Knowledge-based model for constructing master assembly sequence

• A novel knowledge-based approach is introduced for assembly sequence planning.
• A MIP model is developed for generating a master (consensus) assembly sequence tree.
• The model is inspired by the concept of consensus trees found in Biology.
• Assembly sequences can be extracted for new variants within the scope of master tree.
• The model can generate assembly sequences for products with new groups of components.

A novel knowledge-based mixed-integer programming (MIP) model is presented for generating the assembly sequence of a given product based on available assembly sequence data of similar products. The proposed mathematical model finds the optimal consensus assembly sequence tree for an existing product family based on the assembly sequence trees of individual product family members. The proposed model is inspired by problems studied in biology and phylogenetics where a consensus species classification for a set of conflicting classifications is sought. The generated consensus tree serves as a master assembly sequence tree and is used to generate the assembly sequence for new product variants that falls within, or significantly overlaps with, the boundary of the considered family of products. The developed model is demonstrated using a family of pilot valves. The knowledge-based MIP model supports automatic assembly sequence generation, hence, reduces assembly planning effort and cost and improves productivity.