Structuralization of customer requirements by association rule mining and design structure matrix for configure-to-order products

Structural analysis of customer data such as purchase history and customer attributes is expected to be effective for designing the products that are appropriately adapted to requirements of individual customers. This paper proposes a structuralization method of customer requirements for configure-to-order products with the customer data analysis and the design structure matrix (DSM). In the method, association rule mining is applied to order reception data for extracting structural relationships among customer requirements. The extracted association rules are transformed into a customer requirements DSM, which can be used as the input to the clustering method for the multi-domain matrix across customer requirements, physical functions and entity structure. A case study of an industrial three-axis linear-type robot is demonstrated. The customer requirements DSM generated by the proposed method is compared with the one generated without using association rule mining. Its results show the effectiveness of the proposed method.