Rolls-Royce maintains a strong commitment to providing the highest quality gas turbine power system products in the marketplace today. However, given the global pressures to achieve a high level of quality at a low predictable cost of ownership under the new TotalCare(R), MissionCare(R) and CorporateCare(R) maintenance agreements, Rolls-Royce utilizes reliability improvement programs early in a products life cycle to grow the reliability to maturity in an effort to assure the maintenance agreement costs are set competitively. Maintaining a highly reliable product has not always been the number one priority of some gas turbine engine programs due to the nature of previously negotiated contracts which had different primary objectives in mind. As the legacy contracts slowly begin to phase out, it becomes increasingly important to assess the early reliability of the engine fleet by reviewing component condition data for each engine, collected during the time of each engine shop visit. Evaluating shop visit data to increase the products reliability is an extremely labor intensive and costly process. Until recently the benefits from a data collection effort were thought to be immeasurable. Therefore, allocating the correct type and scale of resources necessary to understand the root cause(s) behind any reliability shortfalls is paramount. Overall, reliability data collection efforts serve more than one purpose to the engine program. Therefore, an optimization tool was developed to assure the correct data collection strategy is adopted. The tool is known as the REliability Data Collection Optimization Tool or REDCOT. The ultimate goal of REDCOT is to correctly recommend to the user which of three different typical data collection strategies available offers the greatest life cycle cost benefit. It is important to note that the output from REDCOT does not provide the user with recommended system architecture, but instead simply aids in steering a programs data collection strategy. Applying REDCOT to define new data collection requirements helps assure resources are not allocated unnecessarily to collect shop visit records which are not needed to help improve product reliability. Case studies demonstrate a recommended range of data collection coverage during the fleets shop visits in order to assure the reliability can be improved by selecting the appropriate root cause to address.


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    Title :

    Engine fleet reliability data management optimization


    Contributors:


    Publication date :

    2011


    Size :

    6 Seiten, 2 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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