An intelligent approach to non-constant feed rate determination for high-performance 2D CNC milling

Chen, Zezhong C.; Miao, Zhibin

doi:10.1504/ijmtm.2006.010056

Cited by 8 publications

(5 citation statements)

References 4 publications

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“…As compared to most of the existing end milling control systems (Chen, 2006), the proposed adaptive system has the following advantages: 1. the computational complexity of UNKS does not increase much with the complexity of process; 2. the learning ability of UNKS is more powerful than that of conventional adaptive controller; 3. UNKS has a generalisation capability; 4. insensitive to changes in workpiece geometry, cutter geometry, and workpiece material; 5. cost-efficient and easy to implement; and 6. mathematically modeling-free.…”

Section: Resultsmentioning

confidence: 99%

Control Strategy of Constant Milling Force System and Metal Removal Rate Maximizion

Čuš

Balič

Župerl

2010

Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics

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An adaptive control system in conjunction with off-line optimization is built which controlling the cutting force and maintaining constant roughness of the surface being milled by digital adaptation of cutting parameters. In this way it compensates all disturbances during the cutting process: tool wear, nonhomogeneity of the workpiece material, vibrations, chatter etc. The basic adaptive control design is based on the control scheme (UNKS) consisting of two neural identificators of the process dynamics and primary neural regulator.

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Section: Resultsmentioning

confidence: 99%

Control Strategy of Constant Milling Force System and Metal Removal Rate Maximizion

Čuš

Balič

Župerl

2010

Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics

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“…16 Parameters used during simulation included values of F e = 80 N, F t = 400 N, a cutter rake angle of 0°, a p = 0.3 mm, b = 0.2 mm, a cutter rotating speed of S = 40 rpm, a cutter radius of r = 10 mm, and a cutter cutting speed v c = 2prS. 19 These parameters were entered into MATLAB to calculate l. When the cutterchip contact length (l) is input into MATLAB it is found that it is insensitive to the chip thickness (b) but is proportional to the cutting depth (a p ).…”

Section: Cutter-chip Contact Area Simulationmentioning

confidence: 99%

Design of surface micro texture in the cutter-chip contact area of a cemented carbide cutter

Tong

Zhang

Shen

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part B:

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Placing micro textures on a cutter surface can enhance the cutter-chip and cutter-workpiece contact, improving the cutter performance and machined surface quality. However, both the proper placement of micro textures and careful modeling of their density function are required for optimizing the cutting performance. In this study, a ball end milling cutter was utilized to demonstrate how these can be achieved. Initially, the theoretical cutter-chip contact length of the was calculated based on the chip curl theory and the theoretical cutter-chip contact area was obtained by combining the theories of cutter contact area and micro texture placement. Then, a mathematical model describing the micro texture distribution was established using a uniform density function, which allowed the determination of the specific distribution model for the micro textures. Finally, both simulations and experiments were used to validate the accuracy of the theoretical solution for the cutter-chip contact area and the uniformity of the micro texture density function. The results showed that the theoretical cutter-chip contact area and the uniform micro texture density mathematical model are consistent with the simulation and experimental results. The results reported in this paper provide a theoretical basis for the accurate preparation of micro textures.

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“…To improve part quality using optimal feed rates, the concept of surface roughness model is adopted in a method proposed by Baek,et al,([2]), which could plan the optimal feed rates. This method analyzes the effect of feed rate variation on surface roughness and dimension accuracy in a face milling operation, and the optimal feed rate, which provides the maximum material removal rate under the given surface roughness constraint, could be selected using a bisection method.…”

Section: Related Workmentioning

confidence: 99%

A fuzzy system approach of feed rate determination for CNC milling

Miao

2009

2009 4th IEEE Conference on Industrial Electronics and Applications

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Determinationof optimal machining parameters -spindle rate, feed rate, and depth of cut -has been a research topic for decades. Since the parameters of CNC machining significantly influence part machining time, part surface quality, and tool life, techniques of determining optimal machining parameters are in high demand in manufacturing industry. Usually the depth of cut and spindle rate are determined according to machinist manuals before machining; and the feed rate is determined subjectively either by CNC machine operators or programmers. As a result, the feed rate is not optimal in terms of the machining condition at every cutter location, and it is fixed at a conservative value causing longer machining time or shorter tool life. In this work, a generic and intelligent approach of feed rate determination for CNC profile milling is proposed. First a simplified cutting force model is introduced and an example database of machining parameters is presented. Second a fuzzy rule-based system is established to predict the cutting force based on the radial and axial depths of cut, and the assumed feed rate. Then identify the geometric features of the part, calculate the engagement angles of the geometric features, and find optimal feed rates for them. Finally apply this approach on an example part for profile milling, and the results are simulated with CATIA CAD/CAM system to demonstrate the advantages of this approach.

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An intelligent approach to non-constant feed rate determination for high-performance 2D CNC milling

Cited by 8 publications

References 4 publications

Control Strategy of Constant Milling Force System and Metal Removal Rate Maximizion

Control Strategy of Constant Milling Force System and Metal Removal Rate Maximizion

Design of surface micro texture in the cutter-chip contact area of a cemented carbide cutter

A fuzzy system approach of feed rate determination for CNC milling

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