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

Anders Forslund (Institutionen för industri- och materialvetenskap) ; Samuel Lorin (Institutionen för produkt- och produktionsutveckling, Produktutveckling) ; Lars Lindkvist (Institutionen för industri- och materialvetenskap, Produktutveckling) ; Kristina Wärmefjord (Institutionen för industri- och materialvetenskap, Produktutveckling) ; Rikard Söderberg (Institutionen för industri- och materialvetenskap, Produktutveckling)
Proceedings of the ASME 2017 International Mechanical Engineering Congress and Exposition (2017)
[Konferensbidrag, refereegranskat]

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 in such a process, tolerances are introduced into the design. However, for certain assembly operations this method can yield suboptimal quality. For instance, 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. Since parts in welded assemblies are not easily disassembled and reused, interchangeability is not a relevant concern. This recognition means that each welded assembly can be adapted individually for the specific idiosyncrasies of ingoing parts. This paper focuses on two specific mass customization techniques; permutation genetic algorithms to assemble nominally identical parts, and virtual locator trimming. Based on these techniques, a six-step method is proposed, aimed at minimizing thing 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 one specific product; the turbine rear structure of a commercial turbofan engine. Using this simulation approach, the effects of using permutation genetic algorithms 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. This can be attributed to the orthogonality in fixturing. Seam variation is linked to weldability, which in turn has significant impact on estimated fatigue life. These results underscore the potential of virtual trimming and genetic algorithms in manufacturing, as a means both to reduce cost and increase functional quality.



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Denna post skapades 2017-12-21.
CPL Pubid: 254000