An adaptive and upgradable agent-based system for coordinated product development and manufacture

Last decade witnessed the growth of globally decentralized product development and manufacture. The complexity of products created in such a distributed environment often requires close collaborations among a number of design and production partners. In this paper, an agent-based system for coordinated product development and manufacture is presented. The system consists of two categories of agents. The first category consists solely of a managing agent (MA) and the second consists of many functional agents such as the manufacturability evaluation agent, resource agent, process-planning agent, scheduling agent, etc. Each agent represents a domain expert and it can be installed in an individual computer. All the agents could be dispersed in geographically different regions and communicate with one another through the Internet. With each functional agent having specific functionality, the MA is the center of the intelligent system. It assists the work of other agents and enables them to collaborate closely with one another. With such a system in place, a product life cycle can be optimized from product design to final manufacturing as all the procedures are considered comprehensively and integrally, and each procedure is performed in a way as to ease and expedite the work of other agents. An agent language, which includes many specifically defined performatives, is defined. Each agent can perform its task intelligently by interpreting the commands (performatives) from other agents. Moreover, with the consideration of possible future methodology changes, the internal structure of each functional agent is modularized into several components. Such an architecture ensures that the system is flexible, adaptive and upgradable.     

An agent-oriented approach to resolve scheduling optimization in intelligent manufacturing

Agent technology is considered as a promising approach for developing optimizing process plans in intelligent manufacturing. As a bridge between computer aided design (CAD) and computer aided manufacturing (CAM), the computer aided scheduling optimization (CASO) plays an important role in the computer integrated manufacturing (CIM) environment. In order to develop a multi-agent-based scheduling system for intelligent manufacturing, it is necessary to build various functional agents for all the resources and an agent manager to improve the scheduling agility. Identifying the shortcomings of traditional scheduling algorithm in intelligent manufacturing, the architecture of intelligent manufacturing system based on multi-agent is put forward, among which agent represents the basic processing entity. Multi-agent-based scheduling is a new intelligent scheduling method based on the theories of multi-agent system (MAS) and distributed artificial intelligence (DAI). It views intelligent manufacturing as composed of a set of intelligent agents, who are responsible for one or more activities and interacting with other related agents in planning and executing their responsibilities. In this paper, the proposed architecture consists of various autonomous agents that are capable of communicating with each other and making decisions based on their knowledge. The architecture of intelligent manufacturing, the scheduling optimization algorithm, the negotiation processes and protocols among the agents are described in detail. A prototype system is built and validated in an illustrative example, which demonstrates the feasibility of the proposed approach. The experiments prove that the implementation of multi-agent technology in intelligent manufacturing system makes the operations much more flexible, economical and energy efficient.     

Multi-agent Mediator architecture for distributed manufacturing

A generic Mediator architecture for distributed task planning and coordination has been developed using multi-agent paradigms. In this approach, agents function autonomously as independent computing processes, and dynamic virtual clusters coordinate the agent's activities and decision making. This coordination involves dynamically created coordination agents and resource agents concurrently. The Mediator architecture contains three levels of these coordination agents: the template mediator, the data-agent manager, and the active mediator. The template mediator is the top-level global coordinator. This agent contains both the templates and the cloning mechanism to create the successively lower-level agents. Task plans are decomposed successively into subtasks, which are allocated to dynamically created agent clusters coordinated through data-agent managers and active mediators. Coordination of agent activity takes place both among the clusters and within each cluster. The system dynamically adapts to evolving manufacturing tasks, with virtual agent clusters being created as needed, and destroyed when their tasks are completed. The mediator architecture and related mechanisms are demonstrated using an intelligent manufacturing scheduling application. Both the machines and the parts involved in this production system are considered as intelligent agents. These agents use a common language protocol based on the Knowledge Query Manipulation Language (KQML). The generic Mediator approach can be used for other distributed organizational systems beyond the intelligent manufacturing application it was originally developed for.     

