Availability classification for applications in construction production systems: A review

Mirkovic, Milan

doi:10.2298/fuace180318028m

Cited by 2 publications

(3 citation statements)

References 2 publications

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“…We used point availability performance indicators for the expected instantaneous availability of a system at a given time. System availability (

{E_{Avl}}

) is a function of MTBF and MTTR values and it represents the probability of the availability for both the system and operator at the time the system is needed for operation 67,68 …”

Section: Obsolescence Modelmentioning

confidence: 99%

“…Steady-state availability (Equation 19), also called asymptotic availability, is the limit of the availability function of the availability for both the system and operator at the time the system is needed for operation. 67,68 The reliability of a system (E Rlb ) is a function of MTBF and represents the probability that the system will perform over a required period of time under specific conditions 65,69,70 when needed.…”

Section: Efficiency Modelmentioning

confidence: 99%

“…Operational efficiency is a factor of system's availability, reliability, and maintainability. System availability (E Avl ) is a function of MTBF and MTTR values and represents the probability of availability for the system and operator at the time the system is needed for the operation 67,68.…”

mentioning

confidence: 99%

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Multi‐objective approach to forecast design refresh time due to COTS obsolescence

Özkan

Bulkan

2022

Systems Engineering

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The purpose of this study is to provide program managers and systems engineers with a novel algorithm in determining the design refresh time (DRT) of sustainmentdominated systems due to COTS obsolescence. Most of the research done so far has focused on cost optimization. The main contribution of the study is two-fold. First, besides cost optimization, we have introduced efficiency optimization within a balanced approach to determine the DRT, under multiple objectives. Second, we used a set-based approach over the hypervolume quality values of solutions rather than population-based Pareto solutions. We proposed a discrete-time simulation model by using Multi-Objective Evolutionary Algorithms where the deterioration over the quality values of Pareto solution sets is used as an indicator for a DRT. We supported the proposed mathematical model in theory with empirical findings from a case study for a sustainment-dominated Naval Command and Control System that was designed in 2004 and deployed in 2007. We ran the simulation as for 2007 and conducted an analysis over the cost and operational efficiency objectives to compare the situation experienced in real life against the simulation outputs of the proposed model. The results revealed that not only the total life cycle cost but also efficient operational sustainability of a system would be increased significantly if the system had gone through design refreshes as proposed by the model. We showed that the deterioration of the Pareto optimal solutions' hypervolume quality values over time is an effective marker to decide the optimal DRT under conflicting multiple objectives.

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“…We used point availability performance indicators for the expected instantaneous availability of a system at a given time. System availability (

{E_{Avl}}

) is a function of MTBF and MTTR values and it represents the probability of the availability for both the system and operator at the time the system is needed for operation 67,68 …”

Section: Obsolescence Modelmentioning

confidence: 99%