Research Papers

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

[+] Author and Article Information
Anders Forslund, Lars Lindkvist, Kristina Wärmefjord, Rikard Söderberg

Department of Industrial and Materials Science,
Chalmers University of Technology,
Gothenburg SE-41296, Sweden

Samuel Lorin

Fraunhofer Chalmers Centre,
Gothenburg SE-41296, Sweden

Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received December 21, 2017; final manuscript received May 24, 2018; published online August 6, 2018. Editor: Satyandra K. Gupta.

J. Comput. Inf. Sci. Eng 18(4), 041010 (Aug 06, 2018) (8 pages) Paper No: JCISE-17-1306; doi: 10.1115/1.4040952 History: Received December 21, 2017; Revised May 24, 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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Fig. 1

Self-compensating assembly line [9]

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Fig. 2

Turbine rear structure

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Fig. 3

3-2-1 locating scheme

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Fig. 4

Gap and flush between two parts

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Fig. 5

Double ellipsoid heat flux [19]

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Fig. 6

Welding simulation

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Fig. 7

Turbine rear structure (marked in red)

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Fig. 15

Color-coded before-and-after visualization

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Fig. 14

Seam variation with updated color coding

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Fig. 13

Seam variation after GA

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Fig. 12

3-2-1 locating scheme

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Fig. 11

Histogram over 300 random samples

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Fig. 9

A-B-C reference points

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Fig. 8

Color coding of standard deviation of part geometric variation

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Fig. 16

Configurations over generations

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Fig. 17

Seam variation after virtual locator trimming

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Fig. 18

Seam variation after virtual locator trimming with updated color coding



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