Modeling and design of information-analytical production processes based on neuro-fuzzy temporal Petri nets

The article is devoted to the issues of modeling and designing information-analytical processes corresponding to the production and technological processes at the enterprise. In the modern conditions of the functioning of the market, the enterprise faces important tasks of embedding in global supply chains, responding to an increase in the need for personalized products and, most importantly, reducing costs and improving product quality. In addition to solving these problems, the enterprise has to deal with such problems as: overproduction, waiting and wasted time, defects and marriage. Despite the fact that economic efficiency is put at the forefront, in order to ensure the sustainable development of an enterprise, it is necessary the criteria of environmental friendliness, accident-free operation and social efficiency. Enterprises, whose competitive advantages are flexibility and response speed to market needs, require tools for the operational management of production and technological processes. For effective functioning within a complex system, planning and implementation of production and technological processes must be supported by appropriate information-analytical processes that provide the collection and analysis of information, as well as modeling and making control decisions for the production and technological process. Production management is carried out in the form of strategic, tactical and operational planning, which puts forward additional requirements for modeling tools and management decision support. A variety of neuro-fuzzy Petri nets with temporal fuzzy neurons is proposed. An example of building a model of the production process and the corresponding information-analytical processes is considered. The developed specialized software for modeling production and technological processes and the implementation of information- analytical processes, including modules for forming an ontological model of a complex system and processes, obtaining data, a neural network supervisor, building a model of a production- technological process and corresponding information-analytical processes using the mechanism constructors based on neuro-fuzzy temporal Petri nets is considered.