pressure distribution

• Stress accumulation within welded structures

By quantifying these effects, engineers can iteratively adjust fixture layouts, refine clamp sequencing, and optimise weld placement and welding sequence based on simulation results rather than iterative physical testing. This data-driven approach supports fine-tuning of assembly strategies to improve dimensional stability and reduce downstream rework.

Operational Impact of Virtual Assembly Simulation

Simulation-driven assembly process, engineering, and validation can offer several operational advantages for manufacturing organisations.

Reduced Physical Rework

By predicting and quantifying distortion early, engineers can reduce the number of physical iteration loops required during try-out phases. This reduces tooling modification costs and time, limits scrap generated during process tuning, contributing to a more stable ramp-up.

Faster Production Readiness

Early simulation enables engineering teams to converge on robust assembly strategies more quickly. By resolving potential distortion issues before tooling is finalised, manufacturers can reduce the risk of delays at start of production (SOP) and improve the transition from pre-production to serial manufacturing.

Data-Supported Engineering Decisions

Simulation also strengthens the decision-making process within engineering teams. Rather than relying solely on prior experience or intuition, engineers can use simulation results to evaluate how proposed fixture changes, clamp strategies, or weld sequence modifications influence distortion behavior.

This capability is particularly valuable during cross-functional reviews or management discussions. Instead of stating that a proposed countermeasure is expected to improve the situation, engineers can present quantitative simulation evidence showing the predicted impact on dimensional stability. By supporting recommendations with physics-based analysis, the approach increases confidence in technical decisions and reduces reliance on subjective judgment

Integration with the Digital Manufacturing Process Chain

Assembly simulation forms an important component of the broader digital manufacturing process chain. Modern development workflows increasingly integrate multiple simulation disciplines, including forming analysis, assembly simulation, and structural performance evaluation.

Within this ecosystem, assembly simulation links component manufacturing to final vehicle performance. By analysing how part deviations propagate through assembly processes, engineers can better ensure that final structures meet dimensional and structural requirements.

These digital workflows support broader industry goals, including improved manufacturing efficiency, reduced material waste, and more sustainable production practices ^[1].

Conclusion

Automotive Body-in-White manufacturing continues to grow more complex as vehicle architectures evolve and development timelines shorten. Traditional assembly validation methods, primarily based on physical try-outs, are increasingly insufficient for efficiently managing this complexity.

Virtual distortion engineering enables evaluation of assembly behavior earlier in the development process by simulating how part deviations, clamping strategies, and welding sequences interact. Through workflow-driven modelling, automated stamping geometry prediction, and physics-based analysis, simulation tools enable engineers to identify potential assembly issues before physical tooling is finalised.

By supporting this predictive approach to assembly validation, Keysight Assembly provides a specialised simulation environment for analysing automotive assembly processes. As digital manufacturing workflows continue to mature, such simulation-driven methods are likely to play an increasingly important role in enabling efficient, reliable, and sustainable vehicle production. 

To learn more, visit Assembly Simulation Software | Keysight or check out the webinar, Future of Automotive Assembly.

References

1. Keysight Technologies. (2024a). Virtual process chains: Building digital workflows for smarter joining and assembly in automotive BiW.
   https://www.keysight.com/blogs/en/tech/sim-des/virtual-process-chains-building-digital-workflows-for-smarter-joining-and-assembly-in-automotive-biw

2. Keysight Technologies. (2024b). Introducing the new Keysight assembly simulation software: Interview with the product manager.
   https://www.keysight.com/blogs/en/tech/sim-des/introducing-the-new-keysight-assembly-simulation-software-interview-with-the-product-manager

3. Keysight Technologies. (2024c). Keysight Assembly simulation software.
   https://www.keysight.com/cae/products/keysight-assembly