Agent-based Plug and Produce Cyber-Physical Production System – Test Case

Rocha, Andre Dionisio; Tripa, João; Alemão, Duarte; Peres, Ricardo Silva; Barata, José

doi:10.1109/indin41052.2019.8972169

Cited by 10 publications

(6 citation statements)

References 22 publications

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“…This study differs from the works presented in this research regarding the application of CPPS (Hu et al, 2016;Lee et al, 2017;Lee et al, 2018;Drennan-Stevenson, 2019;Cruz Salazar et al, 2018;Ashtari Talkhestani et al, 2019;among others presented), as its focus is on the evaluation of cyberphysical production systems from the point of view of operations management, while most of the works on the subject work from the point of view of the science of computing. However, the approach to work with a focus on the shop floor stands out, especially Romero-Silva & Hernández-López (2020), Govender et al (2019), Torres et al (2019), andRocha et al (2019).…”

Section: Integration Of Machines and The Production Processmentioning

confidence: 99%

“…Recently studies have investigated CPPSs in the most different contexts, such as digital twin (Zhang et al, 2019;Zang et al, 2020;Liu et al, 2020;Ait-Alla et al, 2019), internet of things (Berlak et al, 2020;Stock et al, 2020), cloud computing (Mourtizis & Vlachou, 2016;Mourad et al, 2020;Borangiu et al, 2020), voice assistant (Afanasev et al, 2019) and shop floor (Romero-Silva & Hernández-López, 2020;Govender et al, 2019;Torres et al, 2019;Rocha et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Cyber-physical production system assessment within the manufacturing industries in the Amazon

Coelho

Oliveira

Dessimoni

et al. 2022

Int. J. Prod. Manag. Eng.

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Cyber-physical production systems (CPPS) represent a relevant aspect related to industry 4.0 and the advances promoted by the digitization and use of artificial intelligence in the production environment in the search for the development of smart factories. This study aims to assess the maturity level of cyber-physical production system (CPPS) within manufacturing industries in the Amazon. The research uses a quali-quantitative approach to analyze the problem by conducting exploratory case studies (indepth case) and the research framework used aimed to evaluate and measure the CPPS within three manufacturing industries in the Amazon (n = 3) to measure their maturity. Findings reveal a positive relationship between the type of production system adopted by the company, the level of automation, and the maturity of the CPPS. The proposed methodology can assist other companies in the development of the technological strategy, supporting the digital transformation process in order to obtain competitive advantage. The study contributes by addressing the topic of cyber-physical production systems from the point of view of operations management and strategy.

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Section: Integration Of Machines and The Production Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cyber-physical production system assessment within the manufacturing industries in the Amazon

Coelho

Oliveira

Dessimoni

et al. 2022

Int. J. Prod. Manag. Eng.

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“…The data model designed in [24] in order to abstract this MAS is presented in Figure 2. According to Figure 2, this data model describes four types of entities:…”

Section: Simulation-based Digital Twin Frameworkmentioning

confidence: 99%

“…Therefore, most applications only support workers in the decision-making process [23]. The Distributed Control Layer (DCL) contains the demonstrator from [24], controlled by a fully working MAS capable of dynamically adapting its behaviour according to the production requirements and the available stations.…”

mentioning

confidence: 99%

Application of a Simulation-Based Digital Twin for Predicting Distributed Manufacturing Control System Performance

et al. 2021

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During the last years, several research activities and studies have presented the possibility to perform manufacturing control using distributed approaches. Although these new approaches aim to deliver more flexibility and adaptability to the shop floor, they are not being readily adopted and utilised by the manufacturers. One of the main challenges is the unpredictability of the proposed solutions and the uncertainty associated with these approaches. Hence, the proposed research aims to explore the utilisation of Digital Twins (DTs) to predict and understand the execution of these systems in runtime. The Fourth Industrial Revolution is leading to the emergence of new concepts amongst which DT stand out. Given their early stage, however, the already existing implementations are far from standardised, meaning that each practical case has to be analysed on its own and solutions are often created from scratch. Taking the aforementioned into account, the authors suggest an architecture that enables the integration between a previously designed and developed agent-based distributed control system and its DT, whose implementation is also provided in detail. Furthermore, the digital model’s calibration is described jointly with the careful validation process carried out. Thanks to the latter, several conclusions and guidelines for future implementations were possible to derive as well.

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“…The use of MAS technology addresses the flexibility in terms of software that can be logically controlled [8]. It contains distributed individual intelligent agents throughout the manufacturing process which can negotiate (interact) with each other to make decisions [9,10]. Thereby these agents can solve more complex tasks by negotiating new solutions, which a single agent cannot solve.…”

Section: Introductionmentioning

confidence: 99%

Online Path Planning in a Multi-agent-Controlled Manufacturing System

Ramasamy

Bennulf

Zhang

et al. 2022

Lecture Notes in Mechanical Engineering

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In recent years the manufacturing sectors are migrating from mass production to mass customization. To be able to achieve mass customization, manufacturing systems are expected to be more flexible to accommodate the different customizations. The industries which are using the traditional and dedicated manufacturing systems are expensive to realize this transition. One promising approach to achieve flexibility in their production is called Plug & Produce concept which can be realized using multi-agent-based controllers. In multi-agent systems, parts and resources are usually distributed logically, and they communicate with each other and act as autonomous agents to achieve the manufacturing goals. During the manufacturing process, an agent representing a robot can request a path for transportation from one location to another location. To address this transportation facility, this paper presents the result of a futuristic approach for an online path planning algorithm directly implemented as an agent in a multi-agent system. Here, the agent systems can generate collision-free paths automatically and autonomously. The parts and resources can be configured with a multi-agent system in the manufacturing process with minimal human intervention and production downtime, thereby achieving the customization and flexibility in the production process needed.

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Agent-based Plug and Produce Cyber-Physical Production System – Test Case

Cited by 10 publications

References 22 publications

Cyber-physical production system assessment within the manufacturing industries in the Amazon

Cyber-physical production system assessment within the manufacturing industries in the Amazon

Application of a Simulation-Based Digital Twin for Predicting Distributed Manufacturing Control System Performance

Online Path Planning in a Multi-agent-Controlled Manufacturing System

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