Preliminary design and manufacturing planning integration using web-based intelligent agents

Software agents have been increasingly used in the product and process development in industry over the past years due to the rapid evolvement of the Internet technology. This paper describes agents for the integration of conceptual design and process planning. Agents provide mechanisms to interact with each other. This mechanism is important since both of those processes involve negotiations for optimization. A set of design and planning software agents has been developed. These agents are used in a computer-based collaborative environment, called a multi-agent platform. The main purpose of developing such a platform is to support product preliminary design, optimize product form and structure, and reduce the manufacturing cost in the early design stage. The agents on the platform have access to a knowledge base that contains design and planning rules. These rules are derived from an analysis of design factors that influence process and resource planning, such as product material, form, shape complexity, features, dimension, tolerance, surface condition, production volume, and production rate. These rules are used by process planning agents to provide process planners with information regarding selecting preliminary manufacturing processes, determining manufacturing resources, and constructing feedback information to product designers. Additionally, the agents communicate with WEB servers, and they are accessible by users through Internet browsers. During performing design and planning tasks, agents access the data pertinent to design and manufacturing processes by the programming interfaces of existing computer-aided design (CAD) and manufacturing system. The agents are supported by a developed prototype agent platform. The agents and the platform enable the information exchange among agents, based on a previously developed integrated design and manufacturing process object model.     

The Fabricare scheduling prototype suite: Agent interaction and knowledge base

This work presents a prototype system (named Fabricare) for the scheduling of manufacturing orders, based on holonic manufacturing systems using extended logic programming. The system is composed of several holons that cooperate among themselves using an extension to the contract net protocol named contract net with constraint propagation protocol. This protocol enables explicit cooperation among service providers that use constraint propagation in order to guarantee the precedence relationships between the different operations participating in the same task. Some precautions have been taken to avoid conflicts and combinatorial explosion. The complexity analysis of the protocol has been performed. The main agents in this system are task and resource agents; the knowledge bases of these agents are presented. Also, a notation for representation of incomplete information on an agent's knowledge base is presented.     

敏捷虚拟企业中基于CORBA的多级代理建模

敏捷制造虚拟企业（Agile Virtual Enterprise,AVE）作为一种新型的制造模式正在逐渐兴起。将CORBA技术应用到制造业中，根据制造业自身的特点，提出了分布式制造系统的多级代理模型。在该模型中，代理表示虚拟组织中某一功能部件或任务执行点；工作流表示代理之间相互依赖的关系；事件触发机制实现代理之间的互操作。由此，虚拟组织的运作和产品的协同开发就有了可靠的实现依据 。     

The model-based product agent: A control oriented architecture for intelligent products in multi-agent manufacturing systems

The multi-agent control strategy has been previously shown to improve the flexibility of complex, dynamic manufacturing systems. One key component of this strategy is the product agent. The product agent is responsible for autonomously guiding a physical part in the manufacturing system based on its production goals. Though the product agent has been described in previous works, a fully developed software architecture for the product agent that uses a model-based optimization approach has not been proposed. In this work, a product agent architecture with the capabilities to explore the local environment, plan and schedule events based on its knowledge, and request desired actions from the resources in the system is presented and tested.     

An object-oriented knowledge based Petri net approach to intelligent integration of design and assembly planning

Artificial intelligence can play an important role in the reduction of manufacturing costs and the enhancement of production efficiency and product quality. In order to assist designers in the early stages of a product development this paper develops an intelligent methodology for integration of design and assembly planning processes, including product design, assembly evaluation and redesign, assembly process planning, design of assembly system and assembly simulation, subjected to both econo-technical and ergonomic evaluations. A new unified class of object-oriented knowledge based Petri nets called OOKPNs, incorporating knowledge based expert systems and fuzzy logic into ordinary place–transition Petri nets, is defined and used for the representation and modeling of the distributed design processes. A prototype intelligent integrated design and assembly planning system (IIDAP) is implemented through distributed blackboard structure with concurrent integration of multiple cooperative knowledge sources and software. It consists essentially of the networked agents and the meta-system, each of which is a knowledge Petri net system with the capabilities of problem solving, learning and conflict resolution, and can be obtained through the inheritance, polymorphism and dynamic binding of instances of OOKPNs. In IIDAP system, both C/C++ language and COOL (CLIPS object-oriented language) are used to incorporate a Petri net tool, a geometric modeling and design tool, a planner and simulator and an evaluation tool. By use of this system, product design and assembly planning can be carried out simultaneously and intelligently in an entirely computer-aided concurrent design and assembly planning system. The design of manufacturable, cost-effective, usable products can therefore be achieved rapidly and flexibly. The developed methodology and system have been successfully applied to assembly design and planning of a micro switch.     

