Modeling of service agents for simulation in cloud manufacturing

doi:10.1016/j.rcim.2019.101910

Robotics and Computer-Integrated Manufacturing

Volume 64, August 2020, 101910

https://doi.org/10.1016/j.rcim.2019.101910 Get rights and content

Highlights

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This manuscript presents an encapsulation of service agent. Services encapsulated by service agent will have many advantages such as autonomy, independence and adaptability.
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This manuscript an architecture of communication of service agents.
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This manuscript introduces the service agent modeling for cloud manufacturing simulation platform, and introduces the functions and properties of each module of service agent model and service center model.

Abstract

Cloud Manufacturing is a paradigm of intelligent manufacturing system with information opening, resource sharing, and diversified services. In order to research the issues in cloud manufacturing, such as behaviors of a service provider and service consumer, matching of service, dynamic change of resource, verification of business model, scheduling of service and evolution of service network, cloud manufacturing simulation platform is widely applied. However, the method of simulation-based on agent or rule lacks to represent the characteristics of service in cloud manufacturing. This paper presents a method of integrating the service and agent to form a service agent. The service agent integrates intelligence to the service in cloud manufacturing so that it can trade autonomously and adapt itself to the environment. A simulation case of production takt is presented in the rear of the paper. It shows that the conceptual model of the service agent and the communication architecture of the service agent can build the service agent model, which can support the cloud manufacturing simulation platform.

Introduction

With the deepening of cloud-related manufacturing research, many new manufacturing models and solutions are sprung up around the world [1]. Cloud manufacturing is a typical service-oriented manufacturing paradigm. In a cloud manufacturing environment, manufacturing resource supports consumers by the form of service. Service platform is used as a core in cloud manufacturing system, provides the capability of services, such as integration, sharing and distribution, and enables the service’s interaction, collaboration, composition, trading freely. The concept of service-oriented architecture has a great effect on the development of the technologies of distributed system and integration of software system. A service is defined as a network unit, which is independent, opening and non-related with systems. The service is established in a distributed environment, which has advantages in flexibility, reusability and sustainability [2], [3], [4]. As a paradigm of intelligent manufacturing system, cloud manufacturing has the characteristics includes information opening, resource sharing and diversity of service. A cloud manufacturing platform can provide consumers with manufacturing services by manufacturing resource access from providers. In order to research issues such as verification of business model, schedule of service, evolution of service network, architectures of cloud manufacturing simulation are sprung up [5], [6].

Developing of agent has accelerated the relevant research in the manufacturing field. The agent becomes an important part of cloud manufacturing[7]. Most of functions in a cloud manufacturing simulation platform are used to simulate the behavior of services. Therefore, an intelligent simulation platform should combine the concept of agent with the concept of service. Using functions and characteristics of the agent, manufacturing services are upgraded and encapsulated to form a service agent. The service agent enables service in a distributed environment to better understand the requirement of consumers and choice more appropriate behaviors. In cloud manufacturing simulation platform, the service agent can simulate the running of service and conduct the cooperation and interaction among the services autonomously.

In this paper, a concept of service-agent-based modeling for cloud manufacturing simulation is presented, which includes communication of service agent, modeling of virtualized resource, modeling of manufacturing service, modeling of the service agent, modeling of service center and modeling of transaction. Using the modeling methods of service agents, many kinds of business modes can be simulated in the cloud manufacturing simulation environment. Thus, researchers can study running characteristics of elements in the cloud manufacturing environment, methods of manufacturing service composition, methods of manufacturing resource optimization and prediction of business behavior.

The contributions of this paper are as follows:

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Through modeling of resources, services and service agents, this work has a very specific reference and helps for related researches on simulation of cloud manufacturing.
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Through building of service agent communication architecture, problems of service agent communication in a simulation environment are solved.
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Through application of clock, random number and other parameters, difference and randomness of service agent can be simulated.

