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Build variation has long been recognized as one of the most important factors in vehicle performance. In this study an elastic assembly simulation program is used to guide a wheelhouse assembly process design to reduce build variation. Five (5) different clamping schemes are evaluated through the simulation program. From the five proposed process design choices, the best assembly process was identified, which results in reduced assembly variation and less tooling and manufacturing costs. Two different variation simulation approaches, one based on perturbation and the other based on Design of Experiments, were used to predict the assembly variation. Good agreement between the two approaches provided a validity check for the simulation tool.

In the automotive industry there is a continual drive to reduce cost and improve processing flexibility in the assembly plants. The competitive market place demands flexible and common processes to help reduce assembly costs and improve build quality. The selection of these common processes requires experience based knowledge to pick the best practice among a set of alternatives. This paper demonstrates how math based manufacturing analysis can be used to help in this selection process. Within General Motors, the BOP (Bill Of Process) represents a globally templated approach to manufacturing and assembling vehicles. All vehicle programs are required to follow the common BOP. Broadly defined, the BOP is a set of common processing standards relating to datum number and selection, number of stations required to build a sub assembly, etc.

Finite element methods can be used to simulate a class of variation problems induced by build distortion in the assembly process. The FEM approach was used to study two representative assembly problems: 1) Front fender mounting and resulting distortion due to various fastening sequences; and, 2) Coupe door assembly process and resulting deformation due to clamping and welding of flexible sheet metal parts. FEM is used to generate sensitivities of various process conditions. Correlation with measured Co-ordinate Measuring Machine (CMM) data is shown. The use of FEM to simulate manufacturing/assembly processes in the automotive industry is in it's infancy. As the new methods are developed this capability can be used to study the assembly process and provide guidance in designing more robust parts and assembly processes.