Fig 5 - uploaded by Georgios Andreadis
Content may be subject to copyright.
![Multi-agent platform [18].](profile/Georgios-Andreadis/publication/261104048/figure/fig1/AS:614137860202497@1523433284230/Multi-agent-platform-18.png)
Source publication
![Fig. 5. Multi-agent platform [18].](profile/Georgios-Andreadis/publication/261104048/figure/fig1/AS:614137860202497@1523433284230/Multi-agent-platform-18_Q320.jpg)
![Fig. 7. Business and manufacturing network [21].](profile/Georgios-Andreadis/publication/261104048/figure/fig2/AS:614137860202499@1523433284257/Business-and-manufacturing-network-21_Q320.jpg)
Current technology and especially Artificial Intelligence effectively increase productivity and take cost out of operations in the Manufacturing sector. One of the main representatives of information technology in the industrial applications are agents. This paper suggests a way to a) categorize multi-agent systems according to the coordination mod...
Contexts in source publication
Context 1
... we mentioned before, agents can enable operations integration. In the project [18] agents are used and aim to the integration of preliminary design with manufacturing planning software systems. In this work, a multi-agent platform for concurrent design and process planning activity integration is examined. The system's structure is represented in Fig. 5. Briefly, we can describe system's structure. The design agent group consists of agents that take care of functional, embodiment and detailed design. As sequence, the design agents belong to design stage. Another agent group, the process planning agent, consists of agents that provide functions such as process selection, resource ...
Context 2
... and graphical user interface. The last three agents belong to a group named as administration agent group. The web agent provides users the ability to interact with agents' beginning and stop. The XML agent offers access to databases' information displayed in the appropriate form via web browsers administration agent group is not visible in Fig. 5. Moreover, the knowledge base agents include a knowledge base handling agent and a mathematical tool handling agent. As Fig. 5 shows, the database agent interacts with a respective database in order to supply other agents with data, such as NC programs and fixture ...
Context 3
... provides users the ability to interact with agents' beginning and stop. The XML agent offers access to databases' information displayed in the appropriate form via web browsers administration agent group is not visible in Fig. 5. Moreover, the knowledge base agents include a knowledge base handling agent and a mathematical tool handling agent. As Fig. 5 shows, the database agent interacts with a respective database in order to supply other agents with data, such as NC programs and fixture ...
Similar publications
Growing competition in the construction industry has forced key players to focus on maintaining high quality and performance within their firms. An engineering consultant has a vital role in the construction market as he represents a client and facilitates the contractor during construction (Turner, 2003). This paper presents a case study of an eng...
An automatic pipe routing system is proposed and implemented. Generally, the pipe routing design as a part of the shipbuilding process requires a considerable number of man hours due to the complexity which comes from physical and operational constraints and the crucial influence on outfitting construction productivity. Therefore, the automation of...
Production processes have over time evolved from the use of just CAD to the integration of CAD and CAM technologies to solve the problem of limited productivity and efficiency. This integration while solving the defined need have had to keep up with the ever-evolving process of product design and manufacture which now includes the inspection of the...
Industrial programming is a tiresome and time-consuming task that requires technical skill. Thus, new and more intuitive ways for people to interact with CNC machines are required to make programming easier. The goal is to present two methods of programming that helps users to program a machine in an intuitive way, providing a high-level of abstrac...
Citations
... There are various approaches in the field of multi-agent systems to achieve this coordination [15,16]. For example, in a centralized approach, one agent undertakes the task of coordinating other agents [17]. In multi-agent systems, approaches within the framework of virtual organizations are very important to determine this responsible agent to ensure coordination among agents. ...
... 16 Distributed generation agent gives production information to the load agent and requests load shedding in underproduction. 17 Load agent requests power from the battery agent. 18 Battery agent provides production information to load agent and requests charge shedding when SoC is low. ...
