A method for managing machine operation comprising: defining a network relationship structure having three bands, the first band comprising possible features which are each representative of an event occurring within the machine, or a component thereof, being monitored; the second band comprising possible symptoms and the third band comprising possible diagnoses, wherein the features are linked to symptoms and symptoms are linked to diagnoses; wherein the features and diagnoses are represented as nodes within said network structure and links are formed there-between to identify which features impact on which diagnoses; sensing a plurality of operational variables for a machine during use thereof so as to generate operational data for said variables; processing said operational data so as to determine features within the operational data indicative of a divergence from a desired operational state; determining a confidence value associated with said features to determine whether or not the feature has occurred; assessing whether a plurality of features and associated confidence value are indicative of a predetermined diagnosis for said machine, the assessing comprises determining one or more symptom confidence values from the plurality of feature confidence values and assessing whether the one or more symptom confidence values are indicative of a predetermined diagnosis; determining a confidence value for said diagnosis based upon the associated symptom confidence value; and outputting a signal indicative of an operational state of the machine if the diagnosis confidence value exceeds a threshold diagnosis confidence. defining a network relationship structure having three bands, the first band comprising possible features which are each representative of an event occurring within the machine, or a component thereof, being monitored; the second band comprising possible symptoms and the third band comprising possible diagnoses, wherein the features are linked to symptoms and symptoms are linked to diagnoses; wherein the features and diagnoses are represented as nodes within said network structure and links are formed there-between to identify which features impact on which diagnoses; sensing a plurality of operational variables for a machine during use thereof so as to generate operational data for said variables; processing said operational data so as to determine features within the operational data indicative of a divergence from a desired operational state; determining a confidence value associated with said features to determine whether or not the feature has occurred; assessing whether a plurality of features and associated confidence value are indicative of a predetermined diagnosis for said machine, the assessing comprises determining one or more symptom confidence values from the plurality of feature confidence values and assessing whether the one or more symptom confidence values are indicative of a predetermined diagnosis; determining a confidence value for said diagnosis based upon the associated symptom confidence value; and outputting a signal indicative of an operational state of the machine if the diagnosis confidence value exceeds a threshold diagnosis confidence.