Knowledge Based Planning Framework for Intelligent Distributed Manufacturing Systems

Fedorov, A; Shkodyrev, Viacheslav; Zobnin, Sergey

doi:10.1007/978-3-319-20472-7_32

Cited by 5 publications

(3 citation statements)

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“…In the study of Kravchenko (2019) proposed strategies for personnel development in order to develop new effective management tools for intelligent production systems. Fedorov et al (2015) in their work identified the features and advantages of software platforms in intellectual production based on the knowledge and competencies of personnel. At the same time, both in foreign and domestic industry, when introducing innovations and switching to intelligent production systems, the capabilities of personnel are not fully evaluated, while highly qualified personnel are the source and tool for modernizing petrochemical production.…”

Section: Problem Statementmentioning

confidence: 99%

Training Of Personnel In The Conditions Of Innovative Management Of Petrochemical Production

Nurgaliev¹

2021

European Proceedings of Social and Behavioural Sciences

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Section: Problem Statementmentioning

confidence: 99%

Training Of Personnel In The Conditions Of Innovative Management Of Petrochemical Production

Nurgaliev¹

2021

European Proceedings of Social and Behavioural Sciences

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“…For example rule "If car is broken the traffic jam probability will be High" and rule "If number of cars near semaphore a 10 then traffic jam probability will be Medium" will be merged to rule "If number of cars is 10 and car ahead is broken then the probability of traffic jam will be Very High". The basic approach of distributed knowledge base is described in paper [5] and [6].…”

Section: Fig 2 Distributed Knowledge Based Decision Makingmentioning

confidence: 99%

Fuzzy Decision Support in Distributed V2V Systems

Федоров¹,

Zobnin²,

Shkodyrev³

et al. 2016

DAAAM Proceedings

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This paper presents a new approach of automated decision making in vehicle-to-vehicle (V2V) environments. Approach is based on extension of fuzzy knowledge-based decision making with automatic V2V communication that provides an ability for systems of Intelligent Transportation Agents (ITAs) to create a distributed network, where each agent is a part of the coalition that reacts to the environment changes (such as traffic jams, car accidents etc.). This paper considers a particular task of finding the shortest path in dynamical environments. An architecture of the system as well as mathematical model and simulation results is presented in the paper.

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“…All-round automation of complex manufacturing process includes its fuzzy model to be created [1]. Afterwards this model is to be refined step by step.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Intelligent Manufacturing Control Systems

Yerofeyev¹,

Ipatov²,

Markov³

et al. 2016

DAAAM Proceedings

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The article is devoted to development of the concept of the integrated intelligent control system for complex manufacturing process. The base of the system is recurrent decomposition method, which allows reconfiguring systems logical structure in case of the given optimum criteria. A recurrent decomposition model of the general problem of manufacturing process automation and the algorithm of multi-level control for automated facilities with scalable tree structures are suggested. In this paper, the design of processes, as well as the problem of automating the lifecycle of the product are considered within the concept of Industry 4.0. The methods of final product quality control based on the control and testing processes optimization are considered as well as methods of structural and parametric optimization of technological processes. Some application examples of the developed mathematical models for technological systems are given.

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Knowledge Based Planning Framework for Intelligent Distributed Manufacturing Systems

Cited by 5 publications

References 1 publication

Training Of Personnel In The Conditions Of Innovative Management Of Petrochemical Production

Training Of Personnel In The Conditions Of Innovative Management Of Petrochemical Production

Fuzzy Decision Support in Distributed V2V Systems

Adaptive Intelligent Manufacturing Control Systems

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