Weibull Distributions Applied to Cost and Risk Analysis for Aero Engines
Paper in proceedings, 2008
This paper presents the use of Weibull formulation to the life analysis of different parts of the engine in order to estimate the cost of maintenance, the direct operating costs (DOC) and net present cost (NPC) of future type turbofan engines. The Weibull distribution is often used in the field of life data analysis due to its flexibility—it can mimic the behavior of other statistical distributions such as the normal and the exponential. The developed economic model is composed of three modules: a lifing module, an economic module and a risk module. The lifing module estimates the life of the high pressure turbine blades through the analysis of creep and fatigue over a full working cycle of the engine. The value of life calculated by the lifing is then taken as the baseline distribution to calculate the life of other important modules of the engine using the Weibull approach. Then the lower of the values of life of all the distributions is taken as time between overhaul (TBO), and used into the economic module calculations. The economic module uses the TBO together with the cost of labour and the cost of the engine (needed to determine the cost of spare parts) to estimate the cost of maintenance and DOC of the engine. In the present work five Weibull distributions are used for five important sources of interruption of the working life of the engine: Combustor, Life Limited Parts (LLP), High Pressure Compressor (HPC), General breakdowns and High Pressure Turbine (HPT). The risk analysis done in this work shows the impact of the breakdown of different parts of the engine on the NPC and DOC, the importance that each module of the engine has in its life, and how the application of the Weibull theory can help us in the risk assessment of future aero engines. A detailed explanation of the economic model is done in two other works (Pascovici et. al.  and Pascovici et. al. ), so in this paper only a general overview is done.