A microgrid can be defined as a grid of interconnected distributed energy resources, loads and energy storage systems. In microgrid systems containing renewable energy resources, the coordinated operation of distributed generation units is important to ensure the stability of the microgrid. A microgrid needs a successful control scheme to achieve its design goals. Undesirable situations such as distorted voltage profile and frequency fluctuations are significantly reduced by installing the appropriate hardware such as energy storage systems, and control strategies. The multi-agent system is one of the approaches used to control microgrids. The application of multi-agent systems in electric power systems is becoming popular because of their inherent benefits such as autonomy, responsiveness, and social ability. This study provides an overview of the agent concept and multi-agent systems, as well as reviews of recent research studies on multi-agent systems’ application in microgrid control systems. In addition, a multi-agent-based controller and energy management system design is proposed for the DC microgrid in the study. The designed microgrid is composed of a photovoltaic system consisting of 30 series-connected PV modules, a wind turbine, a synchronous generator, a battery-based energy storage system, critical and non-critical DC loads, the grid and the control system. The microgrid is controlled by the designed multi-agent-based controller. The proposed multi-agent-based controller has a distributed generation agent, battery agent, load agent and grid agent. The roles of each agent and communication among the agents are designed properly and coordinated to achieve control goals, which basically are the DC bus voltage quality and system stability. The designed microgrid and proposed multi-agent-based controller are tested for two different scenarios, and the performance of the controller has been verified with MATLAB/Simulink simulations. The simulation results show that the proposed controller provides constant DC voltage for any operation condition. Additionally, the system stability is ensured with the proposed controller for variable renewable generation and variable load conditions.
... flexible, and autonomy allows them to respond to a variety of problems. A common approach for autonomous robotic control is multi-agent systems [25]: each agent has a belief-desire-intention (BDI) software architecture and is responsible for its goals as a "desire" and coordinates with other agents to achieve it [26]. As many robots are batterypowered, autonomous robotic research includes energy use optimization [27]. ...
Modern manufacturing has to cope with dynamic and changing circumstances. Market fluctuations, the effects caused by unpredictable material shortages, highly variable product demand, and worker availability all require system robustness, flexibility, and resilience. To adapt to these new requirements, manufacturers should consider investigating, investing in, and implementing system autonomy. Autonomy is being adopted in multiple industrial contexts, but divergences arise when formalizing the concept of autonomous systems. To develop an implementation of autonomous manufacturing systems, it is essential to specify what autonomy means, how autonomous manufacturing systems are different from other autonomous systems, and how autonomous manufacturing systems are identified and achieved through the main features and enabling technologies. With a comprehensive literature review, this paper provides a definition of autonomy in the manufacturing context, infers the features of autonomy from different engineering domains, and presents a five-level model of autonomy — associated with maturity levels for the features — to ensure the complete identification and evaluation of autonomous manufacturing systems. The paper also presents the evaluation of a real autonomous system that serves as a use-case and a validation of the model.
... Robots are highly flexible devices, and autonomy is used to allow them to respond to a wide variety of situations and applications. A common approach for autonomous robotic control is the employment of multi-agent systems: each agent in this system has a belief-desire-intention (BDI) software architecture where each agent is responsible for its goals as a 'desire' and coordinates with 105 other agents to achieve this goal [26]. A truly autonomous system could develop its own desires by evaluating the environment it interacts with [27]. ...
Modern manufacturing has to cope with dynamic and changing circumstances. Market fluctuations, the effects caused by unpredictable material shortages, highly variable product demand, and worker availability all require system robustness, flexibility, and resilience. To adapt to these new requirements, manufacturers should consider investigating, investing in, and implementing system autonomy. Autonomy is being adopted in multiple industrial contexts, but divergences arise when formalising the concept of autonomous systems. To develop an implementation of autonomous manufacturing systems it is essential to specify what autonomy means, how autonomous manufacturing systems are different from other autonomous systems, and how autonomous manufacturing systems are identified and achieved through the main features and enabling technologies. With a comprehensive literature review, this paper provides a definition of autonomy in the manufacturing context, infers the features of autonomy from different engineering domains, and presents a five-level model of autonomy -- associated with maturity levels for the features -- to ensure the complete identification and evaluation of autonomous manufacturing systems. The paper also presents the evaluation of a real autonomous system that serves as a use-case and a validation of the model.
... The two big groups of architecture are centralized coordination, where one or more Agents are responsible to mediate and coordinate the actions of other Agents (an example can be consulted at [16]) or the decentralized coordination approach where all Agents are responsible for creating and executing a production plan. Focusing on the decentralized approaches, each Agent can communicate with the others through asynchronous messages [17]. One of the most used protocols to communicate between Agents is the Agent Communication Language standardized by Foundation for Intelligent Physical Agents (FIPA) [18]. ...
