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Monte Carlo simulation of a reliability optimized maintenance concept for systems with limited accessibility

Keshkamat, Ashish and Hauschild, Jan and Meyer, Hendrik (2019) Monte Carlo simulation of a reliability optimized maintenance concept for systems with limited accessibility. In: Proceedings of the 29th European Safety and Reliability Conference. Research Publishing, Singapore. 29th European Safety and Reliability Conference - ESREL 2019, 22.-26. Sep. 2019, Hannover, Germany. doi: 10.3850/9819730000000. ISBN 981-973-0000-00-0.

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Official URL: http://itekcmsonline.com/rps2prod/esrel2019/e-proceedings/html/0120.xml


Artificial satellites, space stations and offshore wind turbines are examples of systems which have limited accessibility due to hostile environment and restricted transport capability. The availability of such systems becomes more critical when the maintenance is difficult to perform i.e. the system maintenance involves extraordinary costs or is inherently challenging. The aim of this paper is to propose an adequate model considering the complicated system design (modelled using Reliability Block Diagram tool developed in-house in Airbus Defence and Space), different maintenance strategies (preventive, corrective or combined) and limited accessibility of the system. The proposed model should be able to calculate availability (point availability and mean availability) and replacement rates. The operational capability or performance of a system can be increased by maintenance of the system's sub-units. This operational capability or performance of a system is described as the availability of a system. The availability, in general is used to express the probability of a system being in functional state at any point in time within a defined period. Calculations of availability are determined by the proportion of the so called uptime (describing the operational time) and the so called downtime (describing the non-operational time) of a system. The downtime is not only owed to failures, but includes the related time for maintenance and logistics required to restore the system back to the operational state. Monte Carlo simulation is chosen for the modelling due to its simplicity and flexibility. A Monte Carlo simulation model is applied to provide system availability and replacement rates. The outcome is expected to influence decisions related to the layout of the system, the design of sub-units (like parts quality, internal redundancies, mass, volume), maintenance strategy & sparing concepts and the mission planning (launch schedules).

Item URL in elib:https://elib.dlr.de/132860/
Document Type:Conference or Workshop Item (Speech)
Title:Monte Carlo simulation of a reliability optimized maintenance concept for systems with limited accessibility
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Keshkamat, AshishTU HamburgUNSPECIFIED
Hauschild, JanAirbus DSUNSPECIFIED
Meyer, HendrikHendrik.Meyer (at) dlr.deUNSPECIFIED
Date:September 2019
Journal or Publication Title:Proceedings of the 29th European Safety and Reliability Conference
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
DOI :10.3850/9819730000000
EditorsEmailEditor's ORCID iD
Publisher:Research Publishing, Singapore
Keywords:Maintenance, Availability, Replacements, Reliability Block Diagram, Systems, Monte Carlo Simulation, Optimization
Event Title:29th European Safety and Reliability Conference - ESREL 2019
Event Location:Hannover, Germany
Event Type:international Conference
Event Dates:22.-26. Sep. 2019
Organizer:Institute for Risk and Reliability
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:fixed-wing aircraft
DLR - Research area:Aeronautics
DLR - Program:L AR - Aircraft Research
DLR - Research theme (Project):L - Simulation and Validation (old)
Location: Hamburg
Institutes and Institutions:Institute of Maintenance, Repair and Overhaul > Process Optimisation and Digitalisation
Deposited By: Meyer, Hendrik
Deposited On:06 Jan 2020 08:06
Last Modified:06 Jan 2020 08:06

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