Innovative Structural Optimization and Dynamic Performance Enhancement of High-Precision Five-Axis Machine Tools
Abstract
:1. Introduction
2. Materials and Methods
2.1. Material
2.2. Physical Structure of 5-Axis Machine
2.3. Research Process
2.4. Finite Element Analysis
2.5. Static Stiffness Analysis
2.6. Modal Analysis
2.7. Harmonious Evaluation
- Z−1(s) is the inverse of the impedance matrix;
- F(s) is the applied force;
- H(s) is the transfer function of the system.
2.8. Cutting Transient Analysis
2.9. Cutting Spectrum Analysis
2.10. Effect of Moving Structure on Dynamic Structure Performance in Different Locations
Impact of Dynamic Structure on the Accuracy of the Static Structure
2.11. Force Flow Explore
2.12. Steady-State Thermal Analysis
3. Experimental Modal Testing
4. Results
4.1. Modal Comparison
4.2. Modal Assurance Criteria (MAC) Analysis [41]
Modal Assurance Criterion (MAC) Unity
- Incomplete measurement of modal vectors, with too few response stations included;
- Forced excitation from an unintended source, such as unbalanced rotating equipment;
- Modal vectors consist primarily of coherent noise, potentially reflecting random noise or bias;
- Modal vectors representing the same mode with different arbitrary scaling, differing only by a complex-valued scale factor when normalized.
4.3. Coordinate Modal Assurance Criterion (COMAC)
5. Conclusions
- (1)
- The machine’s weight was 15% less than in the original design model, the material it was exposed to was not strained, and the region of the structure where the force was considerably deformed was reinforced. All of these improvements may effectively increase the stiffness of the machine structure;
- (2)
- The static analysis was performed when 100 N of force was applied to the blade tip in the X-axis direction. The maximum deformation obtained was 28.7 µm. We also discussed a comparison of the dynamic machine structure trends when it is in different positions. The static stiffness analysis confirms that the designed five-axis machine tool meets the required rigidity standards for precise machining;
- (3)
- The outcomes of the modal trials were contrasted with the FEA findings. Based on a real modal analysis, the basic FEA parameters and material characteristics were confirmed. The differences in the modal testing findings between the first-order model analysis and the model testing were +6.6%, and for the second, third, and fourth orders the differences were +6.8%, +8.1%, +2.6%, respectively; all of these differences were within acceptable bounds. A high degree of correlation between the mode forms under comparison is indicated by a good MAC result;
- (4)
- The COMAC analysis provided valuable insights into the consistency and reliability of the modal vectors for the five-axis machine tool design. The high COMAC values across most DOFs confirm the robustness of the modal analysis, while the lower values at certain locations highlight areas for potential improvement. Overall, the COMAC results reinforce the validity of the structural dynamics assessment conducted in this research;
- (5)
- The optimization of the five-axis machine tool design successfully met the objectives of weight reduction, stiffness enhancement, and cost efficiency. Advanced optimization techniques and finite element analysis provided a robust framework for improving machine tool performance. These findings demonstrate the potential of optimization in advancing engineering design and achieving superior outcomes;
