Classification and Review of Multi-agents Systems in the Manufacturing Section

Andreadis, Georgios; Klazoglou, P.; Niotaki, Kyriaki; Bouzakis, K.‐D.

doi:10.1016/j.proeng.2014.02.233

Cited by 36 publications

(16 citation statements)

References 13 publications

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“…In the manufacturing field, Industry 4.0 is characterized by the autonomous systems with cyber and physical representation [20][21][22] and advance in ICT [23] such as cloud computing [24], internet of things (IoT), internet of service (IoS) [25][26][27][28][29], agent technology [30][31][32][33][34][35], cognitive technology [36,37], big data [38,39], data mining [40,41], and artificial intelligence [42][43][44][45][46][47]. Smart manufacturing systems (SMS) built with intelligent cyber-physical systems (CPSs) are the heart of the fourth industrial revolution [21,48].…”

Section: Introductionmentioning

confidence: 99%

“…The development of manufacturing not only considers technological innovations but also economic, social and environmental effects [4,7]. In the literature, many novel paradigms known as intelligent manufacturing systems (IMS) [8][9][10][11][12][13][14][15] have been proposed such as holonic [16], biological [17], reconfigurable [18], and cloud manufacturing systems [19].In the manufacturing field, Industry 4.0 is characterized by the autonomous systems with cyber and physical representation [20][21][22] and advance in ICT [23] such as cloud computing [24], internet of things (IoT), internet of service (IoS) [25][26][27][28][29], agent technology [30][31][32][33][34][35], cognitive technology [36,37], big data [38,39], data mining [40,41], and artificial intelligence [42][43][44][45][46][47]. Smart manufacturing systems (SMS) built with intelligent cyber-physical systems (CPSs) are the heart of the fourth industrial revolution [21,48].…”

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confidence: 99%

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Development of a Smart Cyber-Physical Manufacturing System in the Industry 4.0 Context

Tran

Park²,

Nguyen

et al. 2019

Applied Sciences

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Featured Application: A proposed smart manufacturing system has the ability to adapt to manufacturing changes. Abstract:The complexity and dynamic of the manufacturing environment are growing due to the changes of manufacturing demand from mass production to mass customization that require variable product types, small lot sizes, and a short lead-time to market. Currently, the automatic manufacturing systems are suitable for mass production. To cope with the changes of the manufacturing environment, the paper proposes the model and technologies for developing a smart cyber-physical manufacturing system (Smart-CPMS). The transformation of the actual manufacturing systems to the Smart-CPMS is considered as the next generation of manufacturing development in Industry 4.0. The Smart-CPMS has advanced characteristics inspired from biology such as self-organization, self-diagnosis, and self-healing. These characteristics ensure that the Smart-CPMS is able to adapt with continuously changing manufacturing requirements. The model of Smart-CPMS is inherited from the organization of living systems in biology and nature. Consequently, in the Smart-CPMS, each resource on the shop floor such as machines, robots, transporters, and so on, is an autonomous entity, namely a cyber-physical system (CPS) which is equipped with cognitive capabilities such as perception, reasoning, learning, and cooperation. The Smart-CPMS adapts to the changes of manufacturing environment by the interaction among CPSs without external intervention. The CPS implementation uses the cognitive agent technology. Internet of things (IoT) with wireless networks, radio frequency identification (RFID), and sensor networks are used as information and communication technology (ICT) infrastructure for carrying out the Smart-CPMS.Currently, manufacturing demands are changing from mass production to mass customization, which is focused on exclusive and individualized demand [2,3]. This trend requires the manufacturing systems to have the ability to adapt to the fast change of the manufacturing environment. To face this challenge, the new trend of manufacturing system development is to apply autonomous behaviors inspired from living systems and nature to have the sustainable manufacturing systems. Industry 4.0 enables the realization of sustainable manufacturing using the ubiquitous information and communication technology (ICT) infrastructure [4]. National strategies for developing smart manufacturing systems are focused on by both developing and developed countries [5,6]. The development of manufacturing not only considers technological innovations but also economic, social and environmental effects [4,7]. In the literature, many novel paradigms known as intelligent manufacturing systems (IMS) [8][9][10][11][12][13][14][15] have been proposed such as holonic [16], biological [17], reconfigurable [18], and cloud manufacturing systems [19].In the manufacturing field, Industry 4.0 is characterized by the autonomous systems with cyber and physical representation [20]...

