Fixture layout optimization in multi-station sheet metal assembly considering assembly sequence and datum scheme

Abstract

One of the most influential causes of dimensional inaccuracy in automotive bodies is the inescapable fixture deviation, which is propagated in a Multi-Station Assembly (MSA) process. Therefore, a robust fixture design is necessary to increase product quality. The aim of this paper is to present a methodology for simultaneous optimization of fixture layout and assembly configuration, including assembly sequence and datum shift scheme, in MSA. To model the accumulated variation from one station to the downstream stations, a non-linear state-space representation is adopted. Feasible assembly sequences are automatically generated using a liaison graph and Breadth-First Search algorithm, and also all datum scheme options are provided based on a permutation method that is dependent on the number of parts and stations. Further, the sum of squared standard deviations for key product characteristics to be minimized is an optimization object. Part boundaries, design requirements, and assembly configuration feasibility are the constraints. This constrained problem is converted into an unconstrained one by two strategies: (i) Geometry boundaries and assembly configuration constraints are fulfilled through removing infeasible solutions from the design space and (ii) Design requirements are met by using a self-adaptive penalty function. Finally, the unconstrained problem is optimized using a genetic algorithm. The proposed methodology improved assembly process capability by 68 to 84% for an automotive body side in a case study.