A new systematic error identification and optimal sampling method for multi- axis CNC milling machine tools | |
| Author | Nguyen Van Chung |
| Call Number | AIT Diss. no.ISE-12-04 |
| Subject(s) | Milling-machines--Numerical control Machine-tools--Numerical control |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Engineering in Design and Manufacturing Engineering, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Dissertation ; no. ISE-12-03 |
| Abstract | Multi-axis machine tools are subjected to many different error sources. The error sources can be categorized as geometric erros or kine matic errors, errors derived from weight of the machine tool structure, errors due to thermally, and dynamic errors. The first three errors are the called quasi-static error. They are error sources in the relationship between the cutting tool and the workpiece, they changed slowly in time. They influence the accuracy of dimensions of the manufactured worpieces. Therefore, we need to improve the accuracy of multi-axis machine tools by trying to compensate or reduce these errors. A new artifact based approach to determine the systematic errors of multi-axis CNC machine tools minimizing the worst case prediction error is presented. The closed loop volumetric error is identified by simultaneously moving the axes of the machine tool. The physical artifact is manufactured on the machine tool and later measured on a Coordinate Measuring Machine. The artifact consists of a set of holes in the machine tool workspace at locations that minimize the worst case pred iction error for a give n bounded measurement error. The number of holes to be drilled depe nds on the degree of polynomials that are used to model the systematic error and the number of axes of the CNC machine tool. The prediction errors are also functions of the number and location of the holes. The physical artifact in the experiment contained multiple virtual artifacts. This allowed to separate the random errors from the systematic errors and assessing their relative magnitude. The procedure to measure component s of orientation vector of the artifact holes on a CMM is developed. The case studies are included to demonstrate the developed new method. The first case study focuses on identifying the angular error of X Z C CNC lath e to illustrate the theory. The procedure to measure i, j, k values of th e artifact holes on a CMM is developed. The systematic angular errors of this case study machine tool were modeled as three dimensional polynomials of degree 5 based on 142 optimal sampling points. The second case study shows the systematic error iden tification for a 2D milling machine. The feasibility of the method is investigated for a 2-axis machine to find the best experimental setting. Finally based on the 2-axis case study we extend the results to machine tools with any number of axes by identifying the systematic error for 3-axis and 5-axis CNC machine tool with the first degree polynomials. This dissertation contributes to the evaluation of the practical feasibility of a procedure for compensating systematic errors in CNC milling machine. The procedure is based on the idea to mill an artifact with the machine to be corrected and then to measure such artifact. The difference between nominal values of the artifact and measured ones allow to identifying the systematic errors |
| Year | 2011 |
| Corresponding Series Added Entry | Asian Institute of Technology. Dissertation ; no. ISE-12-04 |
| Type | Dissertation |
| School | School of Engineering and Technology (SET) |
| Department | Department of Industrial Systems Engineering (DISE) |
| Academic Program/FoS | Industrial Systems Engineering (ISE) |
| Chairperson(s) | Bohez, Erik L. J; |
| Examination Committee(s) | Manukid Parnichkun ;Phan Minh Dung ;Belforte, Gustavo ;Ho Thanh Phong; |
| Scholarship Donor(s) | Vietnam Government (MOET); |
| Degree | Thesis (Ph. D.) - Asian Institute of Technology, 2012 |