scholarly journals LOCALIZED INDUSTRIAL SYSTEMS IN FRANCE: A PARTICULAR TYPE OF INDUSTRIAL SYSTEM

2005 ◽  
pp. 217-236
Keyword(s):  
Industrial System ◽  
Industrial Systems

scholarly journals Diagnostic and Prognostic Models for Predictive Maintenance: Multi-Criteria Comparative Analysis

2021 ◽  
Vol 11 (10) ◽  
pp. 40-49
Author(s):  
Mohammed Bouaicha ◽  
◽  
Imad El Adraoui ◽  
Nadia Machkour ◽  
Hassan Gziri ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Predictive Maintenance ◽  
Prognostic Models ◽  
Industrial System ◽  
Single Model ◽  
Mutual Cooperation ◽  
Industrial Systems ◽  
The Past ◽  
Clear Vision ◽  
The Comparative Study

Predictive maintenance has evolved considerably over the past two decades making this strategy an effective way to monitor the operation of industrial systems, thereby predicting its future states and remaining lifespan. It is therefore developed through a process that begins with the collection of information from the industrial system, the objective of which is its diagnosis or / and its prognosis. This article presents an analysis of single-model and multi-model approaches to the effect of diagnostic and prognostic tasks. This analysis is based on a multi-criteria comparison of the different models in order to provide a clear vision to choose the appropriate approach for predictive maintenance. The relevance of the comparative study is argued by the development of criteria directly impacting performance, reliability, efficiency and mutual cooperation between models. Conclusions are then drawn, in order to identify the appropriate diagnostic and prognostic approach for predictive maintenance.

Modeling the Economic Performance of Industrial Systems Using Mathematical Programming

2015 ◽  
Vol 809-810 ◽  
pp. 1553-1558
Author(s):  
Flavia Fechete ◽  
Anișor Nedelcu
Keyword(s):  
Linear Programming ◽  
Mathematical Programming ◽  
Economic Performance ◽  
Computer Software ◽  
Theoretical Research ◽  
Programming Models ◽  
Optimal Decision ◽  
Management Decision ◽  
Industrial System ◽  
Industrial Systems

Mathematical programming models and especially their subclass - linear programming models - plays an extremely important role, both in theory and in economic practice. Linear programming, through its results, brought a considerable contribution to improving management methods in economics and it has boosted theoretical research in modeling complex economic systems, study and interpretation of laws and economic processes. Developing and designing a model for achieving the economic performance of the industrial system allows managers making optimal decision and ensures the improvement of their activity. This paper aim is to determine an optimal manufacturing program for an industrial system, so that, by its implementation, to achieve economic performance. The manufacturing program conducted using a computer software will allow this entity to optimize their management decision process by providing information related to physical production that must be executed on each of their the products, or about the unused or overloaded capacity, in order to maximize their profits.

scholarly journals Petri Net-Based Approach for “Cyber” Risks Modelling and Analysis for Industrial Systems

2020 ◽  
Vol 170 ◽  
pp. 02001
Author(s):  
K. Labadi ◽  
A.-M. Darcherif ◽  
I. El Abbassi ◽  
S. Hamaci
Keyword(s):  
Cyber Security ◽  
Impact Analysis ◽  
Methodological Approach ◽  
Real Life ◽  
Research Topic ◽  
Industrial System ◽  
Risk Modelling ◽  
Industrial Systems ◽  
Security Challenges ◽  
And Performance

Today, industrial systems are large, complex, and increasingly vulnerable. Specifically, due to the current digital transformation, the industry 4.0 creates crucial cyber-risks and cyber-security challenges. In this context, risk modelling and impact analysis has become a crucial research topic. Based on the formal modelling and performance analysis power of Petri Nets (PN), this paper represents a summary of our methodological approach for “risk” modelling and “impact” analysis of cyber vulnerabilities and / or other critical events. The applicability of the developed approach is demonstrated on a real-life industrial system.

scholarly journals Production Planning of a Failure-Prone Manufacturing System under Different Setup Scenarios

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Guy-Richard Kibouka ◽  
Donatien Nganga-Kouya ◽  
Jean-Pierre Kenne ◽  
Victor Songmene ◽  
Vladimir Polotski
Keyword(s):  
Optimal Control ◽  
Stochastic Optimal Control ◽  
Optimal Control Theory ◽  
Manufacturing System ◽  
Industrial System ◽  
Industrial Systems ◽  
Inventory Costs ◽  
Decision Variables ◽  
Random Disturbances ◽  
System Operating

This paper presents a control problem for the optimization of the production and setup activities of an industrial system operating in an uncertain environment. This system is subject to random disturbances (breakdowns and repairs). These disturbances can engender stock shortages. The considered industrial system represents a well-known production context in industry and consists of a machine producing two types of products. In order to switch production from one product type to another, a time factor and a reconfiguration cost for the machine are associated with the setup activities. The parts production rates and the setup strategies are the decision variables which influence the inventory and the capacity of the system. The objective of the study is to find the production and setup policies which minimize the setup and inventory costs, as well as those associated with shortages. A modeling approach based on stochastic optimal control theory and a numerical algorithm used to solve the obtained optimality conditions are presented. The contribution of the paper, for industrial systems not studied in the literature, is illustrated through a numerical example and a comparative study.

