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A semi-automatic mold cost estimation framework based upon geometry similarity

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Abstract

The automation of cost estimation for manufacturing processes is a challenging task in computer-aided manufacturing. In this paper, we introduce a two-step analogy and mathematical approach to estimate the cost of injection molding. In the analogy step, data of molds are partitioned into homogeneous groups based on mold type and mold design. In the prediction step, regression models based upon geometry, topology, and other inherent shape properties are constructed within each group. The variables in the regression models within each group are extracted automatically from one orthographic two-dimensional (2D) image of the injection-molded part. Mean and variance estimates are calculated on a subset of relevant molds so that the risk of an inaccurate bid can be assessed on a subset of relevant molds.

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Authors and Affiliations

  1. Veterans Administration Center for Applied Systems Engineering, 2669 Cold Spring Road, Indianapolis, IN, 46222, USA

    Cyrus Hillsman

  2. George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Yan Wang

  3. H. Milton Stewart School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Dima Nazzal

Authors
  1. Cyrus Hillsman
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  2. Yan Wang
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  3. Dima Nazzal
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Correspondence to Cyrus Hillsman.

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Hillsman, C., Wang, Y. & Nazzal, D. A semi-automatic mold cost estimation framework based upon geometry similarity. Int J Adv Manuf Technol 68, 1387–1399 (2013). https://doi.org/10.1007/s00170-013-4929-6

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  • DOI: https://doi.org/10.1007/s00170-013-4929-6

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