- (6)
- To comprehend the thermal behavior of a five-axis vertical milling machine, steady-state thermal analysis is essential. This research aids in the optimization of thermal management systems, assuring accurate and dependable operation by detecting temperature distributions and possible hot spots. In order to maximize thermal distortion reduction, achieve high precision in machining processes, and prolong machine life, it is imperative to maintain stable temperature conditions;
- (7)
- Future work could explore further refinements in enhancing the FE model, material selection, and structural configurations to achieve additional improvements.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Wang, Y.; Dong, W.; Zhang, S.; Tang, Z.; Wang, L.; Liu, Y. Design and development of a five-axis machine tool with high accuracy, stiffness and efficiency for aero-engine casing manufacturing. Chin. J. Aeronaut. 2022, 35, 485–496. [Google Scholar] [CrossRef]
- Khan, A.W.; Wuyi, C. Systematic geometric error modeling for workspace volumetric calibration of a 5-axis turbine blade grinding machine. Chin. J. Aeronaut. 2010, 23, 604–615. [Google Scholar] [CrossRef]
- Yang, B.; Zhang, G.; Ran, Y.; Yu, H. Kinematic modeling and machining precision analysis of multi-axis CNC machine tools based on screw theory. Mech. Mach. Theory 2019, 140, 538–552. [Google Scholar] [CrossRef]
- Ibaraki, S.; Oyama, C.; Otsubo, H. Construction of an error map of rotary axes on a five-axis machining center by static R-test. Int. J. Mach. Tools Manuf. 2011, 51, 190–200. [Google Scholar] [CrossRef]
- Liu, K.; Li, T.; Liu, H.; Liu, Y.; Wang, Y. Analysis and prediction for spindle thermal bending deformations of a vertical milling machine. IEEE Trans. Ind. Inform. 2019, 16, 1549–1558. [Google Scholar] [CrossRef]
- Liu, J.; Ma, C.; Wang, S. Data-driven thermal error compensation of linear x-axis of worm gear machines with error mechanism modeling. Mech. Mach. Theory 2020, 153, 104009. [Google Scholar] [CrossRef]
- Jin, L.; Yan, Z.; Xie, L.; Gou, W.; Tang, L. An experimental investigation of spindle rotary error on high-speed machining center. Int. J. Adv. Manuf. Technol. 2014, 70, 327–334. [Google Scholar] [CrossRef]
- Shi, S.; Lin, J.; Wang, X.; Zhao, M. A hybrid three-probe method for measuring the roundness error and the spindle error. Precis. Eng. 2016, 45, 403–413. [Google Scholar] [CrossRef]
- Wang, J.; Niu, W.; Ma, Y.; Xue, L.; Cun, H.; Nie, Y.; Zhang, D. A CAD/CAE-integrated structural design framework for machine tools. Int. J. Adv. Manuf. Technol. 2017, 91, 545–568. [Google Scholar] [CrossRef]
- Wang, L.; Wang, D.; Wang, B.; Li, W. Development of an oscillating grinding machine tool based on error analysis. Sci. China Technol. Sci. 2020, 63, 912–922. [Google Scholar] [CrossRef]
- Chan, T.-C.; Reddy, S.V.V.S.; Ullah, A.; Roy, B. Effect of spatial moving structure and topology optimization of the CNC turning machine tools. Int. J. Adv. Manuf. Technol. 2023, 129, 2969–2987. [Google Scholar] [CrossRef]
- Shen, L.; Ding, X.; Li, T.; Kong, X.; Dong, X. Structural dynamic design optimization and experimental verification of a machine tool. Int. J. Adv. Manuf. Technol. 2019, 104, 3773–3786. [Google Scholar] [CrossRef]
