A Feature-Based Semantic Model for Automatic Product Cost Estimation

To address the requirement of dynamic pricing and cost control in high-variation product manufacturing, nowadays many companies face the problem of generating quotes and order prices timely, accurately and consistently. A generic semantic model for the purpose of automatic cost estimation is proposed, in which a new concept named cost feature, is suggested. A cost feature can be identified with data mining methods for different targeted clients or products, and conceptually interfaced with product design and manufacturing features. Feature-based mapping model is used to determine feature scope and cost level defined, including all the dependency relations with other domain features. This model is expected to enable a visual, flexible and semantically consistent scheme to address effective and efficient product cost structures, frequent configuration variations and business changes. A case study is used to illustrate this new method. The preliminary study shows that the proposed method is potentially effective for manufacturers.