The remainder of this paper is organized as follows. First, the related works of modeling and service agent in cloud manufacturing are summarized in Section 2. Second, concept and conceptual model of service agent are presented in Section 3. In Section 4a communication architecture of the service agent is described. Fourth, service-agent-based methods of modeling for cloud manufacturing simulation are presented in Section 5. Section 6, a simulation case is provided to show the methods of modeling above. And the simulation process is analyzed through the monitoring of the service center. Finally, Section 7 concludes the paper.

Section snippets

Literature review

In artificial intelligence field, agent is an autonomous entity which can observe and respond to the environment by sensors and actuators. An agent is a rational entity that can interact with the environment and perform a task to achieve some specific purpose. In addition, it can achieve its goals by rules, learning or using knowledge. So, an agent can be used as simple or as complex according to situation. Following the emergence of object-oriented concept, many researchers believe that agent

Conceptual modeling of service agent

Based on the simple agent model, this section proposes a modeling method for service agents. This method extends the BDI model of a single agent at the semantic level, focusing on the behaviors of agent perception, planning, action, coordination and collaboration. Through this method, a model of the instance service is established. This forms a service agent with intelligent features. This paper establishes corresponding functional modules and interfaces for the model, and implements the

Communication architecture of service agent

The service agent which is encapsulated by the agent has characteristic of the ability to communicate independently. Therefore, communication architecture is an important technology of service agent. In order to realize the independent communication of service agent, this research builds a communication architecture of service agent, in Fig. 3.

As shown in Fig. 3. The communication architecture of the service agent is divided into four layers, Includes the resource layer, service layer, service

Service-agent-based modeling for cloud manufacturing simulation

Service agent gives the service intelligent and autonomy, which can cooperate actively. In the cloud manufacturing environment, due to the complexity and variety of manufacturing resources, and services are more diverse, and descriptions of services are more complex. In the cloud manufacturing application platform, service agents can help enterprises find partners faster with more accurately. But In the cloud manufacturing simulation platform, the service agent can simulate the behavior of

Case study

In the previous work, we built an agent-based cloud manufacturing simulation platform [6]. The platform enables the functions to include simulation, data storage, visual output and so on. In this paper, we improve the system and clarify the encapsulation of resources, services and service agents, especially the architecture of message. After improvement, the conceptual model of cloud manufacturing simulation platform is shown in Fig. 9, which consists of three types of roles, three types of

Conclusions

Services evolved into service agents through encapsulation of agent and have many characteristics of intelligence such as autonomy, independence, and adaptability. Service agents can proactively self-assemble and self-schedule according to their needs, thus reducing the burden on the service registry. In a system without a central or weak center, the advantages of the service agent can be more reflected, and components can be formed quickly and efficiently to meet the needs of demanders. There

Declaration of Competing Interest

We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome.

CRediT authorship contribution statement

Chun Zhao: Software, Data curation, Writing - original draft. Xiao Luo: Conceptualization, Supervision. Lin Zhang: Writing - review & editing.

Acknowledgment

This work is supported by the National Program on Key Basic Research Project of China (Grant No. 2018YFB1701602), the National Natural Science Foundation of China (Grant No. 61374199), the National High-tech Research and Development Program of China under (Grant No. 2015AA042101).

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Modeling of service agents for simulation in cloud manufacturing

Highlights

Abstract

Introduction

Section snippets

Literature review

Conceptual modeling of service agent

Communication architecture of service agent

Service-agent-based modeling for cloud manufacturing simulation

Case study

Conclusions

Declaration of Competing Interest

CRediT authorship contribution statement

Acknowledgment

Robot. Comput. Integr. Manuf.

Int. J. Model. Simul.Sci. Comput.

Auton. Agent Multi Agent Syst.

Robot. Comput. Integr. Manuf.

IEEE Access

Procedia Manuf.

Int. J. Prod. Res.

Robot. Comput. Integr. Manuf.

Patterns: Service-Oriented Architecture and Web Services

Web Services

Web Services

Service oriented computing-principle and application

Qing Hua University publisher

SDMSIm: a manufacturing service supply demand matching simulator under cloud environment

Robot. Comput. Integr. Manuf.

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