The organization of production is based on technological preparation processes and subsequent tests for certification of a new product line. The existing methodology for organizing production is based on the basic structures of production technologies that include heterogeneous technological systems with a control superstructure and pronounced standard group elements that make up the integrity of any technology: personnel, equipment, materials and processes. Changing the standard element will change the state of the technological system; therefore, the introduction of the SMED methodology for the technological preparation processes of organizing new production or the optimization of existing production cycles will lead to a reduction in typical losses and a decrease in production cycle costs.
This article focuses on the decision of problems of increase of efficiency of introduction of innovation in industrial enterprise. The publication includes a description of the author’s approach to innovation in the industrial enterprise, implemented in the form of a database. The main functions of the database are divided into two main stages – preparatory and informative. The functions of the preparatory stage include the collection of information about the industrial enterprise, the rationale for the choice of innovation, determination of the composition and administration of training (retraining), justification of the technical appearance of innovation. At the supporting stage, the database allows information support in the development and implementation of innovations in terms of timing, volume and costs, to carry out a priori and a posteriori evaluation of the quality of innovation on the basis of situational norms, as well as support for decision-making on innovation management in the industrial enterprise. The database is based on the theory of system analysis, the basic principles of the theory of innovation, methods of situational modeling, graph theory and probability theory. The results of the developed database can be used by modern industrial enterprises in the implementation of innovations.
Numerical methods for solving mathematical problems describing the state of complex physical systems in modern digital production can be used to assess the quality and viability of materials used in additive manufacturing. In this article, the Dzeno model is chosen, as the physical behavior of the body under dynamic load and the gradual attenuation of the load.
Computer modeling of the behavior of materials is very important for the development of additive technologies at the present stage. This article is devoted to a review of models that can and should be used for numerical modeling of material deformation as applied to additive technologies in the process of layer-by-layer synthesis, as well as an exposition of the Cosserat elastoplastic model, the rationale for its application for modeling plastic deformation in structurally inhomogeneous materials such as polymers for additive manufacturing.
Аннотация. Рассматриваются особенности применения спектрофотометрического метода для исследования этилового спирта в некоторых сортах пивной продукции. Методы оптической спектроскопии позволяют количественно и качественно анализировать состав вещества. Эти высокоточные, информативные, а также экономичные методы широко применяются в силу доступности приборного обеспечения, легкости получения и интерпретации информации. Представлен внешний вид спектрофотометра, дана оптическая схема и приведены технические характеристики прибора. Получены и проанализированы спектральные зависимости коэффициента поглощения доли этилового спирта в разных сортах пива. Найдено максимальное поглощение в представленных жидкофазных средах в диапазоне длин волн от 200 до 1100 нм.
The article considers the task of assessing the quality of an intelligent decision support system for monitoring complex technical systems. A hierarchical system of indicators of the information system quality is presented, with account to the specifics of the subject area. It is proposed to use information power as a generalized indicator of the quality of the upper level which is formed from group indicators of the 1st level: information potential, functional suitability, level of performance, compatibility, usability, reliability, security and maintainability. To aggregate heterogeneous indicators, both quantitative and qualitative, at various levels of the system hierarchy, measured on different scales and having a different range of values, an approach based on a fuzzy classification of parameter values and fuzzy inference using the Takagi-Sugeno algorithm is used. The quantitative assessment of the indicator is supplemented by a qualitative assessment, expressed in the form of a linguistic description and the degree of evaluative confidence in the result of the assessment, which is understandable and convenient when used in the decision development process. The considered structure of quality indicators and a fuzzy model for their assessment can be applied in the quality management of existing and promising decision support systems and automated information systems.
The article considers a target approach to assessing the organizational effectiveness of the functioning of an intelligent decision support system for controlling complex instrumental equipment at the level of a technological control system. As an indicator of organizational efficiency, it is proposed to use the degree of achievement of an organizational goal based on a comparison of the result obtained (the organizational effect of the intellectual system) and the goal (improving the quality of management decisions). To determine the organizational effect, the indicator of the level of organization of activities is used, and for the quantitative presentation of the goal - the coefficient of the quality of managerial decisions, which characterizes their accuracy and timeliness. It is proposed to supplement the quantitative assessment of effectiveness with a qualitative assessment in the form of a verbal description of the degree of achievement of the organizational goal, which is more understandable and convenient for decision-makers. To obtain a qualitative assessment, a five-level fuzzy classifier of an indicator of the organizational effectiveness of an intelligent system is used. The obtained theoretical results can be applied in the development and implementation of intelligent systems to analyze their organizational effectiveness at all stages of the product life cycle.
The article describes the approaches to the analysis of drifting models of the functional properties of products or technological systems. Methods for analyzing the transitional states between modernization and degradation of the potential of a product or a technological system are described. Drifting models are based on the principles of functionally sufficient and functionally necessary states of products.
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