In order to meet the requirements of grouping product families for advanced manufacturing modes such as mass customization

the features in BOM (Bill of Materials) are comprehensively analyzed

and a concept of BOM structure-based similarity metric model

a content-based similarity metric model

and an ensemble model combined with both are proposed.In the structure-based model

BOMs are represented by adjacent matrixes

including the relationships between materials and the quantity of materials

and the Orthogonal Procrustes Analysis is implemented to measure the similarity among BOMs.While in content-based model

effective text features are extracted from BOMs

being transformed to vectors by TFIDF(Term Frequency-Inverse Document Frequency)

and finally being inputted into cosine approximation formula for similarity value.To obtain more accuracy and performance

a weight distribution method based on the Gini coefficient is proposed for the ensemble model.Finally

a test framework is provided and all models are in evaluated experimentally in accuracy and performance.