Multi-scenario and multi-criteria approach to evaluate prediction techniques used to recognise failure patterns

Abstract

Predicting the next failure of a specific component in a machine results in higher performance of the equipment in terms of its reliability. This study examines the five most applicable prediction methods used to predict HVAC filter blockage. Considering different scenarios that use design of experiment (DOE), a multiple criteria decision making (MCDM) tool, known as TOPSIS, is utilised to compare the performance of each predictive technique according to their performance in various contexts. The results show that the performance of the system is improved when the best predictive method has been selected not only on the premises of a purely mathematical approach, but also when the solid mathematical prediction is supplemented by the judgments of experts and edited data. In addition, the empirical data is retrieved and a new method to evaluate the prediction techniques based on the applications of DOE and MCDM tools is illustrated.