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Abstract
With the demand for increased availability and a higher level of safety, the defence industry is faced with reducing operational and maintenance budgets. Additional focus on acquisition programmes is being placed on through-life requirements, with demonstration and assurances sought early in the life cycle that these requirements can be achieved. Generic approaches to availability, cost and safety modelling are being re-examined, with a push to provide a universal view across both the submarine life-cycle and the support enterprise.
The role of a support solution is to ensure continuous understanding of the platform material state, thereby maintaining operational readiness, and to do so in a safe and cost effective manner. Despite the fact that the mission only represents a portion of the life of a platform, traditional availability studies have tended to focus on the performance in this state, thus neglecting the impact that standby and maintenance periods may have. This paper looks beyond the inherent design characteristics of a platform and towards the other enterprise factors that may affect availability, with a view to modelling and quantifying the impact these influences may have on overall platform availability.
A collaborative approach is described, with data being drawn from a number of organisations at various maturity levels and integrated into a cohesive, class level model. Targets are derived and reports produced that enable interrogation of driving factors down to a low level of granularity across multiple areas, including material failure modes, training provision, facilities, infrastructure and technical publications.
Modelling and simulation has been used in order to forecast the ability of a product to meet availability, safety and cost requirements when operated in a defined usage and upkeep cycle. These predictions, performed as early in the design phase as possible, enable the macro effects of small design changes to be assessed and feedback given into design teams. As the design phase progresses, outputs are used to optimise decisions made in the support solution design against constraints in the platform design – with the ultimate aim of maximizing capability whilst working within greater financial constraints. The development of this process and model is intended to provide increased confidence that an available, safe and affordable platform will be delivered.
The role of a support solution is to ensure continuous understanding of the platform material state, thereby maintaining operational readiness, and to do so in a safe and cost effective manner. Despite the fact that the mission only represents a portion of the life of a platform, traditional availability studies have tended to focus on the performance in this state, thus neglecting the impact that standby and maintenance periods may have. This paper looks beyond the inherent design characteristics of a platform and towards the other enterprise factors that may affect availability, with a view to modelling and quantifying the impact these influences may have on overall platform availability.
A collaborative approach is described, with data being drawn from a number of organisations at various maturity levels and integrated into a cohesive, class level model. Targets are derived and reports produced that enable interrogation of driving factors down to a low level of granularity across multiple areas, including material failure modes, training provision, facilities, infrastructure and technical publications.
Modelling and simulation has been used in order to forecast the ability of a product to meet availability, safety and cost requirements when operated in a defined usage and upkeep cycle. These predictions, performed as early in the design phase as possible, enable the macro effects of small design changes to be assessed and feedback given into design teams. As the design phase progresses, outputs are used to optimise decisions made in the support solution design against constraints in the platform design – with the ultimate aim of maximizing capability whilst working within greater financial constraints. The development of this process and model is intended to provide increased confidence that an available, safe and affordable platform will be delivered.