Using Morphing Techniques in Early Variation Analysis
Journal article, 2014

Today, in order to be competitive in a fierce global car market, higher demands are placed on the Perceived Quality (PQ) of the products. The end customer's visual impression of fit and finish are one of several factors influencing the overall PQ. When assessing the PQ of split-lines, the assumed geometric variation of the ingoing parts is an important prerequisite for trustworthy visualization and for correct judgments. To facilitate early decision making in conceptual phases, new demands are set on virtual tools and methods to support the engineers. In this study, a method for early evaluation of the impact of geometrical variation on PQ of split-lines is proposed. Starting from an exterior styling model, mesh morphing techniques have been used to distort the exterior model according to measurement data acquired in running production. Morphing techniques have also been used to adopt previous structural design solutions onto the new styling, in order to make an early assumption of the assembly stiffness. The used method is described and adopted in an industrial case. The study shows that the presented technique can be used to create continuous and correlated datasets. Non-rigid part behavior can be included in early PQ evaluations, even if final CAD/FEA engineering design models do not yet exist.

Non-Rigid

Perceived Quality

Assembly Simulation.

Sheet Metal

Geometry Assurance

Author

Ola S Wagersten

Chalmers, Product and Production Development, Product Development

Björn Lindau

Chalmers, Product and Production Development, Product Development

Lars Lindkvist

Chalmers, Product and Production Development, Product Development

Rikard Söderberg

Chalmers, Product and Production Development, Product Development

Journal of Computing and Information Science in Engineering

1530-9827 (ISSN)

Vol. 14 1 Art. no. 011007- 011007

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Other Mechanical Engineering

Areas of Advance

Production

DOI

10.1115/1.4025719

More information

Latest update

4/5/2022 6