Interval-Based Out-of-Order Event Processing in Intelligent Manufacturing

Estimating the cycle time of each job over event streams in intelligent manufacturing is critical. These streams include many long-lasting events which have certain durations. The temporal relationships among those interval-based events are often complex. Meanwhile, network latencies and machine failures in intelligent manufacturing may cause events to be out-of-order. This topic has rarely been discussed because most existing methods do not consider both interval-based and out-of-order events. In this work, we analyze the preliminaries of event temporal semantics. A tree-plan model of interval-based out-of-order events is proposed. A hybrid solution is correspondingly introduced. Extensive experimental studies demonstrate the efficiency of our approach.