Semantic Scholar Open Access 2019 272 sitasi

Smart Manufacturing Scheduling With Edge Computing Using Multiclass Deep Q Network

Chun-Cheng Lin Der-Jiunn Deng Yen-Ling Chih Hsin Chiu

Abstrak

Manufacturing is involved with complex job shop scheduling problems (JSP). In smart factories, edge computing supports computing resources at the edge of production in a distributed way to reduce response time of making production decisions. However, most works on JSP did not consider edge computing. Therefore, this paper proposes a smart manufacturing factory framework based on edge computing, and further investigates the JSP under such a framework. With recent success of some AI applications, the deep Q network (DQN), which combines deep learning and reinforcement learning, has showed its great computing power to solve complex problems. Therefore, we adjust the DQN with an edge computing framework to solve the JSP. Different from the classical DQN with only one decision, this paper extends the DQN to address the decisions of multiple edge devices. Simulation results show that the proposed method performs better than the other methods using only one dispatching rule.

Topik & Kata Kunci

Computer Science

Penulis (4)

Chun-Cheng Lin

Der-Jiunn Deng

Yen-Ling Chih

Hsin Chiu

Format Sitasi

APA MLA BibTeX

Lin, C., Deng, D., Chih, Y., Chiu, H. (2019). Smart Manufacturing Scheduling With Edge Computing Using Multiclass Deep Q Network. https://doi.org/10.1109/TII.2019.2908210

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Informasi Jurnal

Tahun Terbit: 2019
Bahasa: en
Total Sitasi: 272×
Sumber Database: Semantic Scholar
DOI: 10.1109/TII.2019.2908210
Akses: Open Access ✓