What Happens to Process Data in Chemical Industry? From Source to Applications – an Overview

TLDR: This paper briefly overviews some of the commercial products on market and the applicable data analysis techniques which guide process data from source to its application: from technology to expert knowledge with the help of knowledge discovery in databases (KDD) process.

Abstract: It is globally accepted that information is a very powerful asset that can provide significant benefits and a competitive advantage to any organization, like production technologies in the chemical industry, which was driven by market forces, customer needs and perceptions, resulting in more and more complex multi-product manufacturing technologies. These technologies, due to their highly automated level, provide mountains of process data, which is applied only in daily operation and control, but it definitely can give access to the underlying structure of any system. To enhance this automation level while keep operation safe and efficient, one needs more information, i.e. knowledge about the process, which can be extracted from process data, and more tools, which can extract effectively this knowledge. To meet the growing expectations for future chemical engineering tasks, like multi-scale modelling, simulation and control or process and product design, advanced data analysis techniques can lead a way to solution. This paper briefly overviews some of the commercial products on market and the applicable data analysis techniques which guide process data from source to its application: from technology to expert knowledge with the help of knowledge discovery in databases (KDD) process. Numerous citations and their evaluation are given to show that data mining in chemical engineering can efficiently solve many data analysis related problems.