scholarly journals The Digital Twin for Agricultural Machinery Restoration Processes

2021 ◽  
Vol 31 (4) ◽  
pp. 530-543
Author(s):  
Yuriy G. Sledkov ◽  
Leonid L. Khoroshko ◽  
Pavel M. Kuznetsov ◽  
Anton O. Butko
Keyword(s):  
Production System ◽  
Production Systems ◽  
Discrete Event ◽  
Complete Information ◽  
Information Support ◽  
Agricultural Machinery ◽  
Repair Work ◽  
Digital Twin ◽  
Event Modeling ◽  
Twin Model

Introduction. Agricultural machinery provides the required level of mechanization. Sand abrasive, dirt, and open-air operations considerably accelerate the wear of mechanisms. An improper work plan and lack of complete information about the state of specific equipment units increase the time for repair and maintenance operations. The purpose of the study is to develop a digital twin model for the repair and restoration system of enterprises. The model will reduce material costs and allow for the best solutions to organize the work. Materials and Methods. The model is developed on the basis of simulation modeling. The authors used the approach based on discrete-event modeling with the logical-mathematical apparatus for describing events occurring in a real object. Results. Information support is formed taking into account the parameters of the production systems of repair enterprises and a mathematical model, which is a digital twin of the production system. This approach made it possible to automate the development of optimal plans for organizing repair work by repair enterprises, taking into account their interrelationships. Discussion and Conclusion. The digital twin for the generalized production system of repair organizations allows developing options for the resource allocation and verifying them promptly to choose the best options through accumulating information about the most successful solutions. This will reduce the time for repair and restoration works, improve their quality and save labor.

scholarly journals Construction of Intelligent Integrated Model Framework for the Workshop Manufacturing System Via Digital Twin

2021 ◽  
Author(s):  
Zhongyu Zhang ◽  
Zhenjie Zhu ◽  
Jinsheng Zhang ◽  
Jingkun Wang
Keyword(s):  
Real Time ◽  
Production System ◽  
Manufacturing System ◽  
System Optimization ◽  
Production Cycle ◽  
Model Framework ◽  
The Real ◽  
Digital Twin ◽  
Twin Model ◽  
Information Layer

Abstract With the drastic development of the globally advanced manufacturing industry, transition of the original production pattern from traditional industries to advanced intelligence is completed with the least delay possible, which are still facing new challenges. Because the timeliness, stability and reliability of them is significantly restricted due to lack of the real-time communication. Therefore, an intelligent workshop manufacturing system model framework based on digital twin is proposed in this paper, driving the deep inform integration among the physical entity, data collection, and information decision-making. The conceptual and obscure of the traditional digital twin is refined, optimized, and upgraded on the basis of the four-dimension collaborative model thinking. A refined nine-layer intelligent digital twin model framework is established. Firstly, the physical evaluation is refined into entity layer, auxiliary layer and interface layer, scientifically managing the physical resources as well as the operation and maintenance of the instrument, and coordinating the overall system. Secondly, dividing the data evaluation into the data layer and the processing layer can greatly improve the flexible response-ability and ensure the synchronization of the real-time data. Finally, the system evaluation is subdivided into information layer, algorithm layer, scheduling layer, and functional layer, developing flexible manufacturing plan more reasonably, shortening production cycle, and reducing logistics cost. Simultaneously, combining SLP and artificial bee colony are applied to investigate the production system optimization of the textile workshop. The results indicate that the production efficiency of the optimized production system is increased by 34.46%.

scholarly journals Utilization of computer simulation for optimization of furniture production system

BioResources ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. 6752-6765
Author(s):  
Roman Bambura ◽  
Erika Sujová ◽  
Helena Čierna
Keyword(s):  
Computer Simulation ◽  
Production System ◽  
Production Line ◽  
Production Systems ◽  
Discrete Event ◽  
Simulation Software ◽  
Production Optimization ◽  
Furniture Manufacturing ◽  
Production Processes ◽  
Method Of Production

Computer simulation methods are currently used to simulate production processes and optimize production systems. Computer simulation is one of the most effective tools for implementation of Industry 4.0 principles in industrial practice. This research focused on the optimization of production processes in furniture production using simulation, which is an innovative method of production optimization for furniture manufacturers. The aim of this research was to improve the production system of Slovak furniture manufacturing enterprise by creating a discrete event simulation model of production based on the analysis of its current state. Improvement indicators are specific parameters of the production system, which primarily include material flow, productivity, and workload utilization. First, with the use of Tecnomatix Plant Simulation software and the collected real production data, the original production system processes were simulated and analyzed. Second, the incorporation of more powerful devices was proposed to improve the production line. Third, the proposed improvements were simulated and analyzed. The result of this research was a statistical comparison of the parameters of the current production line and the proposed production improvements.

scholarly journals Risk-Optimized Design of Production Systems by Use of GRAMOSA

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Michael Lütjen ◽  
Abderrahim Ait Alla
Keyword(s):  
Production System ◽  
Production Systems ◽  
System Development ◽  
Discrete Event ◽  
Mathematical Optimization ◽  
Optimized Design ◽  
Domain Specific Modeling ◽  
In Series ◽  
Production Technologies ◽  
Optimized Allocation

Today production and logistic systems are getting more complex. This is a problem which the planning and design of such systems have to deal with. One main issue of production system development in series production is the planning of production processes and systems under uncertainty. New and existing production technologies are often not fully adoptable to new products. This is why some of the main characteristics, like, for example, cost, time, or quality, are not definable at the beginning. Only value ranges and probabilities can be estimated. However, the adaptation process is controllable, which means that the adaptation results are depending on the existing development budget and its resources. This paper presents an approach for the optimized allocation of development resources regarding the adaptation risks of production technologies and processes. The modeling concept GRAMOSA is used for integrated modeling and discrete event-based simulation of the aspired production system. To this end a domain-specific modeling language (DSML) is applied. The further risk-based analysis of the simulation results and the optimized allocation of the development budget are done by use of mathematical optimization.

