Integration in industrial automation based on multi-agent systems using cultural algorithms for optimizing the coordination mechanisms

Terán, Juan; Aguilar, José; Cerrada, Mariela

doi:10.1016/j.compind.2017.05.002

Cited by 47 publications

(10 citation statements)

References 17 publications

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“…Multi-agent systems can be useful for this task (Terán et al, 2017), or another platform, such as ROS Industrial (ROS Industrial, 2018). In this sense, a previous work conducted by Aguilar et al (2017d) details how to deal with issues related to the bidirectional communication of software agents and cloud-services, naturally.…”

Section: Discussionmentioning

confidence: 99%

Implementing self-* autonomic properties in self-coordinated manufacturing processes for the Industry 4.0 context

Sánchez¹,

Expósito²,

Aguilar³

2020

Computers in Industry

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Section: Discussionmentioning

confidence: 99%

Implementing self-* autonomic properties in self-coordinated manufacturing processes for the Industry 4.0 context

Sánchez¹,

Expósito²,

Aguilar³

2020

Computers in Industry

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“…ACODAT is one of these strategies, which consists of a set of data analysis tasks that must be performed together to achieve an objective in a given system or situation [24] . This set of tasks interacts, and has different roles in the cycle [25] , [26] : observing the process, analyzing and interpreting what happens in it, and making decisions to achieve the objective for what the cycle was designed.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

An autonomous cycle of data analysis tasks for the clinical management of dengue

Hoyos

Aguilar²,

Toro³

2022

Heliyon

Self Cite

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“…In [286], the authors propose the modeling and synthesis procedures to obtain optimal decentralized industrial controllers in state-feedback form for distributed agents. [287], presents a multi-agent method for industrial process integration implementing coordination optimization mechanisms that enable distributed agent data exchanges, by using cultural algorithms. In [289], the authors introduce noncooperative agents which make decisions based on the capacity allocation and the data of all other agents, thus creating a decentralized feedback loop.…”

Section: B Data Centric Industrial Services 1) Ar / Vrmentioning

confidence: 99%

Data Management in Industry 4.0: State of the Art and Open Challenges

2019

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Information and communication technologies are permeating all aspects of industrial and manufacturing systems, expediting the generation of large volumes of industrial data. This article surveys the recent literature on data management as it applies to networked industrial environments and identifies several open research challenges for the future. As a first step, we extract important data properties (volume, variety, traffic, criticality) and identify the corresponding data enabling technologies of diverse fundamental industrial use cases, based on practical applications. Secondly, we provide a detailed outline of recent industrial architectural designs with respect to their data management philosophy (data presence, data coordination, data computation) and the extent of their distributiveness. Then, we conduct a holistic survey of the recent literature from which we derive a taxonomy of the latest advances on industrial data enabling technologies and data centric services, spanning all the way from the field level deep in the physical deployments, up to the cloud and applications level. Finally, motivated by the rich conclusions of this critical analysis, we identify interesting open challenges for future research. The concepts presented in this article thematically cover the largest part of the industrial automation pyramid layers. Our approach is multidisciplinary, as the selected publications were drawn from two fields; the communications, networking and computation field as well as the industrial, manufacturing and automation field. The article can help the readers to deeply understand how data management is currently applied in networked industrial environments, and select interesting open research opportunities to pursue.

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Integration in industrial automation based on multi-agent systems using cultural algorithms for optimizing the coordination mechanisms

Cited by 47 publications

References 17 publications

Implementing self-* autonomic properties in self-coordinated manufacturing processes for the Industry 4.0 context

Implementing self-* autonomic properties in self-coordinated manufacturing processes for the Industry 4.0 context

An autonomous cycle of data analysis tasks for the clinical management of dengue

Data Management in Industry 4.0: State of the Art and Open Challenges

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