In-process stochastic tool wear identification and its application to the improved cutting force modeling of micro milling

Zhang, Xuewei; Yu, Tianbiao; Xu, Pengfei; Zhao, Ji

doi:10.1016/j.ymssp.2021.108233

Cited by 51 publications

(9 citation statements)

References 33 publications

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“…Because the contact area between the tool and the workpiece depends on the deflection angle between the tool and the workpiece, Utsumi et al [ 12 ] considered the effect of the milling tool position on the milling forces, and using point cloud techniques, developed a model of the milling forces considering the attitude of the tool. Zhang et al [ 13 ] puts forward a comprehensive evaluation method based on long short-term memory (LSTM) and particle filter (PF) algorithm to monitor the random wear of cutting tools in real time. A milling force model considering random tool wear, tool runout and actual tool movement is established.…”

Section: Introductionmentioning

confidence: 99%

Research on the Method of Reducing Dynamic Cutting Force in Aspheric Machining

2023

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With the rapid development of photoelectric communication and other fields, the demand for high-precision aspheric mirrors has been increasing. Predicting dynamic cutting forces is vital in selecting machining parameters and also affects the surface quality of the machined surface. This study comprehensively considers the effects of different cutting parameters and workpiece shape parameters on dynamic cutting force. The actual width of cut, depth of cut, and shear angle are modelled while considering the effects of vibration. A dynamic cutting-force model considering the aforementioned factors is then established. Using experimental results, the model accurately predicts the average value of dynamic cutting force under different parameters and the range of fluctuation of dynamic cutting force, with a controlled relative error of about 15%. The influence of workpiece shape and workpiece radial size on dynamic cutting force is also considered. The experimental results show that the greater the surface slope, the more dramatic the dynamic cutting force fluctuations. This lays the foundation for subsequent writing on vibration suppression interpolation algorithms. The influence of the radius of the tool tip on dynamic cutting forces leads to the conclusion that to achieve the goal of reducing the fluctuation of cutting forces, diamond tools with different parameters should be selected for different feed rates. Finally, a new interpolation-point planning algorithm is used to optimize the position of interpolation points in the machining process. This proves the reliability and practicability of the optimization algorithm. The results of this study are of great significance to the processing of high-reflectivity spherical/aspheric surfaces.

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Section: Introductionmentioning

confidence: 99%

Research on the Method of Reducing Dynamic Cutting Force in Aspheric Machining

2023

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“…Micro-milling vibration monitoring is a hot technology for enterprises to improve their equipment competitiveness and a frontier and difficult point in modern science and technology academic research [ 17 , 18 , 19 ]. Laser displacement sensors [ 9 , 13 , 14 , 20 ], microphones [ 21 ], capacitance sensors [ 22 ], acceleration sensors [ 23 ], and three-dimensional force sensors [ 24 , 25 , 26 , 27 ] are often used by researchers to obtain machining state signals or use multi-sensor information fusion based on the combining of some of these sensors to predict the tool vibration state [ 9 , 20 , 22 ]. However, there are some problems when the laser displacement sensor is used for the measurements of micro-milling vibration, such as when the spot is larger than the surface area of the tooltip and the sensor needs to be installed far away from the tool system [ 28 ].…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Displacement Measurement of Micro-Milling Tool Based on Fiber Array Encoding

Jia

Zhang

2023

Micromachines

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The vibration of the micro-milling tool presents a significant chaotic vibration phenomenon, which has a great influence on the tool life and part machining precision, and is one of the basic problems restricting the improvement of machining efficiency and machining accuracy in micro-milling. To overcome the difficulty of the traditional vibration measurement method with the online measurement of micro-milling tool multi-dimensional vibration, a three-dimensional (3D) measurement method of the micro-milling tool is proposed based on multi-fiber array coding, which converts the tool space motion into a decoding process of the optical coding array employing the tool modulating the multi-fiber array encoding. A 6 × 6 optical fiber array was designed, and a 3D motion platform for micro-milling tools was built to verify the characteristics of the optical fiber measurement system. The measurement results show that the measuring accuracy of the system reached 1 µm, and the maximum linear error in x-, y-, and z-direction are 1.5%, 2.58%, and 2.43%, respectively; the tool space motion position measurement results show that the maximum measurement error of the measuring system was 3.4%. The designed system has unique coding characteristics for the tool position in the space of 100 µm3. It provides a new idea and realization means for the online vibration measurement of micro-milling tools.

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“…By increasing tool life x3 (from 8 to 24 min), reducing the side cutting edge angle also contributed to the improvement in tool life. A study conducted by Zhang et al [16] discussed the use of in-process stochastic tool wear identification as a method for improving micro milling force modelling. To predict stochastic tool wear values, they proposed improving the integrated estimation technique based on the long short-term memory (LSTM) network and particle filter algorithm.…”

Section: Introductionmentioning

confidence: 99%

Parameter optimization of titanium-coated stainless steel inserts for turning operation

Muniyappan,

Nagarajan

2023

Int. J. Simul. Multidisci. Des. Optim.

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This study discusses the three essential process parameters cutting speed, feed and depth of cut on the quality of the tool during turning operation. A high-strength stainless steel tool coated with tungsten carbide is used. The tool is further strengthened using cryogenic treatment by immersing it in liquid nitrogen for 24 h and 36 h respectively. The surface roughness of the simple coated tool and the processed tool is compared using optimization techniques like the Taguchi technique and ANOVA. The analysis revealed that the surface roughness of the simple coated tool insert was 0.5 μm, whereas the surface roughness of the tool inserts immersed in liquid nitrogen for 36 h was 12.5 μm. The processed tool insert became brittle which lead to an increase in surface roughness after the turning operation. Three different algorithms like Grass Hopper Optimization, Moth Flame Optimization, and Salp Swarm Optimization were used to observe the feasibility of the optimization techniques. The Moth Flame Optimization algorithm had good convergence and also delivered results that were correlating with the ANOVA. It is concluded that while keeping a high tool rotation speed of 984.46 rpm, a low feed of 91.4 mm/min and a depth of cut of 0.25 mm resulted in a low surface roughness of simple coated tool insert was 0.59 μm.

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In-process stochastic tool wear identification and its application to the improved cutting force modeling of micro milling

Cited by 51 publications

References 33 publications

Research on the Method of Reducing Dynamic Cutting Force in Aspheric Machining

Research on the Method of Reducing Dynamic Cutting Force in Aspheric Machining

Three-Dimensional Displacement Measurement of Micro-Milling Tool Based on Fiber Array Encoding

Parameter optimization of titanium-coated stainless steel inserts for turning operation

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