- Wu, J.; Yu, G.; Gao, Y.; Wang, L. Mechatronics modeling and vibration analysis of a 2-DOF parallel manipulator in a 5-DOF hybrid machine tool. Mech. Mach. Theory 2018, 121, 430–445. [Google Scholar] [CrossRef]
- Chan, T.-C.; Chang, C.-C.; Ullah, A.; Lin, H.-H. Study on kinematic structure performance and machining characteristics of 3-axis machining center. Appl. Sci. 2023, 13, 4742. [Google Scholar] [CrossRef]
- Gegg, B.C.; Suh, S.C.S.; Luo, A.C.J. Modeling and Theory of Intermittent Motions in a Machine Tool With a Friction Boundary. J. Manuf. Sci. Eng. 2010, 132, 041001. [Google Scholar] [CrossRef]
- Zhou, H.; Hu, P.; Tan, H.; Chen, J.; Liu, G. Modelling and compensation of thermal deformation for machine tool based on the real-time data of the CNC system. Procedia Manuf. 2018, 26, 1137–1146. [Google Scholar] [CrossRef]
- Soori, M.; Jough, F.K.G.; Dastres, R.; Arezoo, B. A Review in Capabilities and Challenges of 5-Axis CNC Milling Machine Tool Operations. Preprint 2024. [Google Scholar] [CrossRef]
- Chan, T.-C.; Hong, Y.-P.; Wang, Y.-C.; Wu, S.-H. Optimization design of the composite structure of linear motor machine tools. J. Mech. Eng. Autom. 2019, 9, 219–224. [Google Scholar] [CrossRef]
- Chan, T.-C.; Medarametla, S.V.; Behera, R. Analyzing positional accuracy and structural efficiency in additive manufacturing systems with moving elements. Results Eng. 2024, 23, 102344. [Google Scholar] [CrossRef]
- Chan, T.-C.; Hong, Y.-P.; Yu, J.-H. Effect of Moving Structure on the Spatial Accuracy and Compensation of the Coordinate Measuring Machine. Int. J. Precis. Eng. Manuf. 2021, 22, 1551–1561. [Google Scholar] [CrossRef]
- Revanasiddesh, B.; Taj, A.P.; Kumar, N.N.; Suresh, B. Extraction of modal parameters of CNC lathe bed using finite element and experimental method. Mater. Today Proc. 2020, 24, 398–405. [Google Scholar] [CrossRef]
- Lima, D.Z.; Dezan, D.J.; Gasparin, E.E.; Salviano, L.O.; Yanagihara, J.I.; Ferreira, W.G. Modal analysis and structural optimization of integrated bladed disks and centrifugal compressor impellers. Struct. Multidiscip. Optim. 2024, 67, 40. [Google Scholar] [CrossRef]
- Ramesha, C.; Abhijith, K.; Singh, A.; Raj, A.; Naik, C.S. Modal analysis and harmonic response analysis of a crankshaft. Int. J. Emerg. Technol. Adv. Eng. 2015, 5, 323–327. [Google Scholar] [CrossRef]
- Ghani, M.U.; Abukhshim, N.A.; Sheikh, M. An investigation of heat partition and tool wear in hard turning of H13 tool steel with CBN cutting tools. Int. J. Adv. Manuf. Technol. 2008, 39, 874–888. [Google Scholar] [CrossRef]
- Suresh, R.; Basavarajappa, S.; Samuel, G. Predictive modeling of cutting forces and tool wear in hard turning using response surface methodology. Procedia Eng. 2012, 38, 73–81. [Google Scholar] [CrossRef]
- Ulrika, L.; Henrik, W.; Artem, K. A methodology for strain-based fatigue damage prediction by combining finite element modelling with vibration measurements. Eng. Fail. Anal. 2021, 121, 105130. [Google Scholar] [CrossRef]
- Chan, T.-C.; Yang, J.-S. Optimized Design and Performance Study of High Speed Five-Axis Machine Tools. In Proceedings of the ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Virtual, 17–19 August 2020. [Google Scholar]
