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http://hdl.handle.net/10603/334539
Title: | Modeling optimisation of geometric errors and accuracy enhancement in three axis vertical machining centre |
Researcher: | Jamuna R |
Guide(s): | Natarajan U |
Keywords: | Engineering and Technology Engineering Engineering Mechanical axis vertical machining centre |
University: | Anna University |
Completed Date: | 2019 |
Abstract: | Precision is the soul of every industry. Modern technology aims at high quality, high accuracy at affordable cost. Engineers aim at achieving high target, high reliability of their product at lower manufacturing cost exhibiting higher precision. Even machine tools like Computer Numeric Control (CNC) machines and Coordinate Measuring Machines (CMM) have geometric errors due to various factors like misalignment of axis, wear and tear of movable parts etc Five axis CNC machines have greater flexibility, but three axis CNC machines have greater accuracy. Among the various errors, the three predominant errors affecting three axis CNC machines are straightness error, squareness error and backlash error. In modern day CNC machines, many companies like Siemens, Fanuc have developed controllers to compensate Backlash error. Errors in machine tools cannot be avoided but can be reduced. Error compensation algorithm has been implemented through controller. Sophisicated devices like Laser Interferometer, Laser Tracer and Laser Tracker are available in modern world and there is a need of low-cost compensation algorithm through controller. Backlash error has been computed from linear positioning error. Squareness error can be expressed as biaxial straightness. Linear positioning error has been measured by Laser Interferometer and readings have been analysed. Artificial Neural Network (ANN), and Mathematical models using polynomial function of second -order, third order,sinusoidal function and quadratic functions have been developed for linear positioning error, straightness error and backlash error Non-traditional optimisation techniques like Harmony Search Algorithm (HAS) and Teaching Learning Based Optimisation (TLBO) have been used iv to get better result of error compensation values. It was also observed that the accuracy enhancement is possible and error has been drastically reduced by using these nontraditional user friendly optimisation techniques. newline |
Pagination: | xxiii, 198p |
URI: | http://hdl.handle.net/10603/334539 |
Appears in Departments: | Faculty of Mechanical Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 25.42 kB | Adobe PDF | View/Open |
02_certificates.pdf | 73.69 kB | Adobe PDF | View/Open | |
03_vivaproceedings.pdf | 153.47 kB | Adobe PDF | View/Open | |
04_bonafidecertificate.pdf | 100.61 kB | Adobe PDF | View/Open | |
05_abstracts.pdf | 12.25 kB | Adobe PDF | View/Open | |
06_acknowledgements.pdf | 223.01 kB | Adobe PDF | View/Open | |
07_contents.pdf | 21.18 kB | Adobe PDF | View/Open | |
08_listoftables.pdf | 66.97 kB | Adobe PDF | View/Open | |
09_listoffigures.pdf | 52.43 kB | Adobe PDF | View/Open | |
10_listofabbreviations.pdf | 47.49 kB | Adobe PDF | View/Open | |
11_chapter1.pdf | 204.84 kB | Adobe PDF | View/Open | |
12_chapter2.pdf | 268.79 kB | Adobe PDF | View/Open | |
13_chapter3.pdf | 184.31 kB | Adobe PDF | View/Open | |
14_chapter4.pdf | 2.36 MB | Adobe PDF | View/Open | |
15_chapter5.pdf | 2.02 MB | Adobe PDF | View/Open | |
16_chapter6.pdf | 678.15 kB | Adobe PDF | View/Open | |
17_conclusion.pdf | 99.87 kB | Adobe PDF | View/Open | |
18_references.pdf | 184.77 kB | Adobe PDF | View/Open | |
19_listofpublications.pdf | 51.9 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 70.99 kB | Adobe PDF | View/Open |
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