A Data-Driven Methodology for Forecasting Long-Term Mission Profiles of Household Appliances from Limited Usage Data

The derivation of mission profiles for household appliances is a critical step in the product development process, as accurate knowledge of consumer usage patterns enables engineers to prevent both under- and over-design. The increasing availability of connectivity in domestic appliances has created new opportunities to replace traditional assumptions, often based on surveys or expert judgment, using datadriven insights. However, understanding long-term usage behaviour remains challenging because available connectivity datasets typically cover periods much shorter than the target service life of the products. This paper presents a forecasting methodology for deriving long-term mission profiles from limited historical data, typically one year, considering univariate usage distribution. The proposed approach aims to overcome current data-length limitations and establish robust, scalable methods for predicting design-goal mission profiles in the context of connected household appliances.

Keywords: Reliability, Product Lifetimes, Prediction, Connectivity.