Abstract—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.
Index Terms—Cost estimation, semantic modeling, product pricing, associative feature, cost feature.
Y.-S. Ma and N. Sajadfar are with the University of Alberta, Edmonton, AB, Canada (e-mail: yongsheng.ma@ualberta.ca; sajadfar@ualberta.ca).
L. Campos Triana is with McCoy Drilling & Completions, Farr, Edmonton, AB, Canada (e-mail: LCampos@mccoyglobal.com ).
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Cite:Y.-S. Ma, N. Sajadfar, and L. Campos Triana, "A Feature-Based Semantic Model for Automatic Product Cost Estimation," International Journal of Engineering and Technology vol. 6, no. 2, pp. 109-113, 2014.
