Keywords
Cnc turning, cnc boring, cnc monitoring, design of experiments
Abstract
Manufacturing operations generate revenue by adding value to material through machine work and the cost associated with part production hinders the maximum profit available. In order to remain competitive, companies invest in research to maximize profit and reduce waste of manufacturing operations. This results in cheaper products for the customer without sacrificing quality. The purpose of this research was to identify machine settings of an Okuma LC 40 Turning Center and optimize the cost of machining in terms of tool cost and energy consumption while maintaining part quality at a productive cycle time. Studying the relationship between energy consumption, tool life, and cycle time with the speed and feed settings through statistical Analysis of Variance (ANOVA) method will allow the production plant to make profitable financial decisions concerning simultaneous turning operation of forged chrome-alloy steel. The project was divided into three phases; the first phase began with a literature survey of sensors used in current manufacturing research and the adaptation of our sensors to the Okuma LC 40 turning center. Then, phase II used design of experiments to identify spindle speed and feedrate settings that optimize multiple responses related to the turning process. The result was a saving in energy consumption (kWh) by 11.8%, a saving in cutting time by 13.2% for a total cost reduction from $1.15 per tool pass to $1.075 per tool pass. Furthermore, this work provides the foundation for phase III to develop an intelligent monitoring system to provide real-time information about the state of the machine and tool. For a monitoring system to be implemented in production, it should utilize cost effective sensors and be nonintrusive to the cutting operation
Notes
If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu
Graduation Date
2012
Semester
Spring
Advisor
Xu, Chengying
Degree
Master of Science in Mechanical Engineering (M.S.M.E.)
College
College of Engineering and Computer Science
Department
Mechanical and Aerospace Engineering
Degree Program
Mechanical Engineering; Mechanical Systems
Format
application/pdf
Identifier
CFE0004278
URL
http://purl.fcla.edu/fcla/etd/CFE0004278
Language
English
Release Date
May 2012
Length of Campus-only Access
None
Access Status
Masters Thesis (Open Access)
Subjects
Dissertations, Academic -- Engineering and Computer Science, Engineering and Computer Science -- Dissertations, Academic
STARS Citation
Hernandez, Manuel, "Process Optimization Towards The Development Of An Automated Cnc Monitoring System For A Simultaneous Turning And Boring Operation" (2012). Electronic Theses and Dissertations. 2134.
https://stars.library.ucf.edu/etd/2134