Minimizing Weld Variation Effects Using Permutation Genetic Algorithms and Virtual Locator Trimming

A. Forslund, S. Lorin, L. Lindkvist, K. Wärmefjord, R. Söderberg. Journal of Computing and Information Science in Engineering 18 (4), 041010, 6 August, 2018.


The mass production paradigm strives for uniformity, and for assembly operations to be identical for each individual product. To accommodate geometric variation between individual parts, tolerances are introduced into the design. However, this method can yield suboptimal quality. In welded assemblies, geometric variation in ingoing parts can significantly impair quality. When parts misalign in interfaces, excessive clamping force must be applied, resulting in additional residual stresses in the welded assemblies. This problem may not always be cost-effective to address simply by tightening tolerances. Therefore, under new paradigm of mass customization, the manufacturing approach can be adapted on an individual level. This paper focuses on two specific mass customization techniques: permutation genetic algorithms (GA) and virtual locator trimming. Based on these techniques, a six-step method is proposed, aimed at minimizing the effects of geometric variation. The six steps are nominal reference point optimization, permutation GA configuration optimization, virtual locator trimming, clamping, welding simulation, and fatigue life evaluation. A case study is presented, which focuses on the selective assembly process of a turbine rear structure of a commercial turbofan engine, where 11 nominally identical parts are welded into a ring. Using this simulation approach, the effects of using permutation GAs and virtual locator trimming to reduce variation are evaluated. The results show that both methods significantly reduce seam variation. However, virtual locator trimming is far more effective in the test case presented, since it virtually eliminates seam variation. These results underscore the potential of virtual trimming and GAs in manufacturing, as a means both to reduce cost and increase functional quality.

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