scholarly journals EFFICIENCY INCREASE OF USING INDUSTRIAL RESOURCES: MAIN ASPECTS

2016 ◽  
Vol 2016 (5) ◽  
pp. 318-325 ◽  
Author(s):  
Екатерина Стрижакова ◽  
Ekaterina Strizhakova
Keyword(s):  
Allocative Efficiency ◽  
Industrial System ◽  
Industrial Systems ◽  
Industrial Enterprises ◽  
Adaptive Efficiency ◽  
Heterogeneous Nature ◽  
Efficiency Increase ◽  
Long Time ◽  
System Effectiveness

Economists are interested in problems of increas-ing the efficiency of resource use in industry for a long time. However in modern conditions at the stage of the transfer to innovative way of development in the situa-tion of sanctions it is one of the key problems. In the article the author's principles of industrial systems management are formulated: compliance; systemacity and integrity; safety; coordination. The author's principle is marked out: the principle of alloca-tive according to which it is necessary to accept admin-istrative efforts for maximum effectiveness resources use and the measures applied in management process have to consider heterogeneous nature of the industrial system, and, therefore, in various sectors they have to be various. The author shows a formula for the growth rate of allocation system effectiveness, classification of re-sources and factors is carried out, the directions for the choice of extensive and intensive type of industrial system growth are shown. Special attention is paid to the management of intangible assets. Methods of in-creasing the efficiency of their use at the microlevel (the industrial enterprise) and macrolevel (industrial system of the country) of management are considered. Using the recommendations presented in the article will give the chance to increase allocative efficiency of the used resources, adaptive efficiency of the industrial enterprises that finally will lead to growth of the overall system effectiveness.

scholarly journals A Discrete Process Modelling and Simulation Methodology for Industrial Systems within the Concept of Digital Twins

2022 ◽  
Vol 12 (2) ◽  
pp. 870
Author(s):  
George Tsinarakis ◽  
Nikolaos Sarantinoudis ◽  
George Arampatzis
Keyword(s):  
Data Exchange ◽  
Modelling And Simulation ◽  
Process Models ◽  
Industrial System ◽  
Industrial Systems ◽  
Physical Systems ◽  
Digital Twins ◽  
Alternative Scenarios ◽  
Scientific Fields ◽  
Open Issues

A generic well-defined methodology for the construction and operation of dynamic process models of discrete industrial systems following a number of well-defined steps is introduced. The sequence of steps for the application of the method as well as the necessary inputs, conditions, constraints and the results obtained are defined. The proposed methodology covers the classical offline modelling and simulation applications as well as their online counterpart, which use the physical system in the context of digital twins, with extensive data exchange and interaction with sensors, actuators and tools from other scientific fields as analytics and optimisation. The implemented process models can be used for what-if analysis, comparative evaluation of alternative scenarios and for the calculation of key performance indicators describing the behaviour of the physical systems under given conditions as well as for online monitoring, management and adjustment of the physical industrial system operations with respect to given rules and targets. An application of the proposed methodology in a discrete industrial system is presented, and interesting conclusions arise and are discussed. Finally, the open issues, limitations and future extensions of the research are considered.

scholarly journals Industrial Efficiency Evaluation in China: A Nonparametric Production-Frontier Approach

2019 ◽  
Vol 11 (18) ◽  
pp. 5019 ◽  
Author(s):  
Linlin Zhao ◽  
Lin Zhang ◽  
Yong Zha
Keyword(s):  
Technical Change ◽  
Productivity Index ◽  
Data Envelopment ◽  
Industrial System ◽  
Efficiency Change ◽  
Industrial Systems ◽  
Static Efficiency ◽  
Regular Production ◽  
Dea Models ◽  
Dynamic Data Envelopment Analysis

An industrial system has positive and negative strategies to adapt to environmental regulations, which can be defined as natural disposability and managerial disposability. Meanwhile, the operational process of an industrial system can be divided into regular production activities and pollutant control activities. Within this, industrial system’s technical efficiency (TE) can be decomposed into economic efficiency (ECE) and environmental efficiency (ENE). On the basis of natural disposability and managerial disposability, this paper proposes static and dynamic data envelopment analysis (DEA) models to evaluate the efficiencies of industrial systems. Based on the proposed approach, TE, ECE, ENE, and Malmqusit productivity index (MPI) values were obtained simultaneously. The MPI values were further separated into the effects of static efficiency change and technical change. The proposed method was applied to assess the technical efficiencies of Chinese regional industrial systems between 2011 and 2015. Key findings are that (1) the low ENE is the main source of technical inefficiency; (2) the average static TE and ENE under natural disposability are both lower than those under managerial disposability; (3) the static efficiency change and technical change of TE are similar to those of ENE; and (4) the technical change has a significant impact on the changes in TE.

