Titanium alloys are used in various industries due to their superior mechanical strength and corrosion resistance. However, titanium is classified as a difficult-to-machine material due to its low thermal conductivity that consequently causes poor tool life. In this study, cryogenic+MQL milling was performed to improve the machinability of Ti-6Al-4V; a cryogenic coolant and a minimum quantity fluid were sprayed simultaneously. The machinability was analyzed according to the cooling and lubrication conditions, focusing on the cutting force and tool wear. When the minimum quantity fluid was injected using two nozzles during cryogenic machining, the cutting force remained low despite the increase in machining distance due to the effective lubrication. The average cutting force at the long machining distances (82-86 passes) was 14.8% lower than that under the wet condition. The tool wear progressed without chipping, and the flank wear length was 55.5% lower than that of the wet machining because the cryogenic cooling and minimum quantity lubrication reduced the tool temperature, friction, and thermal shock.
Citations
Citations to this article as recorded by
Design and Development of a Real-Time AI-Based Tool Failure Prediction System for Machining Difficult-to-Cut Materials Mi-Ru Kim, Hoon-Hee Lee, Min-Suk Park, Wang-Ho Yun Journal of the Korean Society of Manufacturing Technology Engineers.2025; 34(4): 225. CrossRef
With the advent of the 4th industrial revolution, advanced digital manufacturing technologies are actively developed to strengthen manufacturing competitiveness. Smart factories require a real-time digital twin including a Cyber-Physical System (CPS) of machines and processes and intelligent technologies based on the CPS. To predict machining quality and optimize machines and processes, it is necessary to analyze the cutting force during machining. Therefore, for real-time digital twin, a fast cutting force simulation model that receives information such as the positions of the feed axes in short time intervals from the CNC and calculates the cutting force until the next information is input is required. This paper proposes a voxel-based fast cutting force simulation in NC milling for real-time digital twin. The proposed simulation model quickly calculates the cutting force by using only information of voxel elements removed by each tool edge without complicated Cutter-Workpiece Engagement (CWE) and chip thickness calculations in previous studies. To verify the performance of the developed simulation, experimental machining was performed and the measured cutting force and simulated cutting force were compared. It was demonstrated that the proposed model can successfully predict the cutting force 3.5 times faster than the actual process.
Citations
Citations to this article as recorded by
Autonomous Mobile Machining and Inspection System Technology for Large-Scale Structures Seung-Kook Ro, Chang-Ju Kim, Dae-Hyun Kim, Sungcheul Lee, Byung-Sub Kim, Jeongnam Kim, Jeong Seok Oh, Gyungho Khim, Seungman Kim, Seongheum Han, Quoc Khanh Nguyen, Jongyoup Shim, Segon Heo International Journal of Precision Engineering and Manufacturing.2025; 26(9): 2345. CrossRef
In this study, a wire electrical discharge milling electrode was developed, and electric discharge machining characteristics were studied by using the electrode. The wire electrical discharge milling electrode is a form, in which the wire is conveyed by using a cylindrical rod with a hemispherical end as a guide, and it also rotates in one direction around the guide axis. If the wire electrical discharge milling electrode is used in electrical discharge machining (EDM), there is no need to consider electrode wear compensation. The EDM characteristics according to capacitance of the RC circuit and the rotational speed of the wire electrical discharge milling electrode were examined. The machining conditions were selected, and a hemispherical shape with good shape accuracy and fine surface finish was fabricated in two stages of roughing and finishing. By applying the wire electrical discharge milling electrode to the electric discharge milling process, straight and curved shapes were successfully machined.
Citations
Citations to this article as recorded by
Experimental study on the wire electrical discharge machining of PCD with different grain sizes Kechuang Zhang, Laifa Zhu, Zhongwei Chen, Jianyun Shen, Xuefeng Zhao, Xian Wu Diamond and Related Materials.2025; 155: 112331. CrossRef
Compacted graphite iron (CGI) has been widely used in the automobile industry because of its good mechanical properties. CGI has better strength as compared to grey iron due to its internal structure. It includes graphite particles, which enhance the adhesion between graphite and iron. However, the material characteristics can negatively affect the machinability. In this study, cryogenic milling was performed for CGI450. It is well known that cryogenic machining is effective in improving the machinability. The process included spraying liquid nitrogen as a cryogenic coolant, and the influences on machinability were experimentally investigated with a focus on the cutting force and surface roughness. When liquid nitrogen was sprayed, the cutting force was slightly increased due to the cold-strengthening effect. On the other hand, surface roughness was dramatically decreased by 44.7% as compared to dry milling because brittleness of work material was increased by cryogenic coolant spraying.
