СЪДЪРЖАНИЕ
- автоматика
М. Хаджийски, Интегриране на технологиите на изкуствения интелект в индустриалните системи за автоматизация - Н. Делийски, Н. Тумбаркова, Д. Ангелски, П. Вичев, К. Атанасова, Изчисляване на енергийния разход за разтопяване на леда в дървесината с използване на софтуера Table Curve 2D
- С. Мизанали, А. Килитчи Калайър, Интелигентни домове и взаимодействие между хора и компютри: оценка от гледна точка на сигурността
- 75-годишен юбилей на проф. д-р инж. Ангел Смрикаров
- Доц. д-р инж. Драгомир Добруджалиев на 75 години
Key Words: Artificial Intelligence; integration; industrial automation; industrial control systems; Machine Learning; operational control; technological control.
Abstract. The newly emerging challenges of interpenetration and multifaceted integration of modern artificial intelligence technologies and leading computer systems of industrial automation are considered in the article. The relatively independent development of industrial automation and artificial intelligence has reached in the last one or two decades such a high technological level of openness, flexibility and compatibility, creating prerequisites to build integrated systems based on a holistic synthesis of a completely new type for solving tasks which until recently were considered intractable. The new conditions of competition are significantly complicated due to the extremely accelerated dynamics and depth of the various stages of industrial processes – supply chains, transportation problems, technological breakthroughs in the basic facilities and processes, malicious cyber attacks, situations resulting from global geopolitical conflicts. The main achievements that give rise to huge expectations for overcoming these and the expected future challenges are: the fundamentally new level of information treatment (Big Data), the modern achievements of computing technology (Industrial Internet of Things – IIoT, cloud technologies, computing architectures based on of graph models) and the explosive development of artificial intelligence (multidimensional and multi-aspect models, automatic prediction, decision-making and planning, revealing implicit relationships and dependencies, learning based on historical, current and simulation data, human-machine interaction of a new type ). Under the new highly complicated conditions and increased requirements, industrial automation is steadily following its trajectory of expanding its scope of action – from primarily technological control to gradually including all sides of the operational control and management (planning, production schedules, predictive maintenance of the facilities, adaptation to the goals and situations in the short and long term). The realistic approach requires strategic decisions in the development of industrial automation to be in the direction of „end-to-end automation“ by upgrading existing systems while uncompromisingly evaluating the advantages and disadvantages of the relevant artificial intelligence technologies that we have now.
