This paper presents an innovative diagnostic approach that includes detection and fault isolation using the Mahalanobis distance (MD). The fault isolation approach is based on the analysis of residual MD values corresponding to performance parameters. The residual value is calculated by taking the differences between MD values estimated in two different scenarios: first, when a performance parameter is present, and second, when that performance parameter is absent. The residual of MD values for each parameter is obtained by using training data under several experiments planned by design-of-experiment concept, to analyze impact of each parameter. The distribution of residual MD values for each parameter is analyzed and a 95% probabilistic range is established. This range represents the expected contribution by parameters towards healthy systems MDs, and it is used to identify parameters that are responsible for the anomalous behaviour of a system. Parameters that fall beyond the threshold limit are considered responsible for the anomalous behaviour, and the parameter that has lowest residual value is isolated as
the faulty parameter. A case study on notebook computers is presented to demonstrate and test the suggested new approach’s ability to isolate faulty parameters.

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