Sponsor
Portland State University. Department of Mechanical and Materials Engineering
First Advisor
Sung Yi
Date of Publication
Winter 4-10-2018
Document Type
Thesis
Degree Name
Master of Science (M.S.) in Mechanical Engineering
Department
Mechanical and Materials Engineering
Subjects
Mathematical optimization, Milling-machines, Algorithms
DOI
10.15760/etd.6141
Physical Description
1 online resource (viii, 59 pages)
Abstract
Minimizing cost and optimization of nonlinear problems are important for industries in order to be competitive. The need of optimization strategies provides significant benefits for companies when providing quotes for products. Accurate and easily attained estimates allow for less waste, tighter tolerances, and better productivity. The Nelder-Mead Simplex method with exterior penalty functions was employed to solve optimum machining parameters. Two case studies were presented for optimizing cost and time for a multiple tools scenario. In this study, the optimum machining parameters for milling operations were investigated. Cutting speed and feed rate are considered as the most impactful design variables across each operation. Single tool process and scalable multiple tool milling operations were studied. Various optimization methods were discussed. The Nelder-Mead Simplex method showed to be simple and fast.
Persistent Identifier
http://archives.pdx.edu/ds/psu/24651
Recommended Citation
Resiga, Alin, "Design Optimization for a CNC Machine" (2018). Dissertations and Theses. Paper 4257.
https://doi.org/10.15760/etd.6141