Abstract: Techniques for performing asset health assessment in industrial networks are described. In an example, a plurality of data streams is received, where the plurality of data streams includes a plurality of data packets associated with an asset within an industrial facility, where the plurality of data packets includes a plurality of variables indicative of operating parameters of the asset. The plurality of data streams is then processed for obtaining a first batch of pre-processed data packets corresponding to each of the plurality of data streams. The first batch of pre-processed data packets includes a first set of values of a first variable from the plurality of variables. The first batch of pre-processed data packets are then merged to obtain a second batch of data packets. Thereafter, data packets within the second batch of data packets are sorted to obtain a serialized ordered list of values.

Abstract: Techniques for determining an anomaly in operation of an asset are described. In operation, operation of an asset within an industrial facility is monitored to identify a silence period for the asset, where the silence period is indicative of a time duration when the asset exhibits no network activity. The silence period is then determined to be longer than a reference silence period, where the reference silence period is utilized for determining an anomaly in the operation of the asset. Based on the determination, an alarm indicative of the anomaly in the operation of the asset is generated.