QFD with statistical ranking – a hydropower turbine case studyRihar, Lidija (Avtor) Jenko, Marjan (Avtor) hydropower turbine maintenanceparameter probability densitypredictive analysisQFDQFD SRsensitivity analysisInfluences of hydropower plant water turbine operational parameters on turbine operational economics, reliability and lifetime are ranged with a new type of QFD method that includes parameter distribution densities and probabilities. In our method, each dominant i.e., main parameter coexists with associated side parameters. Their contribution to effects, usually attributed to the main parameter only, is modelled by a) probability density of the side parameter contribution to the main parameter effects, and by b) side parameters’ Bernoulli distribution since association of side parameter to the dominant parameter effects is in the realm of probability and not all side parameter effects are associated with the main parameter effects at all times. Analysis results are probability densities of dominant parameters influence measure on the turbine operating attributes. A simulation tool was built to establish relations amongst influential parameters and turbine’s economics, reliability and lifetime. We obtained technical data associated with turbine operation attributes from turbine senior designers having led successful projects within last 30 years. Simulation results have been validated with existing turbine-projects maintenance data.20242024-08-26 13:01:49Članek v reviji160338sl