Contribution of cost-benefit analysis to optimization of eco-design plants

2015 ◽  
Vol 13 (2) ◽  
pp. 334-346 ◽  
Author(s):  
Leila Mellal ◽  
Mébarek Djebabra
Keyword(s):  
Design Methodology ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Environmental Constraints ◽  
Industrial System ◽  
Benefit Analysis ◽  
Content Type ◽  
Industrial Systems ◽  
Functional Behavior ◽  
Practical Implications

Purpose – This study aims to interest the eco-design of the systems. This interest is justified by the need to reducing the environmental impacts in phase of the design plant. Design/methodology/approach – It consists of a proposal for a combined methodology of the industrial systems eco-design. This methodology is based on the simultaneous use of a cost-benefit analysis (CBA) method and dependability tools. Findings – In the developed approach, we use the dependability tools for modeling of the functional behavior of the industrial systems and the CBA method for optimization of the industrial system constraints which are in fact environmental constraints. Practical implications – Methodology suggested constitutes an invaluable help to ensure a better integration of the environment in production. Originality/value – Methodology suggested is tallied by the CBA method, which makes it possible to manage the conflict relation between production and environmental protection.

scholarly journals Multi Agent System Based Approach for Industrial Process Simulation

2021 ◽  
Vol 54 (2) ◽  
pp. 209-217
Author(s):  
Lazhar Benoudina ◽  
Mohammed RedjimiRedjimi
Keyword(s):  
Data Processing ◽  
Industrial Process ◽  
Industrial System ◽  
Industrial Systems ◽  
Agent Platform ◽  
Control Loops ◽  
Proper Functioning ◽  
Concrete Application ◽  
Multi Agent ◽  
Reactive Agents

Industrial systems become more and more complex. This complexity is due to the great number of elements that compose them and their interactions. This paper describes a multi-agent approach for modeling such systems. All of their parts are considered and are modeled by using adequate agents. The set of preoccupations were identified to find convenient multi agent models for their resolutions. Then, we implemented our application by using a MADKIT multi-agent platform. The main goal of this work is to build a simulator based on reactive agents able to translate this complex industrial system into a data processing programs that can represent its structure, its behavior, its interaction, its control loops and verify the integrity and its proper functioning. A concrete application of this approach was materialized by building an industrial gas process simulator.Industrial systems become more and more complex. This complexity is due to the great number of elements that compose them and their interactions. This paper describes a multi-agent approach for modeling such systems. All of their parts are considered and are modeled by using adequate agents. The set of preoccupations were identified to find convenient multi agent models for their resolutions. Then, we implemented our application by using a MADKIT multi-agent platform. The main goal of this work is to build a simulator based on reactive agents able to translate this complex industrial system into a data processing programs that can represent its structure, its behavior, its interaction, its control loops and verify the integrity and its proper functioning. A concrete application of this approach was materialized by building an industrial gas process simulator.Industrial systems become more and more complex. This complexity is due to the great number of elements that compose them and their interactions. This paper describes a multi-agent approach for modeling such systems. All of their parts are considered and are modeled by using adequate agents. The set of preoccupations were identified to find convenient multi agent models for their resolutions. Then, we implemented our application by using a MADKIT multi-agent platform. The main goal of this work is to build a simulator based on reactive agents able to translate this complex industrial system into a data processing programs that can represent its structure, its behavior, its interaction, its control loops and verify the integrity and its proper functioning. A concrete application of this approach was materialized by building an industrial gas process simulator.Industrial systems become more and more complex. This complexity is due to the great number of elements that compose them and their interactions. This paper describes a multi-agent approach for modeling such systems. All of their parts are considered and are modeled by using adequate agents. The set of preoccupations were identified to find convenient multi agent models for their resolutions. Then, we implemented our application by using a MADKIT multi-agent platform. The main goal of this work is to build a simulator based on reactive agents able to translate this complex industrial system into a data processing programs that can represent its structure, its behavior, its interaction, its control loops and verify the integrity and its proper functioning. A concrete application of this approach was materialized by building an industrial gas process simulator.

scholarly journals Integrating Risk Analysis With Safety Dyagnostic In Complex Industrial Systems: Modeling Hazard

2015 ◽  
Vol 66 (1) ◽  
pp. 17-22 ◽  
Author(s):  
Lucian Ionel Cioca ◽  
Roland Iosif Moraru ◽  
Gabriel Bujor Băbuţ ◽  
Nicolae Stelian Ungureanu
Keyword(s):  
Risk Analysis ◽  
Diagnostic Procedures ◽  
Technical System ◽  
The Other ◽  
Industrial Plant ◽  
Hazard Models ◽  
Systems Modeling ◽  
Industrial System ◽  
Industrial Systems ◽  
The One

AbstractAdmitting as known the instruments that lends itself to highlighting the causes - consequences relationships in an industrial plant, the purpose of this research is, on the one hand, to integrate these relationships in the safety diagnostic procedures and, on the other hand, to use these “consequences” to forecast future failures likely to occur within the technical system. In this context, the paper aims to study systemic hazard models to develop structural, functional and behavioural models, describing a complex industrial system

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