Practical Prognostics for Condition Based Maintenance

Prognostics Health Management (PHM) technology is being developed for a wide range of platforms to provide the maintenance support and logistics networks with a Condition Based Maintenance (CBM) capability. The impact of prognostics technology in the management of CBM, or Directed Logistics/Performance Based Logistics is not well understood and the CBM logistics systems development is not progressing at the same rate as the PHM technology that supports it. This paper reports some of the results of a three year European Union research program into the requirements for a system designed to implement Performance Based Logistics. There are two principal impacts of prognostics on the logistics network: a) Maintenance alleviation, because the PHM system can determine if maintenance intervention will be required resulting in leaner networks. b) Agile maintenance planning based on forecasted demand derived from the PHM system. This paper explores the relationship between PHM technology and maintenance support network design & management. It describes a unified approach to integrating these technologies to provide Maintenance Repair & Overhaul (MRO) organizations with a practical, streamlined approach to CBM systems development. Current maintenance planning systems are designed to meet the requirements of a scheduled maintenance program with sufficient additional free resource to deal with the demands of unscheduled maintenance. Prognostics based CBM requires that the maintenance planning process is sufficiently dynamic to match the maintenance that is demanded by the condition of the aircraft and eliminate the unnecessary maintenance inherent in the scheduled maintenance approach. This necessitates a more agile MRO network to deliver the parts and resources when and where in the network they are forecasted to be needed. Networks can only be made more agile if they are scaled correctly and this scaling has to allow for the maintenance activities to be lean to enable them to be profitable. Normally network, leaning requires the removal of free resources in the network whilst agility requires increasing free resource. This conflict is the lean-agile dilemma. This paper describes a prognostics tool set that can be utilized to resolve this lean-agile dilemma and provide the necessary network agility by using condition based forecasted demand to direct material through the network. The results of an impact study demonstrates how the dilemma has been resolved using the technology described in the paper.