Application of Enterprise Modelling (EM) Principles to Improving the Performance of a Semi-Automated Production System

2009 ◽  
Vol 62-64 ◽  
pp. 293-302 ◽  
Author(s):  
J.O. Ajaefobi ◽  
R.H. Weston
Keyword(s):  
Production System ◽  
Dynamic Models ◽  
Production Systems ◽  
Discrete Event ◽  
Business Environment ◽  
Automated Production ◽  
Manufacturing Enterprises ◽  
Event Simulation ◽  
Enterprise Modelling ◽  
And Performance

To cope with high levels of complexity, competition and change requirements, manufacturing enterprises (MEs) need to continuously improve their process and resource system performances. Enterprise Modelling (EM) is considered a prerequisite for enterprise integration and performance improvement because it can be used to capture relatively enduring knowledge about any specific business environment in which production systems will be deployed. With this prerequisite in mind, EM principles were deployed to capture and develop ‘static’ models of an SME. This provided detailed descriptions of enterprise production operations and their precedence relationships. A discrete event simulation tool was then used to develop time dependent ‘dynamic’ models of selected process segments of the specific case Enterprise Model. This allowed the computer execution of alternative production system designs to be assessed under SME specific changing scenarios and enabled suggestions for potential improvements to be made.

scholarly journals Design and Implementation of Runtime Verification Framework for Cyber-Physical Production Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Sungjoo Kang ◽  
Ingeol Chun ◽  
Hyeon-Soo Kim
Keyword(s):  
Production Systems ◽  
Heterogeneous Systems ◽  
Runtime Verification ◽  
Production Environment ◽  
Combination Process ◽  
Digital Twin ◽  
Twin Model ◽  
Execution Engine ◽  
Control Command ◽  
Cyber Physical Production Systems

Traditional factories are turning into smart factories with the advent of various ICT technologies, and various control decisions are derived by AI technologies. In this circumstance, runtime verification of a control command is important for zero-defect manufacturing processes but challengeable because factories of the future are highly complex and heterogeneous systems. In this paper, we propose DigTwinOps, a Digital Twin framework for Runtime Verification of Cyber-Physical Production Systems (CPPSs). DigTwinOps features a Digital Twin Execution Engine (DTEE) that manages a Digital Twin Model to synchronize states of a real CPPS object in a production environment. With a monitoring and simulation combination process, a human worker can observe the states of the CPPS object and verify the effectiveness of control commands before applying it to a real production environment. The proposed framework is applied to a CPPS prototype production system, and the results show that the framework can work effectively in the controllability verification of control commands.

scholarly journals Simulation Based Optimization for World Line Card Production System

2012 ◽  
Vol 2 (2) ◽  
pp. 95-104
Author(s):  
Sinan APAK ◽  
Sami ERCAN
Keyword(s):  
Simulation Model ◽  
Production System ◽  
Production Line ◽  
Production Systems ◽  
World Line ◽  
Discrete Event ◽  
Efficient Solutions ◽  
Line Card ◽  
Simulation Based ◽  
Using Data

Simulation based decision support system is one of the commonly used tool to examine complex production systems. The simulation approach provides process modules which can be adjusted with certain parameters by using data relatively easily obtainable in production process. World Line Card production system simulation is developed to evaluate the optimality of existing production line via using discrete event simulation model with variaty of alternative proposals. The current production system is analysed by a simulation model emphasizing the bottlenecks and the poorly utilized production line. Our analysis identified some improvements and efficient solutions for the existing system.

scholarly journals Models for Managing Production Systems of Machine-Building Enterprises Based on the Development and Using of Their Digital Twins

2021 ◽  
Vol 248 ◽  
pp. 04015
Author(s):  
Vitalii A. Dolgov ◽  
Petr. A. Nikishechkin ◽  
Vladimir E. Arkhangelskii ◽  
Pavel I. Umnov ◽  
Alexey A. Podkidyshev
Keyword(s):  
Production System ◽  
Production Systems ◽  
Information Model ◽  
Machine Building ◽  
Digital Twin ◽  
Reliability Indicators ◽  
Digital Twins ◽  
Rational Algorithm ◽  
Building Enterprise ◽  
Traditional Approaches

The paper discusses the goals and objectives of creating digital twins of the production system of a machine-building enterprise. The data structure of the information model of the production system of a machine-building enterprise, which is the basis for building a digital twin, is presented. The paper shows the main approaches to managing a production system based on the construction of its digital twin. It is revealed that along with traditional approaches to PS management by forming recommendations in terms of PS engineering and its operation, the choice of the most rational PS management algorithms that take into account the peculiarities of the production process organization and ensure the formation of production schedules that take into account PS reliability indicators has a great potential. It is proposed to use a specialized language of DPML to describe the information model of the PS through the “product-process-resource” paradigm, which ensures the coordination of the processes of forming recommendations in terms of engineering and operation of the PS, as well as the choice of the most rational algorithm for managing the PS.

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