Experimental analysis and modelling of bond formation in ultrasonic heavy wire bonding

Conference: CIPS 2020 - 11th International Conference on Integrated Power Electronics Systems
03/24/2020 - 03/26/2020 at Berlin, Deutschland

Proceedings: ETG-Fb. 161: CIPS 2020

Pages: 6Language: englishTyp: PDF

Schemmel, Reinhard; Scheidemann, Claus; Hemsel, Tobias; Sextro, Walter (Paderborn University, Chair of Dynamics and Mechatronics, Germany)
Kirsch, Olaf (Infineon Technologies AG, Warstein Germany)

Ultrasonic wire bonding is a process to form electrical connections in electronics well established industry. Typically, a clamping tool is pressed on the wire and forced to vibrate at relative high frequency 40 to 100 kHz. The ultrasonic vibration is transmitted through the wire into the interface between wire and substrate. Due to frictional processes, contamination like oxide layers are removed from the contact zone, the surface roughness is reduced, and with increasing bond duration an metallic connection of wire and substrate is established. It is known that the amount of ultrasonic energy over time directly influences the strength and reliability of the bond connection, but the determination of optimum bond parameters is still a challenging experimental task. For this, in the past different model approaches have been presented, to calculate the bond quality by simulation. Measuring the friction between wire and substrate to validate these models is a challenging task at ultrasonic bonding frequency. Therefore a versatile test rig for bonding experiments at frequencies lower than 1 kHz is setup to get detailed insight into the different phases of the connection process. It includes a piezoelectric force sensor for the measurement of the three-dimensional process forces, an electrodynamic shaker for the vibration excitation and a conventional tension-compression testing machine to apply the bond normal force. Using this test rig, it is possible to observe the different phases of bond formation in detail, validate and enhance existing models and finally optimize bond parameters for different processes.