relation: https://khub.utp.edu.my/scholars/20114/
title: Prescriptive Analytics for Dynamic Risk-Based Naval Vessel Maintenance Decision-Making
creator: Mohd Adha, M.E.
creator: Masdi, M.
creator: Hilmi, H.
description: Prescriptive analytics is a novel maintenance approach by recommending the maintainer, the right maintenance action at the right time through prioritization of maintenance based on the dynamic risk assessment. It assists in improving the existing preventive maintenance approach by offering a dynamic maintenance plan based on risk or risk-based maintenance scheduling. To date, there is no clear definition of risk-based maintenance as well as its framework, and its application has not been applied extensively in naval domain, which is peculiar due to its function-system relationship compared to the plant maintenance. This paper applies risk-based maintenance decision-making framework in naval domain using prescriptive analytics for optimal maintenance scheduling to improve asset availability and reduce maintenance costs while meeting stakeholders� expectations. Objectives and considerations in the case study are also defined for peculiarities application of naval vessels. The novel dynamic risk-based maintenance methodology also aims to improve the effectiveness of the current preventive maintenance practice and the inconsistency issue of the existing maintenance decision-making model using the expert judgment in reliability-centered maintenance. © Institute of Technology PETRONAS Sdn Bhd (Universiti Teknologi PETRONAS) 2024.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2024
type: Article
type: PeerReviewed
identifier:   Mohd Adha, M.E. and Masdi, M. and Hilmi, H.  (2024) Prescriptive Analytics for Dynamic Risk-Based Naval Vessel Maintenance Decision-Making.  Lecture Notes in Mechanical Engineering.  pp. 345-359.  ISSN 21954356     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188664675&doi=10.1007%2f978-981-99-5946-4_28&partnerID=40&md5=4f54661b10ed22600fb0d1a44f292d58
relation: 10.1007/978-981-99-5946-4₂₈
identifier: 10.1007/978-981-99-5946-4₂₈