Highlighting the benefits of Industry 4.0 for production: an agent-based simulation approach

Abstract: Advanced Manufacturing or Industry 4.0 concepts bring new advances and challenges to current industrial processes. Such concepts are not always well understood and their results in terms of production performance may not be clear. This work proposes a comparison between a traditional manufacturing process and an advanced manufacturing process, both modelled by a multiagent society. In the traditional manufacturing simulation, the agents follow the defined times of each process, including the maintenance times. In the advanced manufacturing simulation, the decision about when to stop a piece of equipment for maintenance is defined by the agent according to data received from sensors and the definitions of the process. The results indicate a significant improvement in equipment usage and consequently higher production in the same time interval. The process simulation clearly indicates that the application of advanced manufacturing concepts in industry is relevant in order to increase the efficiency of production processes. Among the main concepts introduced in advanced manufacturing models are the Internet of Things (IoT), Cyber-Physical Systems (CPSs), and Artificial Intelligence (AI). The models generated are computationally simulated using an agent-based simulation method from the software AnyLogic. The results obtained should contribute to encouraging small and medium sized enterprises to adopt the concepts of Industry 4.0 in their businesses.

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Development of a multimodal (railroad-water) chain of grain supply by the agent-based simulation method

Eastern-European Journal of Enterprise Technologies ◽

10.15587/1729-4061.2020.220214 ◽

2020 ◽

Vol 6 (3 (108)) ◽

pp. 14-22

Author(s):

Anatolii Mazaraki ◽

Viacheslav Matsiuk ◽

Nataliia Ilchenko ◽

Olha Kavun-Moshkovska ◽

Tetyana Grygorenko

Keyword(s):

Simulation Method ◽

Agent Based Simulation ◽

Agent Based ◽

Water Chain

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Process Estimation of Word-of-Mouth Information Spread Based on Ad Hoc Communications

Journal of Advanced Computational Intelligence and Intelligent Informatics ◽

10.20965/jaciii.2012.p0619 ◽

2012 ◽

Vol 16 (5) ◽

pp. 619-630

Author(s):

Daisuke Katagami ◽

◽

Mizuki Takei ◽

Katsumi Nitta ◽

Keyword(s):

Time Series ◽

Word Of Mouth ◽

Ad Hoc ◽

Cluster Structure ◽

Simulation Method ◽

Agent Based Simulation ◽

Agent Based ◽

Transmitted Information ◽

The People ◽

Information Spread

We focus on the information spread in ad hoc communications, and propose a method of estimating process of word-of-mouth information spread based on analysis of the human network generated by using a contact history among people. This method extracts the cluster structure of people which changes according to the time-series and identifies the clusters including the people which transmitted information. The results of the experiments which applied the proposal method to the data generated by using an agent based simulation method shows that it becomes possible to estimate the information spread process from a connection among the clusters in the human network.

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Agent-Based Simulation Method of Complex System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.380-384.1378 ◽

2013 ◽

Vol 380-384 ◽

pp. 1378-1381 ◽

Cited By ~ 3

Author(s):

Jia Zhe Lai ◽

Shan Liang Liao

Keyword(s):

Complex System ◽

Simulation Method ◽

Space System ◽

Agent Based Simulation ◽

Agent Based ◽

Agent Platform ◽

Forecasting Method ◽

Agent Structure

In this paper a method is introduced to simulate the Complex system by ABMS . space system can be considered a complex system that is composed of many satellites ,which need a powerful and flexible method to study , MAS structure of space system is gived by analyzing its hiberarchy , by studying the navigation agent , a typical agent structure is gived . introduce the RepastHPC agent platform using MPI , orbit forecasting method is studying , Finally, we realize the MAS simulation and run it on parallel cluster .

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Comparing Three Simulation Model Using Taxonomy: System Dynamic Simulation, Discrete Event Simulation and Agent Based Simulation

International Journal of Management Excellence ◽

10.17722/ijme.v1i3.17 ◽

2013 ◽

Vol 1 (3) ◽

pp. 54-59

Author(s):

Suliza Sumari ◽

Roliana Ibrahim ◽

Nor Hawaniah Zakaria ◽

Amy Hamijah Ab Hamid

Keyword(s):

Simulation Model ◽

Discrete Event Simulation ◽

Discrete Event ◽

Simulation Method ◽

System Dynamic ◽

Agent Based Simulation ◽

Agent Based ◽

Event Simulation ◽

System Dynamic Simulation

Simulation model is one of the methods commonly used in Operational Research in order to represent the real situation that occurs in a system as well as to test the scenario based on different behavior. In this paper we discuss about three different models used in simulation: system dynamic, agent based simulation and discrete event simulation. The aim of this paper is to compare all these three methods in context of features, advantages, disadvantages and tools being used in each simulation method. The comparison of this paper also includes the classification of simulation model using taxonomy. Throughout this paper, we view a few software tools usually being used in a simulation like Vensim, ProModel and AnyLogic.

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Agent Based Simulation of Group Emotions Evolution and Strategy Intervention in Extreme Events

Discrete Dynamics in Nature and Society ◽

10.1155/2014/464190 ◽

2014 ◽

Vol 2014 ◽

pp. 1-17 ◽

Cited By ~ 3

Author(s):

Bo Li ◽

Duoyong Sun ◽

Shuquan Guo ◽

Zihan Lin

Keyword(s):

Complex System ◽

Extreme Events ◽

Collective Behavior ◽

Intervention Strategy ◽

Simulation Method ◽

Chain Model ◽

Agent Based Simulation ◽

Agent Based ◽

Group Emotions ◽

Group Emotion

Agent based simulation method has become a prominent approach in computational modeling and analysis of public emergency management in social science research. The group emotions evolution, information diffusion, and collective behavior selection make extreme incidents studies a complex system problem, which requires new methods for incidents management and strategy evaluation. This paper studies the group emotion evolution and intervention strategy effectiveness using agent based simulation method. By employing a computational experimentation methodology, we construct the group emotion evolution as a complex system and test the effects of three strategies. In addition, the events-chain model is proposed to model the accumulation influence of the temporal successive events. Each strategy is examined through three simulation experiments, including two make-up scenarios and a real case study. We show how various strategies could impact the group emotion evolution in terms of the complex emergence and emotion accumulation influence in extreme events. This paper also provides an effective method of how to use agent-based simulation for the study of complex collective behavior evolution problem in extreme incidents, emergency, and security study domains.

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