Advances in the Smart Data Analytics Framework: Integrating Data Extraction and Automated Reporting

The efficient fusion of information from different data silos in a process plant is essential for a smart data analytics platform. Researchers have developed a GUI-based framework, namely, AMtool, to integrate alarm data and sensor (process) data complemented with process connectivity information. This state-of-the-art smart data analytics framework integrates advanced techniques for data analysis and visualization, performance evaluation, and alarm configuration. This framework also supports alarm flood analysis along with documentation to aid alarm rationalization, enabling industrial processes to become compliant with industry standards. However, an earlier version of the AMtool faced limitations in meeting the automation and real-time data exchange requirements emphasized by the Industry 4.0 paradigm. In this paper, we discuss the recent advances and improvements to make the tool compliant with Industry 4.0 standards, namely, the data extraction interface and automated reporting feature. The data extraction interface facilitates secure and efficient data collection via SQL databases and OPC UA platforms. Additionally, the report generation is more automated for an efficient and more user-friendly option for the regular generation of alarm analysis reports.