Abstract
The injection molding industry is large and diversified. However there is no universally accepted way to bid molds, despite the fact that the mold and related design comprise 50% of the total cost of an injection-molded part over its lifetime. This is due to both the structure of the industry and technical difficulties in developing an automated and practical cost estimation system. The technical challenges include lack of a common data format for both parts and molds; the comprehensive consideration of the data about a wide variety of mold types, designs, complexities, number of cavities and other factors that directly affect cost; and the robustness of estimation due to variations of build time and cost. In this research, we propose a new mold cost estimation approach based upon clustered features of parts. Geometry similarity is used to estimate the complexity of a mold from a 2D image with one orthographic view of the injection-molded part. Wavelet descriptors of boundaries as well as other inherent shape properties such as size, number of boundaries, etc. are used to describe the complexity of the part. Regression models are then built to predict costs. In addition to mean estimates, prediction intervals are calculated to support risk management.
Notes
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Graduation Date
2009
Semester
Fall
Advisor
Wang, Yan
Degree
Doctor of Philosophy (Ph.D.)
College
College of Engineering and Computer Science
Department
Industrial Engineering and Management Systems
Format
application/pdf
Identifier
CFE0002866
URL
http://purl.fcla.edu/fcla/etd/CFE0002866
Language
English
Release Date
November 2014
Length of Campus-only Access
None
Access Status
Doctoral Dissertation (Open Access)
STARS Citation
Hillsman, Cyrus Clinton, "An Analogy Based Costing System For Injection Molds Based Upon Geometry Similarity With Wavelets" (2009). Electronic Theses and Dissertations. 6131.
https://stars.library.ucf.edu/etd/6131