Automatic modeling of machining processes
Author(s)
Sharma, Chetan,M. Eng.Massachusetts Institute of Technology.
Download1252628287-MIT.pdf (5.500Mb)
Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Neil Gershenfeld.
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Show full item recordAbstract
3 axis CNC milling is a ubiquitous manufacturing method in industry due to its versatility and precision. The fundamental parameters that dictate cutting performance ("speeds, feeds, and engagement") must be manually set by the machine programmer; proper operation therefore relies heavily on operator skill. In this thesis, an intelligent CNC controller is presented that uses low-cost sensors to fit an analytical model of cutting forces. The analytical nature of this model allows for favorable convergence characteristics and low computational costs. This is used to optimize cutting feeds with respect to process constraints for future movements; as more data is collected, the model continuously reinforced. This intelligent controller therefore abstracts out some of the complexities of machining and makes the process more approachable.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2021 Cataloged from the official PDF of thesis. Includes bibliographical references (pages 47-48).
Date issued
2021Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.