A small blind internal thread (SBIT) is used to firmly fasten some functional components to the cover of 3C electronic products. The small internal thread is made in a blind hole using a fluteless forming tap (FFT) that does not produce chips. However, the four geometric parameters (tool width (W), tooth root diameter (D2), front-end diameter (Df) and tooth angle (θ)) for the FFT affect the thread filling rate (f) and the minimum torque (T) for the tapping process. This study reports a Box-Behnken design (BBD) using DEFORM-3D (finite element model) and MINITAB (regression analysis) software to tap 7075-T6 aluminum alloy using a small FFT to achieve a repeatable thread filling rate and minimum torque. The experimental results show that the BBD accurately predicts and simulate the thread filling rate for tapping 7075-T6 aluminum alloy. The modelling software and the experimental design for this study can be used to optimize the design of tools that are used in industrial production.

A small blind internal thread (SBIT) is used to firmly fasten some functional components to the cover of 3C electronic products. The small internal thread is made in a blind hole using a fluteless forming tap (FFT) that does not produce chips. However, the four geometric parameters (tool width (W), tooth root diameter (D2), front-end diameter (Df) and tooth angle (θ)) for the FFT affect the thread filling rate (f) and the minimum torque (T) for the tapping process. This study reports a Box-Behnken design (BBD) using DEFORM-3D (finite element model) and MINITAB (regression analysis) software to tap 7075-T6 aluminum alloy using a small FFT to achieve a repeatable thread filling rate and minimum torque. The experimental results show that the BBD accurately predicts and simulate the thread filling rate for tapping 7075-T6 aluminum alloy. The modelling software and the experimental design for this study can be used to optimize the design of tools that are used in industrial production.

Tools with unequal fluteless spacing (UFS) feature are used to cut different materials. The UFS tool and a traditional tool differ in terms of the angle between the two cutting edges. The UFS tool experiences smaller axial and radial cutting forces than the traditional tool so cutting vibration is reduced, tool life is increased and the surface roughness of the workpiece increases. This study uses the smaller hole diameter (D), spindle speed (N) and cutting fluid concentration (C) for the central composite design (CCD). MINITAB statistical software is used for the second-order response surface modeling of the maximum thread filling rate (f) and the minimum torque (T) for micro-forming M1.2 mm taps using UFS on AL-7075 aluminum alloy. The analysis of variance (ANOVA) results for f and T show that D and C are the important parameters that affect f, and D, N and C significantly affect T. Compared with the predicted conditions, the errors in f and T for the experiment are 2.51% and 2.25%, respectively. This study shows that the two second-order mathematical models that are derived using CCD and the response surface method (RSM) feature good prediction accuracy.

Tools with unequal uteless spacing (UFS) feature are used to cut different materials. The UFS tool and a traditional tool differ in terms of the angle between the two cutting edges. The UFS tool experiences smaller axial and radial cutting forces than the traditional tool so cutting vibration is reduced, tool life is increased and the surface roughness of the workpiece increases. This study uses the smaller hole diameter (D), spindle speed (N) and cutting uid concentration (C) for the central composite design (CCD). MINITAB statistical software is used for the second-order response surface modeling of the maximum thread lling rate (f) and the minimum torque (T) for micro-forming M1.2 mm taps using UFS on AL-7075 aluminum alloy. The analysis of variance (ANOVA) results for f and T show that D and C are the important parameters that affect f , and D, N and C signi cantly affect T. Compared with the predicted conditions, the errors in f and T for the experiment are 2.51% and 2.25%, respectively. This study shows that the two second-order mathematical models that are derived using CCD and the response surface method (RSM) feature good prediction accuracy.