Many difficulties in metal machining arise from the precision required by the customer, as well as the exactness necessary for a successful cut to take place. This takes time, effort and money to adjust unique machine tool parameters by a trained professional. This thesis attempts to develop a method for analytically determining the causes for manufacturing process failure during the manufacturing process. It also applies control system theory to autonomously hone in on optimal parameters which would produce a desired end product. The thesis will present a MatLab® code format which could be used to optimize generic system parameters on any instantaneous system. It will be seen that utilizing these methods, it is possible to improve the quality of any final product.
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Details
Title
Machined product failure detection and technique for automation of instantaneous performance optimization
Creators
John D. Gunn - DU
Contributors
Bor-Chin Chang (Advisor) - Drexel University (1970-)
Awarding Institution
Drexel University
Degree Awarded
Master of Science (M.S.)
Publisher
Drexel University; Philadelphia, Pennsylvania
Resource Type
Thesis
Language
English
Academic Unit
College of Engineering (1970-2026); Mechanical Engineering (and Mechanics) [Historical]; Drexel University