Assembly line balancing not only directly determines production efficiency but also influences precision and quality of key assemblies or even the overall performance of final products. Driven by market demand and development of science and technology, product family must evolve constantly, which necessitates frequent adjustment and rebalancing of product family assembly line (PFAL). In order to maintain production efficiency, improve assembly quality and precision, and reduce costs for adjustment, the evolution balancing problem of PFAL for small-sized wheel loader is solved in this paper. Firstly, the evolution balancing model of PFAL is put forward. Then, with minimizing the number of workstations, the in-station and between-station load indexes and adjustment costs, and maximizing relevancy between activities as optimization objectives, meanwhile regarding product platform planning, modularity design and the critical chain technology in concurrent engineering as constraint conditions, the evolution balancing problem of PFAL is optimized using improved genetic algorithm (IGA). Finally, the whole analysis procedure is demonstrated by the small-sized wheel loader PFAL case study and the effectiveness of the proposed method is verified.
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