Abstract
In this paper, we propose an agent-based system to detect abnormal process flow in semiconductor manufacturing process. A large-scale automation system like a semiconductor line is composed of multi-agents. Each agent carries out only a given role with autonomy. Therefore, even if an abnormality occurs, it might cause huge accident easily. For quality control, it is necessary to detect such anomalies promptly and take necessary measures, but the system complexity is so high that process managers are unable to detect abnormalities. In order to allow the administrator to quickly recognize the problem situation, we propose an agent that monitors process flow, and detects abnormal flow, and verify its validity using the data.
| Original language | English |
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| Title of host publication | ICCAS 2017 - 2017 17th International Conference on Control, Automation and Systems - Proceedings |
| Publisher | IEEE Computer Society |
| Pages | 2015-2020 |
| Number of pages | 6 |
| ISBN (Electronic) | 9788993215137 |
| DOIs | |
| Publication status | Published - 2017 Dec 13 |
| Event | 17th International Conference on Control, Automation and Systems, ICCAS 2017 - Jeju, Korea, Republic of Duration: 2017 Oct 18 → 2017 Oct 21 |
Publication series
| Name | International Conference on Control, Automation and Systems |
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| Volume | 2017-October |
| ISSN (Print) | 1598-7833 |
Other
| Other | 17th International Conference on Control, Automation and Systems, ICCAS 2017 |
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| Country/Territory | Korea, Republic of |
| City | Jeju |
| Period | 17/10/18 → 17/10/21 |
Bibliographical note
Publisher Copyright:© 2017 Institute of Control, Robotics and Systems - ICROS.
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Science Applications
- Control and Systems Engineering
- Electrical and Electronic Engineering