In a new world where the virtual and physical world is more and more connected, there is a need to project physical devices as digital clones, but the inverse is also true, projecting physical objects from software assets. The proposed work is an approach to connect virtual (software) and the physical (machines) twins using two asynchronous solutions: persistent bi-directional communication and publish subscribe methods on Arduino based controllers. The focus will be in the interaction of virtual and physical reality in order to track the products mainly for academic and investigation proposes but with focus on the applicability on legacy controllers from shop floors, which were not conceived and projected to have these features.KeywordsModular cyber-physical production systemsVirtual environmentIndustrial agentsIndustrial controllersAsynchronous communicationMQTTWebsocketsFIPA
... Several agents are present in a multi-agent system (MASs) (Figure 2), and interact by exchanging messages using a computer network infrastructure [5]. A multi-agent system can be centralized (one central agent undertakes the collection of partial plans from agents) or decentralized (central agent does not control agents) [6]. The decentralized policies must assume merely partial system knowledge in each agent and must tackle communication comprehensively, whereas the centralized policies indicate the decision of the agents based on the global system state. ...
Energy saving is a significant research area in Saudi Arabia; however, significant problems have emerged related to its distribution and consumption. Use of an agent is assumed to combat these problems by forming efficient coalitions to control the energy consumption and energy distribution process. This study presents a novel algorithm for distributing the value calculation among the cooperative agents. This is likely to reduce the consumption of energy and extend the coalition lifetime used. The developed algorithm is compared with the basic modified coalition formation algorithm for evaluating its effectiveness. The results showed a reduction in cooling consumption by 20% after applying optimization algorithms. The amount of reduction in the cooling consumption reflects a 31% reduction in expected cooling costs, without affecting the household comfort. Therefore, the study concludes that DNsys provided better performance than the NNsys.
... On the other hand, the Industrial Internet of Things (IIoT) [24] promises multiple devices connected to the Internet and aims at integrating operational data to the cyber system to achieve smart behaviours. The introduction of software agents and multi-agent systems (MAS) in manufacturing [25] [26] allows the deployment of these complex systems aiming at autonomy and modularity features in control activities, since agents represent fundamental processing units with advance computational capabilities. These context-aware systems will allow manufacturing systems to behave in a more autonomous manner with self-x capabilities (i.e. ...
Purpose of Review
Latest requirements of the global market force manufacturing systems to a change for a new production paradigm (Industry 4.0). Cyber-Physical Systems (CPS) appear as a solution to be deployed in different manufacturing fields, especially those with high added value and technological complexity, high product variants, and short time to market. In this sense, this paper aims at reviewing the introduction level of CPS technologies in micro/nano-manufacturing and how these technologies could cope with these challenging manufacturing requirements.
Recent Findings
The introduction of CPS is still in its infancy on many industrial applications, but it actually demonstrates its potential to support future manufacturing paradigm. However, only few research works in micro/nano-manufacturing considered CPS frameworks, since the concept barely appeared a decade ago.
Summary
Some contributions have revealed the potential of CPS technologies to improve manufacturing performance which may be scaled to the micro/nano-manufacturing. IoT-based frameworks with VR/AR technologies allow distributed and collaborative systems, or agent-based architectures with advance algorithm implementations that improve the flexibility and performance of micro-/nano-assembly operations. Future research of CPS in micro-/nano-assembly operations should be followed by more studies of its technical deployment showing its implications under other perspectives, i.e. sustainable, economic, and social point of views, to take full advance of all its features.
... Manufacturing and logistics flexibility is achieved through continuous adaptation and improvement of processes [5]. The massive increase of available data allows the optimization of various models and methods to improve and to provide adequate decision support for manufacturing processes [6]. With the help of innovative algorithms and intelligent software applications model and data-driven decision support systems provide the basis for decision making in modern manufacturing environments [7]. ...
Digital transformation potentially improves business processes, leading to increased flexibility in manufacturing and logistics networks. Therefore, decision support systems for responsive manufacturing are gaining importance. In this paper, a discrete event simulation model is applied. In order to assess the potential of digital transformation in the context of Industry 4.0 towards production and logistics network robustness, different simulation scenarios are observed. The results contribute to identify potential flexibility measures and to quantify their impact in order to mitigate control uncertainties within production and logistics networks.
