| Author | Chana Raksiri |
| Call Number | AIT Diss. no.ISE-04-06 |
| Subject(s) | Milling-machines
Machinery, Kinematics of
|
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Engineering, School of Advanced Technologies |
| Publisher | Asian Institute of Technology |
| Series Statement | Dissertation ; no. ISE-04-06 |
| Abstract | High accuracy of CNC milling machines is required in many manufacturers
because the demand of precision components and consistency of quality are growing. They
are important in modern manufacturing system and their accuracy are one of the most
critical considerations. Geometric, cutting force and thermal induced errors are three main
major error causes which affect the accuracy of CNC milling machine. This dissertation
proposes a new off line error compensation model by taking into accounting of geometric,
cutting force and thermal induced errors in a 3-axis CNC milling machine. Geometric error
of a 3-axis milling machine composes of 21 components, which can be measured by laser
interferometer within the working volume. Geometric error estimation determined by
back-propagation neural network is proposed and used separately in the geometric error
compensation model. Likewise, cutting force and thermal induced error are estimated by
back-propagation neural network. Cutting force induced error determined based on a flat
end mill behavior observation is proposed and used separately in the cutting force induced
error compensation model. Various experiments over a wide range of cutting conditions
are done to investigate relation between cutting force and machine error. Thermal induced
error determined based on machine elements temperature observation is proposed and used
separately in the thermal induced error compensation model. There is a significant increase
in the thermal induced error along with an increase in machine elements temperature.
Various experiments over machine continuous operation are done to investigate relation of
machine elements temperature increasing and thermal induced error. Finally, the
combination of geometric, cutting force and thermal induced errors is modeled by the
combined back-propagation neural network. This unique model is used to compensate
geometric, cutting force and thermal induced errors simultaneously by a single model.
Experimental tests have been done in order to evaluate the performance of geometric,
cutting force and thermal induced errors compensation model. |
| Year | 2004 |
| Corresponding Series Added Entry | Asian Institute of Technology. Dissertation ; no. ISE-04-06 |
| Type | Dissertation |
| School | School of Advanced Technologies (SAT) |
| Department | Department of Industrial Systems Engineering (DISE) |
| Academic Program/FoS | Industrial Systems Engineering (ISE) |
| Chairperson(s) | Manukid Parnichkun; |
| Examination Committee(s) | Huynh Ngoc Phien;
Bohez, Erik L.J.;Furutani, Ryoshu; |
| Scholarship Donor(s) | Royal Thai Government Fellowship;Kasetsart University; |
| Degree | Thesis (Ph.D.) - Asian Institute of Technology, 2004 |
