Метод экспертного выбора цифровых компонентов систем промышленной автоматики на основе марков¬ской модели

Abstract

Expert evaluation and reasonable selection of digital components in the microelectronic market is a complex and responsible task. For its solution, the known methods of carrying out expert estimations do not fit fully in connection with the laboriousness of the results processing. The development of an expert choice method for digital components that allows you to quickly obtain a generalized collective expert evaluation (CEE), evaluate the consistency of expert opinions and make informed decisions is a quite actually. The goal of the study is to develop a method for forming a voucher for the selection of digital components of industrial automation systems based on the Markov chain and its verification in the real practical situation. A method is proposed for CEE forming for complex components of automation systems based on the Markov model. When aggregating expert preferences, each alternative is represented as a state of the Markov chain. Next, for the vertices of a Markov graph, the Copeland number is calculated, equal to the difference between the number of arcs entering and leaving the vertex. In collective ranking, alternatives are arranged in descending Copeland numbers. The developed method has a high speed in comparison with the known analogs. The correctness of the proposed method, its efficiency and speed has been confirmed by real expertise and in the process of computer modeling. The executed researches showed that the developed method for the collective expert evaluation forming works 80-200 times faster than the method based on the median Kemeni. The practical significance of the proposed method has been demonstrated on the real expertise carried out at the enterprise «Krioprom» (Odessa, Ukraine) when purchasing a batch of programmable logic microcontrollers within the large-scale project framework for cleaning units automation of industrial air-separation plants.