Semantic Web based innovative design knowledge modeling for collaborative design

This paper describes a study about how to use the Semantic Web technologies for innovative design knowledge modeling in a multi-agent distributed design environment. Semantic Web based knowledge modeling for innovative design is proposed as prelude to the meaningful agent communication and knowledge reuse for collaborative work among multidisciplinary organizations. A model for innovative design is proposed at first, based on which a knowledge schema is brought forward. For sharing the design knowledge among an internet-based or distributed work team, even globally, A RDF-based knowledge model is presented to realize its representation on Semantic Web. A Semantic Web based repository for innovative design and its API for topper Semantic Web applications have been also constructed. The proposed knowledge modeling extends traditional product modeling with capabilities of innovative design, knowledge sharing and distributed problem solving, and is employed as a content language within the messages in the proposed multi-agent system architecture. The proposed approach is viewed as a promising knowledge management method that facilitates the implementation of computer supported cooperative work in innovative design of Semantic Web applications.     

A computational model for distributed knowledge systems with learning mechanisms

This paper addresses the issues of machine learning in distributed knowledge systems, which will consist of distributed software agents with problem solving, communication and learning functions. To develop such systems, we must analyze the roles of problem-solving and communication capabilities among knowledge systems. To facilitate the analyses, we propose a computational model: LPC. The model consists of a set of agents with (a) a knowledge base for learned concepts, (b) a knowledge base for problem solving, (c) prolog-based inference mechanisms and (d) a set of beliefs on the reliability of the other agents. Each agent can improve its own problem-solving capabilities by deductive learning from the given problems, by memory-based learning from communications between the agents and by reinforcement learning from the reliability of communications between the other agents. An experimental system of the model has been implemented in Prolog language on a Window-based personal computer. Intensive experiments have been carried out to examine the feasibility of the machine learning mechanisms of agents for problem-solving and communication capabilities. The experimental results have shown that the multiagent system improves the performance of the whole system in problem solving, when each agent has a higher learning ability or when an agent with a very high ability for problem solving joins the organization to cooperate with the other agents in problem solving. These results suggest that the proposed model is useful in analyzing the learning mechanisms applicable to distributed knowledge systems.     

A multi-agent approach to process planning and fabrication in distributed manufacturing

In the paper a multi-agent approach to the development of a distributed manufacturing architecture is presented. An essential building block introduced here is the virtual work system (VWS) which represents a manufacturing work system in the information space. The VWS is structured as an autonomous agent and is a constituent entity of an agent network. In the network dynamic clusters of cooperating agents are solving manufacturing tasks. A machining work system and its VWS is demonstrated in a case study. Its role in the agent communication network is discussed in a process planning and fabrication domain.     

Scientific and structural base of manufacturing

Science comes from Latin scientia meaning knowledge. Science is difficult to define, but we can obtain an understanding of what we mean. Knowledge, however, is wider in scope than what we generally define as science. Engineering, of which manufacturing is a part, requires creativity, fantasy, scope, and imagination as well as scientific knowledge. These elements are also needed in the scientific work itself. Scientific quality and language to tell the result must be considered separately from each other. Scientific quality means true and accurate knowledge, and the language must be adapted to the problem and to the receiver of the scientific result. Axiomatic decision-rules are being proposed as a scientific method to help in sorting out good solutions in engineering. The manufacturing system can be described and analysed as three main production systems: the manufacturing production system (MPS), the data production system (DPS), and the innovation production system (IPS).     

Organization self-design of distributed production systems

The authors introduce two reorganization primitives, composition and decomposition, which change the population of agents and the distribution of knowledge in an organization. To create these primitives, they formalize organizational knowledge, which represents knowledge of potential and necessary interactions among agents in an organization. The authors develop computational organizational self-design (OSD) techniques for agents with architectures based on production systems to take advantage of the well-understood body of theory and practice. They first extend parallel production systems, where global control exists, into distributed production systems, where problems are solved by a society of agents using distributed control. Then they introduce OSD into distributed production systems to provide adaptive work allocation. Simulation results demonstrate the effectiveness of the approach in adapting to changing environmental demands. The approach affects production system design and improves the ability of build production systems that can adapt to changing real-time constraints     

A collaborative and integrated platform to support distributed manufacturing system using a service-oriented approach based on cloud computing paradigm

