Browsing by Subject "In-service failures"
Now showing 1 - 1 of 1
Results Per Page
Sort Options
Item Open Access Bayesian in-service failure rate models(2022-08) Alankaya, TolunayPredicting the number of appliance failures during service after sales is crucial for manufacturers to detect production errors and plan spare part inventories. We provide a two-phased Bayesian model that predicts the number of refrigerators that fail after sales. Thus the study focuses on both sales forecasting and failure detection. The two-phased Bayesian model is trained by the datasets provided by a leading durable home appliances company. The accuracy results show that one-level models are inferior to multi-level models when the data are sparse. We conclude that hierarchical Bayesian models are preferable since they can naturally capture the heterogeneity across all blends of attributes.