Citations
Citations to this article as recorded by
Tool life assessment of high strength cast iron alloys in dry face milling operations Alcione dos Reis, Gustavo Henrique Nazareno Fernandes, José Aécio Gomes de Sousa, Luiz Leroy Thomé Vaughan, Feliciano Cangue, Álisson Rocha Machado, Wilson Luiz Guesser Journal of Manufacturing Processes.2024; 111: 180. CrossRef
Study on the Effect of MQL Spraying Condition on the Machinability in Titanium Cryogenic Machining Dong Min Kim, Heung Bum Park, Byung-Gook Kim, Hoon-Hee Lee, Young Ha Hwang, Ki Hyuk Kim, In Su Shin, Do Young Kim Journal of the Korean Society for Precision Engineering.2023; 40(4): 261. CrossRef
Tool condition monitoring is one of the key issues in mechanical machining for efficient manufacturing of the parts in several industries. In this study, a tool condition monitoring system for milling was developed using a tri-axial accelerometer, a data acquisition, and signal processing module, and an alexnet as deep learning. Milling experiments were conducted on an aluminum 6061 workpiece. A three-axis accelerometer was installed on a spindle to collect vibration signals in three directions during milling. The image using time-domain, CWT, STFT represented the change in tool wear of X, Y axis directions. Alexnet was modified to learn images of the two directional vibration signals, to predict the tool condition. From an analysis of the results of learning based on the experimental data, the performance of the monitoring system could be significantly improved by the suitable selection of the data image method.
Citations
Citations to this article as recorded by
Anomaly Detection Method in Railway Using Signal Processing and Deep Learning Jaeseok Shim, Jeongseo Koo, Yongwoon Park, Jaehoon Kim Applied Sciences.2022; 12(24): 12901. CrossRef
Comparative Analysis and Monitoring of Tool Wear in Carbon Fiber Reinforced Plastics Drilling Kyeong Bin Kim, Jang Hoon Seo, Tae-Gon Kim, Byung-Guk Jun, Young Hun Jeong Journal of the Korean Society for Precision Engineering.2020; 37(11): 813. CrossRef
When a workpiece contains complex burr edges from a combination of drilling and milling, conventional deburring tools such as wire brushes may not be effective in their removal. In this study, abrasive flow machining was used to gain access to complex burr edges. Experiments on two types of flow guides suggest that an abrupt change in direction of flow around the area with targeted burr edges is essential. The effects of several process parameters are investigated based on the experiments set up.
This paper discusses flow characteristics of nanofluid minimum quantity lubrication (MQL) in the milling process of a titanium alloy by usingnumerical analysis. A mist of nanofluids including nanodiamond and hexagonal boron nitride (hBN) particles is sprayed into a tool-workpiece interface with conditions varying by spray angle and flow rate. The milling. Are experimentally measured and minimized by the determined optimal spray angle and flow rate. The subsequent numerical analysis based on a computational fluid dynamics (CFD) approach is conducted to calculate the penetration ratios of the nanofluid droplets into a tool. At the experimentally obtained optimal spray angle and flow rate of the nanofluids’ mist, the calculated ratio of penetration is highest and, therefore, the optimal spray conditions of the nanofluids are numerically validated.
This paper presents a numerical study on the thermal characteristics of a milling process of titanium alloy with nanofluid minimum-quantity lubrication (MQL). The computational fluid dynamics (CFD) approach is introduced for establishing the numerical model for the nanofluid MQL milling process, and estimated temperatures for pure MQL and for nanofluid MQL using both hexagonal boron nitride (hBN) and nanodiamond particles are compared with the temperatures measured by thermocouples in the titanium alloy workpiece. The estimated workpiece temperatures are similar to experimental ones, and the model is validated.
We used a construction method using a CNC milling machine, where free-formed molds were made by cutting EPS (Expanded PolyStyrene) foam with the CNC machine, to build free-formed buildings. CNC milling is off-the-shelf technology that can easily cut EPS foam; however its production cost is too high and the time to manufacture an EPS mold is too long. This paper proposes a novel cutting machine with a fast and cost effective mechanism to manufacture EPS concrete molds. Our machine comprises a cutter and Cartesian coordinate type moving mechanism, where the cutter cuts EPS foam using a hotwire in the shape of ‘Π’ and is capable of adjusting its cutting angle in real-time while keeping its cutting width. We proved through cutting experiments on the CNC machine that cutting time was greatly shortened compared to the conventional method and that the resulting concrete mold satisfied manufacturing precision.
Citations
Citations to this article as recorded by
Development of Side Mold Control Equipment for Producing Free-Form Concrete Panels Jiyeong Yun, Kyeongtae Jeong, Jongyoung Youn, Donghoon Lee Buildings.2021; 11(4): 175. CrossRef
Manufacturing Automation System of Freeform Concrete Formwork Using S-LOM Method Joonhyeok Sim, Hakmin Kim, Kyunwoo Park, Chanwoo Kim, Daehie Hong Journal of the Korean Society for Precision Engineering.2020; 37(1): 43. CrossRef
First
Prev
