Cooperation Between Smart Manufacturing Scheduling Systems and Energy Providers: A Multi-agent Perspective

Author(s):  
Maroua Nouiri ◽  
Damien Trentesaux ◽  
Abdelghani Bekrar ◽  
Adriana Giret ◽  
Miguel A. Salido
2021 ◽  
Vol 61 ◽  
pp. 265-287
Author(s):  
Julio C. Serrano-Ruiz ◽  
Josefa Mula ◽  
Raúl Poler

Author(s):  
Chun Wang ◽  
Weiming Shen ◽  
Hamada Ghenniwa

This paper investigates issues in the application of auctions as negotiation mechanisms to agent based manufacturing scheduling. We model the negotiation environments that agents encounter as inter-enterprise environment and intra-enterprise environment. A formulation of intra-enterprise scheduling economy is presented. We proved that at price equilibrium, the solution computed by the agents in the economy is a Pareto optimal. AS our first attempt, we formally formulate automated auction configuration as an optimization problem. By solving the problem adaptive negotiation in multi-agent systems can be achieved. In addition to the theoretical models, we discussed various types of auction mechanisms and their applications to agent based manufacturing scheduling. Heuristics and procedures are proposed for solving the automated auction configuration problem. To validate the analysis and proposed approaches, as a case study, we apply the automated auction configuration heuristics and the procedure to an agent based shop floor scheduling environment. Experimental results show that the auction protocol selected by the proposed heuristics provides correct system functionalities. In addition, we compared the selected mechanism with other candidate mechanisms. We found that the selected one performs better in terms of reducing communication cost and improving solution quality.


Author(s):  
Zhaojun Qin ◽  
Yuqian Lu

Abstract Mass personalization is arriving. It requires smart manufacturing capabilities to responsively produce personalized products with dynamic batch sizes in a cost-effective way. However, current manufacturing system automation technologies are rigid and inflexible in response to ever-changing production demands and unforeseen internal system status. A manufacturing system is required to address these challenges with adaptive self-organization capabilities to achieve flexible, autonomous, and error-tolerant production. Within the context, the concept of Self-Organizing Manufacturing Network has been proposed to achieve mass personalization production. In this paper, we propose a four-layer system-level control architecture for Self-Organizing Manufacturing Network. This architecture has additional two layers (namely, Semantic Layer and Decision-Making Layer) on Physical Layer and Cyber Layer to improve communication, interaction, and distributed collaborative system automation. In this architecture, manufacturing resources are encapsulated as Semantic Twins to make interoperable peer communication in the manufacturing network. The interaction of Semantic Twins consolidates system status and manufacturing environment that enables multi-agent control technologies to optimize manufacturing operations and system performance.


2021 ◽  
Vol 13 (2) ◽  
pp. 157-180
Author(s):  
Richárd Beregi ◽  
Gianfranco Pedone ◽  
Davy Preuveneers

Smart manufacturing is a challenging trend being fostered by the Industry 4.0 paradigm. In this scenario Multi-Agent Systems (MAS) are particularly elected for modeling such types of intelligent, decentralised processes, thanks to their autonomy in pursuing collective and cooperative goals. From a human perspective, however, increasing the confidence in trustworthiness of MAS based Cyber-physical Production Systems (CPPS) remains a significant challenge. Manufacturing services must comply with strong requirements in terms of reliability, robustness and latency, and solution providers are expected to ensure that agents will operate within certain boundaries of the production, and mitigate unattended behaviours during the execution of manufacturing activities. To address this concern, a Manufacturing Agent Accountability Framework is proposed, a dynamic authorization framework that defines and enforces boundaries in which agents are freely permitted to exploit their intelligence to reach individual and collective objectives. The expected behaviour of agents is to adhere to CPPS workflows which implicitly define acceptable regions of behaviours and production feasibility. Core contributions of the proposed framework are: a manufacturing accountability model, the representation of the Leaf Diagrams for the governance of agent behavioural autonomy, and an ontology of declarative policies for the identification and avoidance of ill-intentioned behaviours in the execution of CPPS services. We outline the application of this enhanced trustworthiness framework to an agent-based manufacturing use-case for the production of a variety of hand tools.


2020 ◽  
Author(s):  
Dhouha Ben Noureddine ◽  
Moez Krichen ◽  
Seifeddine Mechti ◽  
Tarik Nahhal ◽  
Wilfried Yves Hamilton Adoni

Internet of Things (IoT) is composed of many IoT devices connected throughout the Internet, that collect and share information to represent the environment. IoT is currently restructuring the actual manufacturing to smart manufacturing. However, inherent characteristics of IoT lead to a number of titanic challenges such as decentralization, weak interoperability, security, etc. The artificial intelligence provides opportunities to address IoT’s challenges, e.g the agent technology. This paper presents first an overview of ML and discusses some related work. Then, we briefly present the classic IoT architecture. Then we introduce our proposed Intelligent IoT (IIoT) architecture. We next concentrate on introducing the approach using multi-agent DRL in IIoT. Finally, in this promising field, we outline the open directions of future work.


2019 ◽  
Vol 15 (7) ◽  
pp. 4276-4284 ◽  
Author(s):  
Chun-Cheng Lin ◽  
Der-Jiunn Deng ◽  
Yen-Ling Chih ◽  
Hsin-Ting Chiu

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