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.     

Agent-based distributed manufacturing control: A state-of-the-art survey

Manufacturing has faced significant changes during the last years, namely the move from a local economy towards a global and competitive economy, with markets demanding for highly customized products of high quality at lower costs, and with short life cycles. In this environment, manufacturing enterprises, to remain competitive, must respond closely to customer demands by improving their flexibility and agility, while maintaining their productivity and quality. Dynamic response to emergence is becoming a key issue in manufacturing field because traditional manufacturing control systems are built upon rigid control architectures, which cannot respond efficiently and effectively to dynamic change. In these circumstances, the current challenge is to develop manufacturing control systems that exhibit intelligence, robustness and adaptation to the environment changes and disturbances. The introduction of multi-agent systems and holonic manufacturing systems paradigms addresses these requirements, bringing the advantages of modularity, decentralization, autonomy, scalability and re-usability. This paper surveys the literature in manufacturing control systems using distributed artificial intelligence techniques, namely multi-agent systems and holonic manufacturing systems principles. The paper also discusses the reasons for the weak adoption of these approaches by industry and points out the challenges and research opportunities for the future.     

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.     

An intelligent simulation environment for manufacturing systems

The manufacturing field is an area where the application of simulation is an essential tool for validating methods and architectures before applying them on the factory floor. Despite the fact that there are a great number of simulation tools, most of them do not take into account the specific requirements of the “new manufacturing era” such as distributed organization, interoperability, cooperation, scalability, fault tolerance and agility. On the other hand, Multiagent System technology has demonstrated its utility in manufacturing system modeling and implementation. Agenthood features such as proactivity, reactivity, and sociability may also be useful for associating them with the specific simulation needs of the new changing requirements for manufacturing systems. In this paper, an Agent-supported Simulation Environment for intelligent manufacturing systems is presented. The different roles that are played by the agents of the simulation environment are defined taking into account the specific dynamic features in manufacturing simulation and the requirements of the new manufacturing era. Moreover, the interaction and cooperation scenarios among these agents are specified to facilitate manufacturing simulation in an appropriate and flexible way. A detailed evaluation study, with regards to the new manufacturing era requirements, demonstrates the advantages of the proposed approach over current state-of-the-art proposals.     

Design choices for agent-based control of AGVs in the dough making process

We consider a multi-agent system for the logistics control of Automatic Guided Vehicles that are used in the dough making process at an industrial bakery. Here, logistics control refers to constructing robust schedules for transportation jobs. We discuss how alternative MAS designs can be developed and compared. Qualitative design guidelines turn out to be insufficient to select the best agent architecture. Therefore, we also use simulation to support decision making, where we use real-life data from the bakery to evaluate alternative designs. We show that depending on the degree of dynamism and objectives of the bakery, different architectures are preferred.     

A general framework of a Reference Model for Intelligent Integrated Manufacturing Systems (REMIMS)

Today's highly competitive business environment forces the managers to continuously make the best decisions in the shortest possible time. The ability to provide concurrency among manufacturing functions is a critical need for modern organizations as, especially, distributed environment requires synchronization of manufacturing functions. Moreover, manufacturing companies need to have strong capability of adaptation (agility) mainly because of the dynamic relationships that must be established between manufacturing units. To achieve these, there is a need for an integrated manufacturing system that will handle all interactions and interrelationships which will then be affected by the changes and create maximum gain under limited resources. In order to create and effectively manage such an integrated manufacturing system there is a need for a reference model. In this paper, such a reference model called REference Model for intelligent Integrated Manufacturing System (REMIMS) is introduced. REMIMS has hierarchical architecture with several agents responsible for different manufacturing functions. To facilitate REMIMS and allow interaction among the agents to share their knowledge, a specific knowledge exchange protocol in a knowledge network is being developed.     

Enhancing the performance of an agent-based manufacturing system through learning and forecasting

Agent-based technology has been identified as an important approach for developing next generation manufacturing systems. One of the key techniques needed for implementing such advanced systems will be learning. This paper first discusses learning issues in agent-based manufacturing systems and reviews related approaches, then describes how to enhance the performance of an agent-based manufacturing system through learning from history (based on distributed case-based learning and reasoning) and learning from the future (through system forecasting simulation). Learning from history is used to enhance coordination capabilities by minimizing communication and processing overheads. Learning from the future is used to adjust promissory schedules through forecasting simulation, by taking into account the shop floor interactions, production and transportation time. Detailed learning and reasoning mechanisms are described and partial experimental results are presented.     

FLIP: Prototyping multi-robot systems

The main objective of this article is to promote the use of inexpensive and realistic prototypes to verify the applicability of state-of-the-art technologies in the area of mobile robotics and intelligent manufacturing systems. We propose a toy prototype based on a LEGO^® Mindstorms™ RCX brick extended with a PDA and wireless LAN. We describe and evaluate the application of an agent-oriented approach for a prototype of an autonomous transportation system. This transportation system is an integral part of the FLIP project in which intelligent collaboration during transportation and processing of LEGO^® bricks is investigated.     

MetaMorph II: an agent-based architecture for distributed intelligent design and manufacturing

Agent technology derived from Distributed Artificial Intelligence is increasingly being considered for next generation computer-integrated manufacturing systems, to satisfy new requirements for increased integrability, configurability, adaptability, extendibility, agility, and reliability. This paper reviews our previous research on the application of the agent-based technology to intelligent design and manufacturing and describes the current research project MetaMorph II (an agent-based architecture for distributed intelligent design and manufacturing).     

