DATA REPORTING OF TRACING EVENTS BY EVENT DRIVEN INCIDENCE MATRIX (International Journal of Engineering and Computer Science, 2014)
A platform for online Sensitivity Analysis (SA) that is applicable in large scale real-time data acquisition (DAQ) systems. Supervisory Control and Data Acquisition (SCADA) sensors and actuators connected to monitor the processes of manufacturing and its transmittable operations as a case study for resistant of concept. It deploys the Rank Order Clustering (ROC) method to automatically group all existing data sensors and actuators of the system to the Key Performance Indicators of the system. The sensors and actuators data collected shapes the input data for measuring the performance. The Event Cluster algorithm is located in inside the control centre of the SCADA system to assess the influence of each input to the overall key performance indicators of the process. This method progresses the quality of data analysis and reduces computation overhead on the control system.The flexibility to adapt can only be assured if data is succinctly interpreted and translated into corrective actions in a timely manner. Every single or combination of events could subsequently results in a change to the system state. The Proposed Event-Driven Incidence Matrix is designed based on sorting the rows for inputs and columns for key performance indicators (outputs). Incidence matrix elements can take a value of 0 and 1.