Cognitive smart-technology of distance learning of experion pks distributed control system for oil and gas industry using ontological approach

Abstract

The research is devoted to the actual problem of qualified engineering personnel training for the oil and gas industry of the Honeywell company industrial equipment. There has been developed a cognitive Smart-technology of distance learning of engineers in shared laboratories of Experion PKS distributed control system equipment, which is currently widely used to solve a set of tasks from data collection and processing to technological processes operating modes optimization at refineries. The application of the proposed technology allows to provide high-quality personalized distance learning using ontological models that are designed to analyze the structure of DL, to systematize the input and output data, as well as significantly to improve the quality of the developed complex software. The advantage of the proposed Smart-technology of DL is the use of cognitive methods for the dynamic presentation of educational information using cognitive-visual schemes depending on the type of central nervous system of the student: choleric, sanguine, melancholic or phlegmatic, as well as features of vision in order to improve learning efficiency. Taking into account the individual characteristics of the perception of educational information there was created a personalized learning trajectory. An important feature of the technology is the processing of multidimensional data using a bioinspired approach of artificial immune systems in order to predict learning results and prompt adjustment of the industrial equipment development process.