- Kim, S.; Kim, S.; Kim, T.; Choi, S.; Lee, T.H.; Park, J.S.; Jung, S.-H. Topology optimization of reactive material structures for penetrative projectiles. Def. Technol. 2022, 18, 1205–1218. [Google Scholar] [CrossRef]
- De Lacalle, L.L.; Lamikiz, A.; Salgado, M.; Herranz, S.; Rivero, A. Process planning for reliable high-speed machining of moulds. Int. J. Prod. Res. 2002, 40, 2789–2809. [Google Scholar] [CrossRef]
- Calleja, A.; Bo, P.; González, H.; Bartoň, M.; López de Lacalle, L.N. Highly accurate 5-axis flank CNC machining with conical tools. Int. J. Adv. Manuf. Technol. 2018, 97, 1605–1615. [Google Scholar] [CrossRef]
- González, H.; Calleja, A.; Pereira, O.; Ortega, N.; López de Lacalle, L.N.; Barton, M. Super Abrasive Machining of Integral Rotary Components Using Grinding Flank Tools. Metals 2018, 8, 24. [Google Scholar] [CrossRef]
- Bo, P.; González, H.; Calleja, A.; de Lacalle, L.N.L.; Bartoň, M. 5-axis double-flank CNC machining of spiral bevel gears via custom-shaped milling tools—Part I: Modeling and simulation. Precis. Eng. 2020, 62, 204–212. [Google Scholar] [CrossRef]
- Artetxe, E.; González, H.; Calleja, A.; Valdivielso, A.F.; Polvorosa, R.; Lamikiz, A.; Lacalle, L.N.L.D. Optimised methodology for aircraft engine IBRs five-axis machining process. Int. J. Mechatron. Manuf. Syst. 2016, 9, 385–401. [Google Scholar] [CrossRef]
- Möhring, H.-C.; Wiederkehr, P.; Erkorkmaz, K.; Kakinuma, Y. Self-optimizing machining systems. CIRP Ann. 2020, 69, 740–763. [Google Scholar] [CrossRef]
- Pálmai, Z.; Kundrák, J.; Felhő, C.; Makkai, T. Investigation of the transient change of the cutting force during the milling of C45 and X5CrNi18-10 steel taking into account the dynamics of the electro-mechanical measuring system. Int. J. Adv. Manuf. Technol. 2024, 133, 163–182. [Google Scholar] [CrossRef]
- Yu, Y.; Zhang, S.; Li, H.; Wang, X.; Tang, Y. Modal and Harmonic Response Analysis of Key Components of Ditch Device Based on ANSYS. Procedia Eng. 2017, 174, 956–964. [Google Scholar] [CrossRef]
- Zaghbani, I.; Songmene, V. Estimation of machine-tool dynamic parameters during machining operation through operational modal analysis. Int. J. Mach. Tools Manuf. 2009, 49, 947–957. [Google Scholar] [CrossRef]
- Wu, Z.; Xu, C.; Zhang, J.; Yu, D.; Feng, P. Modal and harmonic reponse analysis and evaluation of machine tools. In Proceedings of the 2010 International Conference on Digital Manufacturing & Automation, Changcha, China, 18–20 December 2010; pp. 929–933. [Google Scholar]
- Chan, T.-C.; Wu, S.-C.; Ullah, A.; Farooq, U.; Wang, I.H.; Chang, S.-L. Integrating numerical techniques and predictive diagnosis for precision enhancement in roller cam rotary table. Int. J. Adv. Manuf. Technol. 2024, 132, 3427–3445. [Google Scholar] [CrossRef]
- Carré, M.; Haake, S. An examination of the Clegg impact hammer test with regard to the playing performance of synthetic sports surfaces. Sports Eng. 2004, 7, 121–129. [Google Scholar] [CrossRef]
- Allemang, R.J. The modal assurance criterion–twenty years of use and abuse. Sound Vib. 2003, 37, 14–23. [Google Scholar]
- Fuentes, H.P.; Zehn, M. Application of the Craig-Bampton model order reduction method to a composite structure: MACco, COMAC, COMAC-S and eCOMAC. Open Eng. 2016, 6, 185–198. [Google Scholar] [CrossRef]
Gray Cast Iron | |
---|---|
Density (kg/m3) | 7200 |
Young’s modulus (Pa) | 1.24 × 1011 |
Poisson’s ratio | 0.3 |
