On the Justification of a Risk Matrix for Technical Systems in European Railways

2011 ◽  
pp. 185-193 ◽  
Author(s):  
Jens Braband
Keyword(s):  
Risk Matrix ◽  
Technical Systems

Abstraction: An alternative neurocognitive account of recognition, prediction, and decision making

2020 ◽  
Vol 43 ◽  
Author(s):  
Valerie F. Reyna ◽  
David A. Broniatowski
Keyword(s):  
Decision Making ◽  
Software Engineering ◽  
Systems Engineering ◽  
Evidence Based ◽  
Extensive Literature ◽  
Trace Theory ◽  
Fuzzy Trace Theory ◽  
Abstract Representations ◽  
Technical Systems

Abstract Gilead et al. offer a thoughtful and much-needed treatment of abstraction. However, it fails to build on an extensive literature on abstraction, representational diversity, neurocognition, and psychopathology that provides important constraints and alternative evidence-based conceptions. We draw on conceptions in software engineering, socio-technical systems engineering, and a neurocognitive theory with abstract representations of gist at its core, fuzzy-trace theory.

Analysis of interconnections between technical systems on hierarchically connected technological levels of steel sheet production by hot rolling

2020 ◽  
Vol 76 (8) ◽  
pp. 847-855
Author(s):  
E. N. Shiryaeva ◽  
M. A. Polyakov ◽  
D. V. Terent'ev
Keyword(s):  
Hot Rolling ◽  
Systems Analysis ◽  
Rolling Mill ◽  
Steel Sheet ◽  
Technological System ◽  
Necessary Condition ◽  
Rolled Sheet ◽  
Technological Systems ◽  
Hot Rolling Mill ◽  
Technical Systems

Complexity of modern metallurgical plants, presence of great number of horizontal and vertical interactions between their various structural subdivisions makes it necessary to apply a systems analysis to elaborate effective measures for stable development of a plant operation. Among such measures, digitalization of a plant is widespread at present. To implement the digitalization it is necessary to have clear vision about links at all the levels of the technological system of a plant. A terminology quoted, accepted in the existing regulatory documents for defining of conceptions, comprising the technological system. It was shown, that the following four hierarchical levels of technological systems are distinguished: technological systems of operations, technological systems of processes, technological systems of production subdivisions and technological systems of plants. A hierarchical scheme of technological systems of hot-rolled sheet production at an integrated steel plant presented. Existing horizontal and vertical links between the basic plant’s shops shown. Peculiarities of flows of material, energy and information at the operation “rolling” of the technological system “hot rolling of a steel sheet” considered. As a technical system of the technological process of the hot rolling, the hot rolling mill was chosen. A structural diagram of the hot rolling mill was elaborated, the mill being consisted of reheating furnaces, roughing and finishing stand groups, with an intermediate roll-table between them, and down-coilers section. Since the rolling stands are the basic structural elements of the hot rolling mill, structural diagrams of a roughing and a finishing stands were elaborated. Results of the systems analysis of the technological and technical systems, hierarchically linked in the process of steel sheet hot rolling, can be applied for perfection of organization structure of the whole plant, as well as for elaboration mathematical models of a system separate elements functioning, which is a necessary condition for a plant digitalization.

Sensor fault identification in technical systems based on sliding mode observers

2019 ◽  
pp. 21-28
Author(s):  
Alexey N. Zhirabok ◽  
Alexander V. Zuev ◽  
Alexey Ye. Shumsky
Keyword(s):  
Sliding Mode ◽  
Fault Identification ◽  
Sensor Fault ◽  
Technical Systems ◽  
Sliding Mode Observers

Risk assessment models with functionally different influences on natural and technical systems

2020 ◽  
Vol 89 ◽  
pp. 8-19
Author(s):  
V. A. Minaev ◽  
◽  
N. G. Topolsky ◽  
A. O. Faddeev ◽  
R. O. Stepanov ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Differential Equations ◽  
Research Area ◽  
Practical Implementation ◽  
Model Assessment ◽  
Mathematical Functions ◽  
Effective Response ◽  
Risk Assessment Models ◽  
Technical Systems ◽  
Material Values

Introduction. The complex combination of natural and technogenic factors that lead to dangerous threats to the health and life of the population, as well as to material values, creates a need to develop special mathematical models for risk assessment in the relevant territories. Herewith it is important to take into account the significant differences between these factors. The new areas of research are models that describe natural and technogenic risks using differential equations that reflect different types of functions. The article presents the development of this research area. Goals and objectives. The goal of the article is to create a model for risk assessment in natural and technical systems (PTS), based on taking into account the influences of different natural and technogenic factors on them. Objectives include justification, construction and practical implementation of the mathematical model of risk assessment in the form of differential equations system. Methods include interpretation of the considered influences on PTS in terms of risks and assessment of the dynamic interaction of natural and technogenic factors in the form of inhomogeneous differential equations. Results and discussion. Solutions for models of assessing complex natural and technogenic risks in relation to two cases that differ in NTS are found: functionally different external natural and technogenic influences on PTS, which are understood as their type, in which the effects of both natural and technogenic factors are described by different mathematical functions. Conclusions. The first model considers parabolic (reflecting threats whose intensity gradually decreases with distance from the epicenter) and linear types of influences (reflecting sudden threats). The second model considers parabolic and hyperbolic (reflecting threats, the intensity of which decreases sharply over time) types of influences. It is concluded that it is necessary to create a special computer album of complex influences on the PTS in order to prevent "replay" of various situations and develop the most effective response to emerging dangers from the EMERCOM units and other structures. Key words: model, assessment, natural and technogenic risks, functionally different influences, counteraction, EMERCOM units.

Influential Factors of Collaborative Networks in Manufacturing: Validation of a Conceptual Model

10.28945/2120 ◽  
2015 ◽  
Vol 10 ◽  
pp. 001-019 ◽  
Author(s):  
Danny Wee Hock Quik ◽  
Nevan Wright ◽  
Ammar Rashid ◽  
Sivadass Thiruchelvam
Keyword(s):  
Organizational Support ◽  
Influential Factors ◽  
Perceived Usefulness ◽  
Manufacturing Industries ◽  
Collaborative Networks ◽  
Collaborative Network ◽  
Perceived Effectiveness ◽  
External Stakeholders ◽  
Technical Systems ◽  
External Learning

The purpose of the study is to identify influential factors in the use of collaborative networks within the context of manufacturing. The study aims to investigate factors that influence employees’ learning, and to bridge the gap between theory and praxis in collaborative networks in manufacturing. The study further extends the boundary of a collaborative network beyond enterprises to include suppliers, customers, and external stakeholders. It provides a holistic perspective of collaborative networks within the complexity of the manufacturing environment, based on empirical evidence from a questionnaire survey of 246 respondents from diverse manufacturing industries. Drawing upon the socio-technical systems (STS) theory, the study presents the theoretical context and interpretations through the lens of manufacturing. The results show significant influences of organizational support, promotive interactions, positive interdependence, internal-external learning, perceived effectiveness, and perceived usefulness on the use of collaborative networks among manufacturing employees. The study offers a basis of empirical validity for measuring collaborative networks in organizational learning and knowledge/information sharing in manufacturing.

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