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Development of a Smart Cyber-Physical Manufacturing System in the Industry 4.0 Context

Tran

Park²,

Nguyen

et al. 2019

Applied Sciences

View full text Add to dashboard Cite

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“…This technology has absorbed lots of attention for exceptional research activities during previous years. As in every technology, the agents possess a variety of special skills thus they are fruitful for distributed, unstructured and decentralized architectures which are complicated due to changes (Andreadis et al, 2014). The term "agent" defines a hardware or (more usually) softwarebased computer system that has the following characteristics:…”

Section: Introductionmentioning

confidence: 99%

“…Agents communicate, collaborate, coordinate and negotiate in a system designed and implemented as a multi-agent system (Andreadis et al, 2014). Supply Chains are comprised of production subsystems, which are heterogeneous and gathered in vast dynamic and virtual coalitions, where each element (or production subsystem) has its own individual goals, while satisfying both local and external constraints.…”

Section: Introductionmentioning

confidence: 99%

Supplier selection in an agent based pharmaceutical supply chain: An application of TOPSIS and PROMETHEE Π

Pourghahreman¹,

Qhatari²

2015

10.5267/j.uscm

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Having a supply chain is an unavoidable fact and all companies should focus on if they wish to survive in the competitive business world. This paper ranks criteria influencing on behavior of a medicine manufacturer agent when its goal is to select the supplier agents to interact with across a pharmaceutical agent based supply chain. The pharmaceutical industry is important for countries due to the distinguished role of health in societies and Iran is not an exception too. Besides, the industry in this country is encountered with some limitations because of the situation imposed by sanctions. In this study, first, ten criteria were selected based on expert's opinions, two categories of quantitative as well as qualitative criteria were chosen for ranking the criteria and then TOPSIS and PROMETHEE Π methods were applied to rank the criteria. According to the results of this survey, qualitative criteria were determined as important factors influencing on supplier selection.Growing Science Ltd. All rights reserved. 5

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“…In MAS, agents are used to represent the logical or physical resources in scheduling process and they together abide by some kind of agreement to fulfill the scheduling objectives through mutual coordination [6]. These characteristics of MAS can precisely match the features of offshore platform project scheduling.…”

Section: Introductionmentioning

confidence: 99%

Development of a Collaborative Scheduling System of Offshore Platform Project Based on Multiagent Technology

Yang

et al. 2014

Advances in Mechanical Engineering

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Aimed at enhancing the effectiveness and efficiency for offshore platform project scheduling, a multiagent collaborative scheduling model based on the analysis of distributed offshore platform project scheduling was proposed. The functional definitions and internal structure of agents in the proposed system were analyzed. Moreover, in order to explore the cooperative way of agents, communication mechanism was presented and a negotiation model was elaborated. Then, system architecture and hardware architecture were constructed to lay a foundation to develop the collaborative scheduling system. Finally, an intelligent algorithm based on Bayesian method was designed to verify the negotiation model and a prototype system was developed to test the feasibility and rationality.

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Classification and Review of Multi-agents Systems in the Manufacturing Section

Cited by 36 publications

References 13 publications

Development of a Smart Cyber-Physical Manufacturing System in the Industry 4.0 Context

Development of a Smart Cyber-Physical Manufacturing System in the Industry 4.0 Context

Supplier selection in an agent based pharmaceutical supply chain: An application of TOPSIS and PROMETHEE Π

Development of a Collaborative Scheduling System of Offshore Platform Project Based on Multiagent Technology

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