Deep reinforcement learning-based orders splitting method for the wire bonding process in semiconductor chip packaging and testing workshops

Tianxin Gu; Lihui Wu

doi:10.1117/12.3038362

5 August 2024 Deep reinforcement learning-based orders splitting method for the wire bonding process in semiconductor chip packaging and testing workshops

Tianxin Gu, Lihui Wu

Author Affiliations +

Proceedings Volume 13226, Third International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2024); 1322652 (2024) https://doi.org/10.1117/12.3038362
Event: 3rd International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2024), 2024, Changsha, China

Abstract

The wire bonding process is a significant production bottleneck in the semiconductor chip packaging and testing workshops, which has the characteristics of large-scale multi-type production orders and parallel machine. Production order splitting is critical for improving the scheduling performance of the wire bonding process. This paper proposes a wire bonding process order splitting method using deep reinforcement learning (DQN), aiming to split production orders into optimized sub-batches. Firstly, factors such as order types, quantities, processing times, and machine capacities are adopted to construct the DQN’s state space. Then, an innovative sub-batch order temporary storage location is designed to build the action space. Finally, a reward function considering the makespan is built to guide DQN’s decision-making. Experimental results show that the proposed order splitting method is superior to traditional order splitting methods in terms of the complete time. Therefore, the proposed method is effective.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Tianxin Gu and Lihui Wu "Deep reinforcement learning-based orders splitting method for the wire bonding process in semiconductor chip packaging and testing workshops", Proc. SPIE 13226, Third International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2024), 1322652 (5 August 2024); https://doi.org/10.1117/12.3038362

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KEYWORDS

Wafer bonding

Packaging

Semiconductors

Data storage

Design

Education and training

Semiconducting wafers

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