• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.47-48
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• 2007

A CMP Process has many factors that affect result of a polished wafer. Dominant factors are velocity, pressure and temperature in process. A pad profile is also considered as affecting factor of CMP. Accoding to variation of a pad profile, the each pan of a wafer is differently pressured. It appears to affect the uniformity of a wafer. A pad profile varies as a swing arm conditioner which have been ordinarily used in industry. A swing arm conditioner has several sectors in its swing path. This study aims that a wafer get a good uniformity as swing arm conditioner's path on pad is analyzed and simulated. Through the simulation, tendency of pad profile after conditioning will be predicted and the result of simulation compared with the result of experiment. The optimized pad profile would be made by to vary swing arm's velocity on each sector. In order to maintain the optimized profile, conditioner design or swing arm's velocity should be changed and designed.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.21 no.11
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• pp.963-967
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• 2008

There are many factors to affect polishing performance normally in chemical mechanical polishing (CMP) process. One of the factors is a pad profile. A pad profile has not been considered as a significant factor. However, a pad profile is easily changed by conditioning process in CMP, and then changed pad profile affects polishing performance. Therefore, understanding how the pad profile is changed by conditioning process is very important. In this paper, through the simulation based on kinematic analysis, the variation of the pad profile was described in accordance with difference condition of conditioning process. A swing-arm type conditioner was applied in this simulation. A swing-arm type conditioner plays a role of generating asperities on pad surface. The conditions of conditioing process to get uniform removal were also investigated by comparing the simulation with the experiment.

• Tribology and Lubricants
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• v.40 no.2
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• pp.67-70
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• 2024

Chemical mechanical planarization (CMP) is an essential process for ensuring high integration when manufacturing semiconductor devices. CMP mainly requires the use of polyurethane-based polishing pads as an ultraprecise process to achieve mechanical material removal and the required chemical reactions. A diamond disk performs pad conditioning to remove processing residues on the pad surface and maintain sufficient surface roughness during CMP. However, the diamond grits attached to the disk cause uneven wear of the pad, leading to the poor uniformity of material removal during CMP. This study investigates the pad wear rate profile according to the swing motion of the conditioner during swing-arm-type CMP conditioning using deep learning. During conditioning, the motion of the swing arm is independently controlled in eight zones of the same pad radius. The experiment includes six swingmotion conditions to obtain actual data on the pad wear rate profile, and deep learning learns the pad wear rate profile obtained in the experiment. The absolute average error rate between the experimental values and learning results is 0.01%. This finding confirms that the experimental results can be well represented by learning. Pad wear rate profile prediction using the learning results reveals good agreement between the predicted and experimental values.