TY  - GEN
N2  - Modern complex warships, amongst the most complicated machines ever built, must be both sustainable and safe to operate. Understanding overall complex warship asset risk requires holistic assessment of every factor which could add to availability or safe to operate risk, including logistical, personnel, engineering support and
performance data. Risk is presently evaluated through best human judgement, with many disparate data streams of available data analysed by multi-disciplinary teams; however, the volume of data generated is overwhelming. There is a need to provide an aggregate assessment of risk to pre-empt and prevent accumulated risks from becoming large issues. This is balanced against the challenge of information-overload; if every possible risk is flagged as a warning or a priority then this is also counterproductive. The emergence of the ability to integrate big data has provided opportunities to better predict and manage warship availability and the safe to operate envelope through the automation of data. This paper proposes a model for an availability and safe to operate risk tool which could be used to enhance understanding of the risk to sustaining readiness and maintaining a safe to operate
position. It proposes a method to analyse the sub-components of capability taking into account all supporting elements as well as criticality analysis to aid prioritisation. Key is to understand the thresholds at which a capability is lost. This paper proposes an expert system which will integrate available data sets to deliver a better understanding of complex warship availability and safety whilst also considering some of the challenges which will arise as higher fidelity of the overall picture is attainable.
DO  - 10.24868/10664
DO  - doi
AB  - Modern complex warships, amongst the most complicated machines ever built, must be both sustainable and safe to operate. Understanding overall complex warship asset risk requires holistic assessment of every factor which could add to availability or safe to operate risk, including logistical, personnel, engineering support and
performance data. Risk is presently evaluated through best human judgement, with many disparate data streams of available data analysed by multi-disciplinary teams; however, the volume of data generated is overwhelming. There is a need to provide an aggregate assessment of risk to pre-empt and prevent accumulated risks from becoming large issues. This is balanced against the challenge of information-overload; if every possible risk is flagged as a warning or a priority then this is also counterproductive. The emergence of the ability to integrate big data has provided opportunities to better predict and manage warship availability and the safe to operate envelope through the automation of data. This paper proposes a model for an availability and safe to operate risk tool which could be used to enhance understanding of the risk to sustaining readiness and maintaining a safe to operate
position. It proposes a method to analyse the sub-components of capability taking into account all supporting elements as well as criticality analysis to aid prioritisation. Key is to understand the thresholds at which a capability is lost. This paper proposes an expert system which will integrate available data sets to deliver a better understanding of complex warship availability and safety whilst also considering some of the challenges which will arise as higher fidelity of the overall picture is attainable.
AD  - Royal Navy
AD  - Royal Navy
T1  - Using Big Data to Understand Complex Warship Asset Risk
DA  - 2022-08-15
AU  - Thomas, W
AU  - Seagrave, S
L1  - https://library.imarest.org/record/10664/files/INEC_2022_paper_22.pdf
JF  - Conference Proceedings of INEC
VL  - INEC 2022
PY  - 2022-08-15
ID  - 10664
L4  - https://library.imarest.org/record/10664/files/INEC_2022_paper_22.pdf
KW  - Digitalisation
KW  - Big Data
KW  - Expert System
KW  - Risk
TI  - Using Big Data to Understand Complex Warship Asset Risk
Y1  - 2022-08-15
L2  - https://library.imarest.org/record/10664/files/INEC_2022_paper_22.pdf
LK  - https://www.imarest.org/events/category/categories/imarest-event/international-naval-engineering-conference-and-exhibition-2022
LK  - https://library.imarest.org/record/10664/files/INEC_2022_paper_22.pdf
UR  - https://www.imarest.org/events/category/categories/imarest-event/international-naval-engineering-conference-and-exhibition-2022
UR  - https://library.imarest.org/record/10664/files/INEC_2022_paper_22.pdf
ER  -