Information and communication technology is undergoing rapid development, and many disruptive technologies, such as cloud computing, Internet of Things, big data, and artificial intelligence, have emerged. These technologies are permeating the manufacturing industry and enable the fusion of physical and virtual worlds through cyber-physical systems (CPS), which mark the advent of the fourth stage of industrial production (i.e., Industry 4.0). The widespread application of CPS in manufacturing environments renders manufacturing systems increasingly smart. To advance research on the implementation of Industry 4.0, this study examines smart manufacturing systems for Industry 4.0. First, a conceptual framework of smart manufacturing systems for Industry 4.0 is presented. Second, demonstrative scenarios that pertain to smart design, smart machining, smart control, smart monitoring, and smart scheduling, are presented. Key technologies and their possible applications to Industry 4.0 smart manufacturing systems are reviewed based on these demonstrative scenarios. Finally, challenges and future perspectives are identified and discussed.

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Smart manufacturing systems for Industry 4.0: Conceptual framework, scenarios, and future perspectives

Agent based models (ABM) have been recently applied to solve optimization problems whose domains present several inter-related components in a distributed and heterogeneous environment. In this work we illustrate the state of the art related to the use and to the application of ABM as optimization technique, given their peculiarity in dealing with the representation and the simulation of complex systems. After a description of the approach and a comparison with classical heuristics, an extensive review aimed at evaluating the impact of these methodologies in the Operational Research/Management Science literature is provided.

Applications of agent-based models for optimization problems: A literature review

https://isiarticles.com/bundles/Article/pre/pdf/27039.pdf

Integrated process planning and scheduling by an agent-based ant colony optimization

Traditionally, process planning and scheduling were performed sequentially, where scheduling was done after process plans had been generated. Considering the fact that these two functions are usually complementary, it is necessary to integrate them more tightly so that the performance of a manufacturing system can be improved greatly. In this paper, an agent-based approach has been developed to facilitate the integration of these two functions. In the approach, the two functions are carried out simultaneously, and an optimization agent based on an evolutionary algorithm is used to manage the interactions and communications between agents to enable proper decisions to be made. To verify the feasibility and performance of the proposed approach, experimental studies have been conducted and comparisons have been made between this approach and some previous works. The experimental results show the proposed approach has achieved significant improvement.

An agent-based approach for integrated process planning and scheduling

This paper presents a hybrid-based multi-agent system (MAS) for integrating process planning with scheduling/rescheduling in job shops or similar kinds of flexible manufacturing environments. The approach is called Online Hybrid Agent-based Negotiation (oHAN). It employs the affected operations rescheduling approach to reschedule the operations affected directly or indirectly by the disruptions. The proposed MAS architecture comprises local agents, which are the part and machine agents, and a supervisor agent. The local agents detect the production disturbances and reschedule the affected operations via decentralized negotiations. A comprehensive set of process plan flexibilities including flexible routings and alternative machines is considered during rescheduling. The supervisor agent coordinates and monitors the rescheduling process in order to ensure the observance of a global rescheduling objective. An online hybrid contract-net negotiation protocol (oHCNP) has been established to control the interac...

Integrated process planning and scheduling/rescheduling—an agent-based approach

This paper is on the development of an agent-based approach for the dynamic integration of the process planning and scheduling functions. In consideration of the alternative processes and alternative machines for the production of each part, the actual selection of the schedule and allocation of manufacturing resources is achieved through negotiation among the part and machine agents which represent the parts and manufacturing resources, respectively. The agents are to negotiate on a fictitious cost with the adoption of a currency function. Two MAS architectures are evaluated in this paper. One is a simple MAS architecture comprises part agents and machine agents only; the other one involves the addition of a supervisor agent to establish a hybrid-based MAS architecture. A hybrid contract net protocol is developed in the paper to support both types of MAS architectures. This new negotiation protocol enables multi-task many-to-many negotiations, it also incorporates global control into the decentralized negotiation. Simulation runs are conducted to compare the performance of the proposed MAS-based IPPS approaches and that of an evolutionary algorithm. It also shows that the hybrid-based MAS, with the introduction of supervisory control, is able to provide integrated process plan and job shop scheduling solutions with a better global performance.

C. W. Leung

Papers

Dynamic shopfloor scheduling in multi-agent manufacturing systems