Circuit Board Assembly Workshop Operational Risk Management and Assessment
- DOI
- 10.2991/978-94-6463-570-6_23How to use a DOI?
- Keywords
- Operational Risk Management; 5M1E; Fault Analysis (FTA); Dynamic Bayesian (DBN); Fuzzy Set Theory
- Abstract
The article presents a method for managing and evaluating operational risks in manufacturing production sites for circuit board assembly, addressing the uncertainties, diversities, and dynamic changes in influencing factors. This approach, employing Fuzzy Dynamic Bayesian Network (FDBN), establishes a risk assessment framework from five perspectives: personnel, machinery, materials, methods, and environment. It constructs a Fault Tree Analysis (FTA) model and maps the fault tree to a Dynamic Bayesian Network model (DBN). Node probabilities are quantified using fuzzy theory and expert scoring method. Through bidirectional inference of dynamic Bayesian reasoning, the method evaluates safety risks for on-site operation personnel in manufacturing production, deriving time-sequential dynamic curves of safety risk changes and reverse inferring key influencing factors. The research conclusions offer new insights for operational safety regulations.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Shichang Lu AU - Fenglian Xie PY - 2024 DA - 2024/11/22 TI - Circuit Board Assembly Workshop Operational Risk Management and Assessment BT - Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024) PB - Atlantis Press SP - 211 EP - 220 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-570-6_23 DO - 10.2991/978-94-6463-570-6_23 ID - Lu2024 ER -