التفاصيل البيبلوغرافية
| العنوان: |
Cost-effective dynamic sampling in high dimensional online monitoring with advantage actor-critic. |
| المؤلفون: |
Li, Haoqian1 (AUTHOR), Chen, Yudong1 (AUTHOR), Liu, Kaibo1 (AUTHOR) kliu8@wisc.edu |
| المصدر: |
International Journal of Production Research. Jan2025, p1-20. 20p. 2 Illustrations. |
| مصطلحات موضوعية: |
*STATISTICAL process control, *ALGORITHMS, DEEP reinforcement learning, REINFORCEMENT learning, ACQUISITION of data |
| مستخلص: |
Industry 5.0 puts a spotlight on the team effort between people and machines, making the fast-paced development of IoT technology and sensor systems crucial. However, limitations such as the high cost of data acquisition, constrained bandwidth, and computational capacity can often hinder the real-time processing needed for human machine collaboration. To address this issue, we propose an integrated framework using Advantage Actor-Critic (A2C) and statistical process control (SPC) for economically monitoring high-dimensional data streams online. Our method leverages deep reinforcement learning with SPC charts to quickly identify system issues by smartly watching a few essential data streams. This approach not only saves resources but also boosts both the sustainability and efficiency of monitoring systems. Specifically, we construct a nonparametric monitoring statistic for each stream and develop a reinforcement learning framework to automatically identify the most informative and minimal number of data streams for observation at each time epoch. Our strategy is proven effective through simulations and a practical example in smart manufacturing, showcasing its superiority in reducing detection delay and minimising resources use compared to state-of-the-art algorithms. [ABSTRACT FROM AUTHOR] |
|
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Business Source Index |