... Within the framework of the given paper, the actual AI methods [27] can be mainly subdivided into multiagent systems (MAS), neural networks, and fuzzy logic systems. MAS are primarily applied for the modeling of software and hardware agents in the tasks of interaction with the environment and other agents, as well as for space positioning [28][29][30][31][32][33][34][35]. Modern versions of deep learning neural networks are concentrated on computer vision and speech procession [36][37][38][39]. ...
... Fuzzy systems can also be integrated with neural networks in neuro-fuzzy systems [43]. Such interesting and actual items of AI research, as reasoning, planning, and data representation methods [27] are out of the frame of the given paper, but in Table 2, they can be associated not only with industrial robots [33,34] and unmanned transport [23][24][25], but also with data leakage protection [9] in computer security systems, where the task is to monitor the illegal activity of the staff. Quantum key distribution (QKD) is here the method of confidential generation of cryptographic keys for CN [8,9], as quantum computing is the prospective way to raise the computing performance for some classes of network tasks and for quantum schemes of MAS learning and neural networks [44][45][46]. ...
Quantum optics is regarded as the acknowledged method to provide network quantum keys distribution and in the future secure distributed quantum computing, but it should also provide cryptography protection for mobile robots and the Internet of Things (IoT). This task requires the design of new secret coding schemes, which can be also based on multiple-valued logic (MVL). However, this very specific logic model reveals new possibilities for the hierarchical data clustering of arbitrary data sets. The minimization of multiple-valued logic functions is proposed for the analysis of aggregated objects, which is possible for an arbitrary number of variables. In order to use all the useful properties of the multiple-valued logic, the heterogeneous network architecture is proposed, which includes three allocated levels of artificial intelligence (AI) logic modeling for discrete multiple-valued logic, Boolean logic, and fuzzy logic. Multiple-valued logic is regarded as the possible platform for additional secret coding, data aggregation, and communications, which are provided by the united high dimensional space for network addressing and the targeted control of robotic devices. Models of Boolean and fuzzy logic are regarded as separate logic levels in order to simplify the integration of various algorithms and provide control of additional data protection means for robotic agents.
... Decision support systems (DSS) are tied in with creating and sending IT-based frameworks to support decision processes [1,2]. Since the 1970s, researchers have concentrated on creating PC innovation-based arrangements that can be utilized to help complex basic leadership and problem-solving situations [3]. The zones of the data systems and advancements have developed fundamentally in the most recent decades. ...
... Haettenschwiler [11] separates between uninvolved, active and cooperative DSS: Decision support systems are connected to making and passing on IT-based systems to help decision methodology [1,2]. Since the 1970s, examiners have focused on making PC development based game plans that can be used to support complex fundamental administration and basic reasoning conditions [3]. The domains of the data systems and progressions have grown basically in the latest decades. ...
... The most common technology used to deploy the DSS is a web or client-server. Examples: chats and instant messaging software, online collaboration and net-meeting systems [3]. II.I. ...
In the field of agriculture systems, the collection of automated data, as well as the development of technological innovations like intelligent crop cultivation systems and new patterns in Decision Support Systems (DSS), has ascended to new applications and techniques for existing decision support innovations. Today, agriculture needs a versatile system that responds and adjusts to the continually changing agricultural prices, weather patterns and water dam levels. The typical decision support systems depend on the weather patterns; that isn't sufficient. We need more precision for better output. well as stakeholders to take their decisions near to correct. In this review paper we are going to investigate how the previous DSS is working in the current situation. DSS consolidate human aptitudes with the capacities of PCs to give effective administration of information, detailing the investigation, demonstrating, and arranging issues. DSS gives a differentiation between organized, semi-organized, and unstructured information. Specifically, a DSS lessens the amount of information to a top-notch organized sum. Because of this, predictions are made to help the Crop Cultivation Process. Additionally, the objective of this review is to dodge issues inside the development procedure even before ranchers furrow for Kharif and Rabbi. This paper gives a review of the state-of-the-workmanship literature on DSS and portrays current procedures of significant DSS applications in present conditions.
... Centralized: This type of agent works in a centralized manner in which one or two agents have the ability to take the role of the coordination or communications can occur between the agents themselves [13]. This type of agent consists of two main strategies: ...
... Decentralized: This type of agent works separately without any kind of coordination [13]. Usually, this type of agent is used for competitions where the aim is to identify the best solution or most efficient mechanism. ...
