System Phase In/Out

The Phase In and Phase Out are two crucial parts of the life cycle of a technical system. Phase In is obviously when the system shall be rolled out into operations, and Phase Out is when the system shall be retired, and replaced by a newer system.

The ramp up of the deploying fleet means that maintenance and support capability must be available to ensure the readiness of the system, but it must be made so that the costs are kept under control. The phase in and phase out are also two very dynamic steps in the life cycle of the system where deployment, usage and configurations might change quickly. There are large uncertainties in how prone to failures the systems are, and thereby also in the magnitude of their maintenance needs. In these phases it is important to be able to reflect the varying fleet sizes, deployments, and utilization of the systems to correctly calculate how, and when, maintenance capabilities should be increased or reduced and how this effects the optimal spares supply and assortment.  

The complexity of Phase In and Phase Out scenarios have made them difficult to analyze and optimize for cost effectiveness. Because of the complexity the effect has often been that too much maintenance capacity has been kept for too long, resulting in unnecessary costs, or that maintenance capability has been ramped up too slowly resulting in poor readiness. The slow and low quality analysis has also led to a situation where it has been difficult to respond to the typical fast changes in both Phase In and Out, and consequently put strains on the out of step maintenance organization. Using artificial intelligence algorithms, Systecon has solved this challenge to enable decision makers to understand risk and rewards in a fast and efficient way

Time phased optimization

Opus Suite incorporates the Phase In/Phase out capability into its core model. By effectively being able to address the dynamic nature of system fleets phasing in and out significant cost reductions can be achieved while maintaining a high operational readiness. In the Opus Suite you can build models that changes over time to reflect the changes in fleet size, deployment, and usage to get results which will be crucial to making the right decisions in terms of phase out schedules and maintenance policies. Always with the focus on cost and effectiveness.

In addition to the work we are doing directly in the Opus Suite we are also continuously expanding the capabilities and scope of the analysis. One aspect of this is to take an active part in academical research and we are proud to contribute to cutting edge research within the area of system Phase In/Out. The latest example can be seen in the form of new optimization methods developed in the Swedish NFFP06 program in close cooperation with academia and industry.

Download paper Phase-out maintenance optimization for an aircraft fleet