Using reliability analysis to support decision making in phased mission systems
Due to the environments in which they will operate, future autonomous systems must be capable of reconfiguring quickly and safely following faults or environmental changes. Past research has shown how, by considering autonomous systems to perform phased missions, reliability analysis can support dec...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017
|
| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/43001/ |
| _version_ | 1848796620352651264 |
|---|---|
| author | Zhang, Yang Prescott, Darren |
| author_facet | Zhang, Yang Prescott, Darren |
| author_sort | Zhang, Yang |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Due to the environments in which they will operate, future autonomous systems must be capable of reconfiguring quickly and safely following faults or environmental changes. Past research has shown how, by considering autonomous systems to perform phased missions, reliability analysis can support decision making by allowing comparison of the probability of success of different missions following reconfiguration. Binary Decision Diagrams (BDDs) offer fast, accurate reliability analysis that could contribute to real-time decision making. However, phased mission analysis using existing BDD models is too slow to contribute to the instant decisions needed in time-critical situations. This paper investigates two aspects of BDD models that affect analysis speed: variable ordering and quantification efficiency. Variable ordering affects BDD size, which directly affects analysis speed. Here, a new ordering scheme is proposed for use in the context of a decision making process. Variables are ordered before a mission and reordering is unnecessary no matter how the mission configuration changes. Three BDD models are proposed to address the efficiency and accuracy of existing models. The advantages of the developed ordering scheme and BDD models are demonstrated in the context of their application within a reliability analysis methodology used to support decision making in an Unmanned Aerial Vehicle. |
| first_indexed | 2025-11-14T19:50:53Z |
| format | Article |
| id | nottingham-43001 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T19:50:53Z |
| publishDate | 2017 |
| publisher | Wiley |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-430012018-07-02T09:13:07Z https://eprints.nottingham.ac.uk/43001/ Using reliability analysis to support decision making in phased mission systems Zhang, Yang Prescott, Darren Due to the environments in which they will operate, future autonomous systems must be capable of reconfiguring quickly and safely following faults or environmental changes. Past research has shown how, by considering autonomous systems to perform phased missions, reliability analysis can support decision making by allowing comparison of the probability of success of different missions following reconfiguration. Binary Decision Diagrams (BDDs) offer fast, accurate reliability analysis that could contribute to real-time decision making. However, phased mission analysis using existing BDD models is too slow to contribute to the instant decisions needed in time-critical situations. This paper investigates two aspects of BDD models that affect analysis speed: variable ordering and quantification efficiency. Variable ordering affects BDD size, which directly affects analysis speed. Here, a new ordering scheme is proposed for use in the context of a decision making process. Variables are ordered before a mission and reordering is unnecessary no matter how the mission configuration changes. Three BDD models are proposed to address the efficiency and accuracy of existing models. The advantages of the developed ordering scheme and BDD models are demonstrated in the context of their application within a reliability analysis methodology used to support decision making in an Unmanned Aerial Vehicle. Wiley 2017-11-28 Article PeerReviewed application/pdf en https://eprints.nottingham.ac.uk/43001/1/Using%20Reliability%20Analysis%20to%20Support%20Decision%20Making%20in%20Phased%20Mission%20Systems.pdf Zhang, Yang and Prescott, Darren (2017) Using reliability analysis to support decision making in phased mission systems. Quality and Reliability Engineering International, 33 (8). pp. 2105-2119. ISSN 1099-1638 Decision Support Reliability analysis Binary Decision Diagrams Variable ordering Phased mission http://onlinelibrary.wiley.com/doi/10.1002/qre.2170/full doi:10.1002/qre.2170 doi:10.1002/qre.2170 |
| spellingShingle | Decision Support Reliability analysis Binary Decision Diagrams Variable ordering Phased mission Zhang, Yang Prescott, Darren Using reliability analysis to support decision making in phased mission systems |
| title | Using reliability analysis to support decision making
in phased mission systems |
| title_full | Using reliability analysis to support decision making
in phased mission systems |
| title_fullStr | Using reliability analysis to support decision making
in phased mission systems |
| title_full_unstemmed | Using reliability analysis to support decision making
in phased mission systems |
| title_short | Using reliability analysis to support decision making
in phased mission systems |
| title_sort | using reliability analysis to support decision making
in phased mission systems |
| topic | Decision Support Reliability analysis Binary Decision Diagrams Variable ordering Phased mission |
| url | https://eprints.nottingham.ac.uk/43001/ https://eprints.nottingham.ac.uk/43001/ https://eprints.nottingham.ac.uk/43001/ |