Hardness, Rockwell C | 20 |
S40C medium carbon steel | |
Density (kg/m3) | 7850 |
Young’s modulus (Pa) | 2 × 1011 |
Poisson’s ratio | 0.28 |
Hardness, Rockwell C | 30 |
Tungsten carbide | |
Density (kg/m3) | 15,000 |
Young’s modulus (Pa) | 5.5 × 1011 |
Poisson’s ratio | 0.28 |
Hardness, Rockwell C | 70 |
Content | Modal Analysis | Feature |
---|---|---|
Mode shape 1 | Arbor supports machine vibrations | |
Frequency | 97.5 Hz | +6.6% |
Mode shape 2 | The F=findings of the vibrations from the column. | |
Frequency | 110.4 Hz | +6.8% |
Mode shape 3 | The primary movement mechanism for the base section along the Z-axis. | |
Frequency | 115.6 Hz | +8.1% |
Mode shape 4 | The fourth modal structure’s primary distortion mode is the machine bed distortion along the Z-axis. | |
Frequency | 129.6 Hz | +2.6% |
Sl. No. | Component Structure | Relatively Maximum Deformation (μm) |
---|---|---|
1 | Rotating seat (C)to Tool holder | 26.98 |
2 | Tool holder to Spindle seat | 16.31 |
3 | Spindle seat to Upright (Z) | 3.85 |
4 | Upright (Z) to Rail table | 4.17 |
5 | Rail table to Base | 2.5 |
6 | Base to Rotating seat (B) | 0.16 |
7 | Rotating seat (B) to Rotating seat (C) | 0.01 |
8 | Overall | 33.23 |
Axis | Sensitivity |
---|---|
X | 103.9 mV/g |
Y | 104.0 mV/g |
Z | 104.6 mV/g |
Dynamic range | ±50 g |
Range of working temperature | −20.671.1 °C |
Force range | 0–4448 N |
Nominal sensitivity | 0.2 mv/N |
Measuring strength range | 0~22.41 N pk |
Measuring force peak range | 26.689 N pK |
Resonance frequency | 20 kHz |
Rated current | 4~20 |
Impact hammer weight | 1.5 Kg |
Handle material | Fiberglass with rubber grip |
Head diameter | 5.1 cm |
Overall length | 35.6 cm |
Content | Modal Analysis | Modal Testing | Feature |
---|---|---|---|
Mode shape 1 | Arbor supports and spindle head vibrations. | ||
Frequency | 97.5 Hz | 104 Hz | +6.6% |
Mode shape 2 | Vibrations from the column. | ||
Frequency | 110.4 Hz | 118 Hz | +6.8% |
Mode shape 3 | Base section along the Z-axis. | ||
Frequency | 115.6 Hz | 125 Hz | +8.1% |
Mode shape 4 | Distortion of the machine saddle along the Z-axis. | ||
Frequency | 129.6 Hz | 133 Hz | +2.6% |
Shape Table 1 | ||||||
---|---|---|---|---|---|---|
Mode Shape | Frequency (or Time) FEA | Frequency (or Time) EMA | MAC Values | |||
Shape 1 | 25.3 Hz | 22.5 Hz | 1 | 0.636 | 0.0942 | 0.0666 |
Shape 2 | 35.3 Hz | 31.3 Hz | 0.636 | 1 | 0.142 | 0.0444 |
Shape 3 | 45.5 Hz | 49.4 Hz | 0.0942 | 0.142 | 1 | 0.151 |
Shape 4 | 80.4 Hz | 78.1 Hz | 0.0666 | 0.0444 | 0.151 | 1 |
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Behera, R.; Chan, T.-C.; Yang, J.-S. Innovative Structural Optimization and Dynamic Performance Enhancement of High-Precision Five-Axis Machine Tools. J. Manuf. Mater. Process. 2024, 8, 181. https://doi.org/10.3390/jmmp8040181
Behera R, Chan T-C, Yang J-S. Innovative Structural Optimization and Dynamic Performance Enhancement of High-Precision Five-Axis Machine Tools. Journal of Manufacturing and Materials Processing. 2024; 8(4):181. https://doi.org/10.3390/jmmp8040181
Chicago/Turabian StyleBehera, Ratnakar, Tzu-Chi Chan, and Jyun-Sian Yang. 2024. "Innovative Structural Optimization and Dynamic Performance Enhancement of High-Precision Five-Axis Machine Tools" Journal of Manufacturing and Materials Processing 8, no. 4: 181. https://doi.org/10.3390/jmmp8040181