Today's manufacturing enterprises struggle to adopt cost-effective manufacturing systems. Overview of the recent manufacturing enterprises shows that successful global manufacturing enterprises have distributed their manufacturing capabilities over the globe. The successes of global manufacturing enterprises depend upon the entire worldwide integration of their product development processes and manufacturing operations that are distributed over the globe. Distributed manufacturing agents' collaboration and manufacturing data integrity play a major role in global manufacturing enterprises' success. There are number of works, conducted to enable the distributed manufacturing agents to collaborate with each other. To achieve the manufacturing data integrity through manufacturing processes, numbers of solutions have been proposed which one of the successful solutions is to use ISO 10303 (STEP) standard. However, adopting this standard one can recognize antonym effects of integration and collaboration approaches that weaken both integration and collaboration capabilities of manufacturing agents. In our latest work, we had developed an integrated and collaborative manufacturing platform named LAYMOD. Albeit the platform in question was through enough to be applied in various collaborative and integrated CAx systems, its embedded structure hampers its application for collaboration in distributed manufacturing systems. To achieve an integrated and collaborative platform for distributed manufacturing agents, this paper proposes a service-oriented approach. This approach is originated from cloud computing paradigm known as one of the technologies which enables a major transformation in manufacturing industry. Also, to maintain the product data integration based on the STEP standard, a new service-oriented approach is proposed. This approach is in parallel to the new capability of the STEP standard for supporting XML data structures. The result is a new platform named XMLAYMOD. XMLAYMOD is able to support distributed manufacturing collaboration and data integration based on the STEP standard. The different aspects of this platform to fulfill the requirements of distributed collaboration and also to overcome the lacks of the STEP standard are discussed through a brief case study.     

基于智能多代理的工作流资源分配

提出了一种基于智能多代理实现分布式工作流资源分配的方法。该方法采用KQML语言来设计资源分配代理和工作流引擎之间面向知识交换的通信协议,并且由Router提供消息存储和转发机制。工作流资源分配代理与工作流管理系统的其他代理程序通过KQML消息交流知识,从而达到在分布式、异构环境下的互操作。     

Autonomous Agents that Learn to Better Coordinate

A fundamental difficulty faced by groups of agents that work together is how to efficiently coordinate their efforts. This coordination problem is both ubiquitous and challenging, especially in environments where autonomous agents are motivated by personal goals.Previous AI research on coordination has developed techniques that allow agents to act efficiently from the outset based on common built-in knowledge or to learn to act efficiently when the agents are not autonomous. The research described in this paper builds on those efforts by developing distributed learning techniques that improve coordination among autonomous agents.The techniques presented in this work encompass agents who are heterogeneous, who do not have complete built-in common knowledge, and who cannot coordinate solely by observation. An agent learns from her experiences so that her future behavior more accurately reflects what works (or does not work) in practice. Each agent stores past successes (both planned and unplanned) in their individual casebase. Entries in a casebase are represented as coordinated procedures and are organized around learned expectations about other agents.It is a novel approach for individuals to learn procedures as a means for the group to coordinate more efficiently. Empirical results validate the utility of this approach. Whether or not the agents have initial expertise in solving coordination problems, the distributed learning of the individual agents significantly improves the overall performance of the community, including reducing planning and communication costs.     

The design of a JADE-based autonomous workflow management system for collaborative SoC design

Given a fast changing electronics goods marketplace, designers of integrated circuits and components need to be more competitive, efficient, flexible, and use collaborative workflow to reduce time-to-market and a project’s life cycle. In recent years, agent-based workflow management systems (WfMS) have been widely used to monitor and control business design processes. In this paper, intelligent agents are applied to the collaborative system-on-chip (SoC) design environment. The proposed JADE-based autonomous workflow management system (JAWMS) uses a workflow coordination mechanism and an agent integration mechanism to enable the analysis, management and interaction of automated design processes. The workflow coordination mechanism uses five domain specific agents to perform the workflow enactment services and a generic agent to control the system flow logic. The system kernel of JAWMS follows the specifications of the workflow reference model provided by the workflow management coalition (WfMC). The agent integration mechanism supports an agent to interact with other JADE-based agent platforms and to coordinate and monitor workflow coordination messages. All agents are written in the Java language using the JADE platform and work together to perform flexible, adaptive and dynamic design tasks in an autonomous and collaborative way. JAWMS facilitates SoC design and team interaction in a collaborative but distributed product development environment.     

一种面向Agent的设计过程模型

本文提出了一种面向ａｇｅｎｔ的设计过程模型，该模型参加设计过程的实体为ａｇｅｎｔ，通过ａｇｅｎｔ有组织的协同工作描述产品设计过程。该模型的构造符合客观世界人们协作完成任务的工作方式，因此，依此模型构造的支撑容易适应现实世界