Quick and Accurate Static Elimination

 In the manufacturing process of electronic devices, it is essential to prevent electrostatic discharge and electrostatic suction that lead to malfunction, destruction, and damage of the devices. Ionizer is a widely used static eliminator that neutralizes the voltage of charged substances (Figs. 1 and 2). However, it is often difficult to obtain a sufficient static elimination rate and residual-charge suppression because the control rules of the ionizer are often developed by the empirical rules of the manufacturer.
 We provide software that gives ionizers static-elimination-characteristic learning function. This function allows the ionizers to respond to changes in the amount of ions generated due to dust adhesion or deterioration to the discharge electrode, and changes in static elimination characteristics due to changes in the distance between the object and the electrode, ambient temperature/humidity, and material changes in the static elimination object.


Fig. 1 Ionizer

Ionizer Cercuit

Fig. 2 Cercuit in Ionizer

 Figure 3 shows the prediction result of the potential change of the static elimination target from artificial intelligence. At 0 seconds, the potential change predicted by artificial intelligence and the actual potential of the object are in good agreement.
 Figure 4 shows the control result of the ionizer utilizing this prediction. At 0.176 seconds, the artificial intelligence predicted that the potential of the static elimination object will be almost 0 at around 0.22 seconds, and the control mode was switched. After this switching, the object potential was quickly and accurately converged to 0. From this, we succeeded to reduce the static-elimination time by 63.2% - 70.7% under comparison with conventional methods.

Prediction Result

Fig. 3 Prediction of AI

Control Result

Fig. 4 Control Result of AI

[1] 金天海, 金田優希,久保勝也, 高橋克幸, 高木浩一(Iwate University), 山口晋一, 永田秀海(Shishido Electrostatic Ltd.):"人工知能に基づいた除電特性適応イオナイザ",静電気学会誌, Vol.45, No.1, (2021).