Recent Advances in Drilling Tool Temperature:A State‑of‑the‑Art Review

Drilling is regarded as the most complex manufacturing process compared with other conventional machining processes.During the drilling process,most of the energy consumed in metal cutting is converted to heat and increases temperature considerably.The resulting thermal phenomena are important since they influence the mode of deformation,the final metallurgical state of the machined surface,and the rate of tool wear.Hence,understanding the temperature characteristics in the drilling process is crucial for enhancing the drill performance and process efficiency.Extensive efforts have been conducted to measure and control the drilling tool temperature successively.However,very few studies have been conducted from a comprehensive perspective to review all the efforts.To address this gap in the literature,a rigorous review concerning the state-of-the-art results and advances in drilling tool temperature is presented in this paper by referring to the wide comparisons among literature analyses.The multiple aspects of drilling tool temperature are precisely detailed and discussed in terms of theoretical analysis and thermal modeling,methods for temperature measuring,the effect of cutting parameters,tool geometries and hole-making methods on temperature and temperature controlling by different cooling methods.In conclusion,several possible future research directions are discussed to offer potential insights for the drilling community and future researchers.

Cutting tool temperature prediction method using analytical model for end milling

Dramatic tool temperature variation in end milling can cause excessive tool wear and shorten its life, especially in machining of difficult-to-machine materials. In this study, a new analytical model-based method for the prediction of cutting tool temperature in end milling is presented.The cutting cycle is divided into temperature increase and decrease phases. For the temperature increase phase, a temperature prediction model considering real friction state between the chip and tool is proposed, and the heat flux and tool-chip contact length are then obtained through finite element simulation. In the temperature decrease phase, a temperature decrease model based on the one-dimension plate heat convection is proposed. A single wire thermocouple is employed to measure the tool temperature in the conducted milling experiments. Both of the theoretical and experimental results are obtained with cutting conditions of the cutting speed ranging from 60 m/min to100 m/min, feed per tooth from 0.12 mm/z to 0.20 mm/z, and the radial and axial depth of cut respectively being 4 mm and 0.5 mm. The comparison results show high agreement between the physical cutting experiments and the proposed cutting tool temperature prediction method.

The Fuzzy Cluster Analysis in Identification of Key Temperatures in Machine Tool

The thermal-induced error is a very important sour ce of machining errors of machine tools. To compensate the thermal-induced machin ing errors, a relationship model between the thermal field and deformations was needed. The relationship can be deduced by virtual of FEM (Finite Element Method ), ANN (Artificial Neural Network) or MRA (Multiple Regression Analysis). MR A is on the basis of a total understanding of the temperature distribution of th e machine tool. Although the more the temperatures measured are, the more accura te the MRA is, too more temperatures will hinder the analysis calculation. So it is necessary to identify the key temperatures of the machine tool. The selectio n of key temperatures decides the efficiency and precision of MRA. Because of th e complexities and multi-input and multi-output structure of the relationships , the exact quantitative portions as well as the unclear portions must be taken into consideration together to improve the identification of key temperatures. I n this paper, a fuzzy cluster analysis was used to select the key temperatures. The substance of identifying the key temperatures is to group all temperatures b y their relativity, and then to select a temperature from each group as the repr esentation. A fuzzy cluster analysis can uncover the relationships between t he thermal field and deformations more truly and thoroughly. A fuzzy cluster ana lysis is the cluster analysis based on fuzzy sets. Given U={u i|i=0,...,N}, in which u i is the temperature measured, a fuzzy matrix R can be obta ined. The transfer close package t(R) can be deduced from R. A fuzzy clu ster of U then conducts on the basis of t(R). Based on the fuzzy cluster analysis discussed above, this paper identified the k ey temperatures of a horizontal machining center. The number of the temperatures measured was reduced to 4 from 32, and then the multiple regression relationshi p models between the 4 temperatures and the thermal deformations of the spindle were drawn. The remnant errors between the regression models and measured deform ations reached a satisfying low level. At the same time, the decreasing of tempe rature variable number improved the efficiency of measure and analysis greatly.

Comparative study on local and global mechanical properties of bobbin tool and conventional friction stir welded 7085-T7452 aluminum thick plate

7085-T7452 plates with a thickness of 12 mm were welded by conventional single side and bobbin tool friction stir welding （SS-FSW and BB-FSW, respectively） at different welding parameters. The temperature distribution, microstructure evolution and mechanical properties of joints along the thickness direction were investigated, and digital image correlation （DIC） was utilized to evaluate quantitatively the deformation of different zones during tensile tests. The results indicated that heat-affected zone （HAZ）, the local softening region, was responsible for the early plastic deformation and also the fracture location for SS-FSW samples, while a rapid fracture was observed in weld nugget zone （WNZ） before yield behavior for all BB-FSW specimens. The ultimate tensile strength （UTS） of SS-FSW joints presented the highest value of 410 MPa, 82% of the base material, at a rotational speed of 300 rpm and welding speed of 60 mm/min, much higher than that of BB-FSW joints, with a joint efficiency of only 47%. This should be attributed to the Lazy S defect produced by a larger extent of heat input during the BB-FSW process, The whole joint exhibited a much higher elongation than the slices. Scanning electron microscopic （SEM） analysis of the fracture morphologies showed that joints failed through ductile fracture for SS-FSW and brittle fracture for BB-FSW.