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Weld Sequence Optimisation for a Fuel Rail

A genetic algorithm coupled to a finite element model was used to optimise the weld sequence for a fuel rail assembly in order to minimise distortion.  Reducing distortion offers significant benefits including fewer process steps, improved part quality and less potential for scrap.


The Innovate UK project ‘Optipress’, led by Unipart Powertrain Applications partnered with TWI and Coventry University, aims to innovate the design of fuel rails by connecting design tools for finite element analysis, distortion prediction and fatigue design, to maximise the potential for autonomous design optimisation.

The fuel rail manufactured by Unipart is a pressure reservoir that feeds fuel injectors from a high pressure fuel pump.  It works in a very demanding environment and the dimensional accuracy of the assembly must be tightly controlled to ensure integrity.  The fuel rail is assembled by tack-welding components together on a jig and then brazing to add strength.  The tack welding introduces residual strains and stress which cause distortion.  Although this can be reduced by applying the welds in a different sequence, the interaction is complex and identifying an “optimal” sequence is not intuitive.


To identify weld sequences which would minimise the distortion in the manufactured fuel rail.

Figure 1a. Finite element model (FEM) distortion predictions for alternative weld sequences
Figure 1a. Finite element model (FEM) distortion predictions for alternative weld sequences
Figure 1b. Finite element model (FEM) distortion predictions for alternative weld sequences
Figure 1b. Finite element model (FEM) distortion predictions for alternative weld sequences


A finite element model was developed, using weld techniques established within TWI, which simulates each of the 22 tack welds in sequence and predicts the resulting distortion.  Figure 1 shows the typical distortion of the weld assembly that can arise due to different tack weld sequences.

The number of possible weld sequences – 22 factorial or approximately 1021 – is far too large to enable analysis of each one.  TWI’s solution therefore was to develop a genetic algorithm (GA) which generates a set of sequences (a ‘generation’), identifies the most successful and uses them to initiate the next generation.

A computer programme was developed which uses the GA to drive the inputs to the FEM and feedback the results.  In this way, progressively better sequences are identified and analysed.

The graph in Figure 2 summarises the predicted distortion for almost 3000 simulations (49 generations of the GA).  The prediction for the current process is shown as a dashed line.

The results show that there are a small number of weld sequences which cause comparatively large distortions.  However the GA routine identifies a number of possible weld sequences that can improve and minimise the distortion compared to the existing manufacturing sequence.  As a result, current work is now being experimentally validated as part of the Optipress project.


The combination of the genetic algorithm and the finite element model enabled the interrogation of the set of possible weld sequences.  Since many sequences lead to less distortion than the current process, there is scope to select the weld sequence based on other parameters, for example to minimise cycle time, thereby gaining further process improvements.

This work was undertaken within the Optipress project which is funded by Innovate UK.

Figure 2. Predicted distortion for all sequences
Figure 2. Predicted distortion for all sequences
Avatar Michael Roy Principal Project Leader, Numerical Modelling and Optimisation

Michael provides finite element analysis and manufacturing process simulations to advise TWI Members on questions related to structural integrity, weld distortion control and thermal management. Before joining TWI, he worked in the ship structures group at QinetiQ, and subsequently in the oil and gas industry where he performed nonlinear structural, thermal and dynamic analysis and design assessment of subsea equipment. Michael is a member of the panel IIW Commission X on fatigue modelling and residual stress, and he holds an MEng in Mechanical Engineering from the University of Strathclyde and a PhD in fatigue crack modelling from Heriot-Watt University.