Expert systems: An application in flexible manufacturing

Flexible manufacturing systems (FMS) are needed to provide manufacturing operations with the capability to adjust, in real time, to changes in the manufacturing environment. Realization of the goals of flexible manufacturing is governed by the ability of the FMS to maintain adequate information on the factory to assist in generating scenarios from product planning to operations and performance. This leads to a view where the factory is represented as an integrated information system. To facilitate the analysis of information requirements and the design of information systems for flexible manufacturing, an expert support system (ESS) which can be used to model and study the various structures is described. This ESS uses the information cell model to build these information structures. Petri net representations of these structures and their interactions are then constructed. The ESS may now be used to exercise these models and study their performance using time and cost measures.     

Designing Holonic manufacturing systems

This paper discusses the design of Holonic manufacturing systems (HMS), with emphasis on manufacturing control. First, it discusses the concept of a Holonic system. Second, it presents the HMS reference architecture for manufacturing control. Third, it addresses the overall design problem, i.e. designing both the holonic control system and the underlying manufacturing system. Finally, the paper addresses the design and development of the control software itself.     

An organism-oriented modeling approach to support the analysis and design of intelligent manufacturing systems

In this paper a generic macroscopic object, termed an organism, is introduced. An organism defines a high-level modeling object that has the capabilities for organizational networking, standardization or characteristics specifications, decoupling of editing and visualization as well as temporal management. Organism-oriented models inherit from their parent object-oriented and object/agent-oriented models a simplified representation of the manufacturing entities as well as a capacity for many levels of abstraction. Moreover, the organism-oriented modeling approach enriches these models by not only considering basic manufacturing objects and agents, but also the fact that each of these objects and agents may itself be an organization and also part of one or several organizations. The paper first surveys some of the current approaches used for modeling and analysing manufacturing systems: structured analysis, Petri nets, object and object/ agent models. The object model behind the organism-oriented modeling approach is then presented and its application to a manufacturing case is illustrated.     

An agent-based framework for collaborative negotiation in the global manufacturing supply chain network

This paper applies the multi-agent system paradigm to collaborative negotiation in a global manufacturing supply chain network. Multi-agent computational environments are suitable for dealing with a broad class of coordination and negotiation issues involving multiple autonomous or semiautonomous problem solving agents. An agent-based multi-contract negotiation system is proposed for global manufacturing supply chain coordination. Also reported is a case study of mobile phone global manufacturing supply chain management.     

An object-oriented framework for developing distributed manufacturing architectures

Management of complexity, changes and disturbances is one of the key issues of production today. Distributed, agent-based structures represent viable alternatives to hierarchical systems provided with reactive/proactive capabilities. In the paper, approaches to distributed manufacturing architectures are surveyed, and their fundamental features are highlighted, together with the main questions to be answered while designing new structures. Moreover, an object-oriented simulation framework for development and evaluation of multi-agent manufacturing architectures is introduced.     

Global robust distributed output consensus of multi-agent nonlinear systems: An internal model approach

This paper studies the problem of global robust distributed output consensus of heterogeneous leader–follower multi-agent nonlinear systems by general directed output interactions. For a class of minimum-phase single-input single-output nonlinear agents having unity relative degree, it is shown that the problem is solvable by an internal model approach under certain mild conditions. A Lyapunov function based output-feedback control law is developed by converting the global output consensus into a global distributed stabilization problem for an augmented network.     

A dynamic scheduling holon for manufacturing orders

This paper deals with a new architecture and negotiation protocol for the dynamic scheduling of manufacturing systems. The architecture is based on two paradigms: multi-agent systems and holonic systems. The main contribution in the architecture is the existence of holons representing tasks together with holons representing resources. The well-known contract net protocol has been adapted to handle temporal constraints and to deal with conflicts. It also deals with conflict situations, namely with the case of the indecision problem. This approach assumes that deadlines are the most important constraints to consider.     

An information system for computer-integrated manufacturing systems

One of the main problems when implementing the computer-integrated manufacturing (CIM) concept concerns information integration. In order to support information integration, an information system provided with suitable data models is required. In this paper an information system is presented, which fulfils the requirements for an appropriate information management in CIM. For this purpose, an EXPRESS-oriented information system has been built on top of a commercial relational DBMS. The conceptual model of the information is built in EXPRESS and then parsed and translated to the corresponding relational constructs. A data access interface has been implemented which allows EXPRESS-oriented data manipulation. The information system was developed inside ESPRIT project No. 2202 CIM-PLATO “CIM System Planning Toolbox” to integrate the information used by the tools developed for flexible manufacturing system planning.     

Intelligent agent systems for manufacturing applications

Using the concept of intelligent agents, two system approaches are described for manufacturing applications. The first is based on the rule-based object (RBO) which is associated with a production-rules knowledge base and is implementable in an object-oriented development environment such as Smalltalk-80. A proof-of-concept automated guided vehicle (AGV) system of this kind has been recently developed. The second and more advanced approach is based on the intelligent agent object (IAO) and an AGV system of this kind is currently under development. This uses a multi-agent entity termed the modulon to handle more effectively both the co-operative planning task and the local route planning task.     

Towards a theory of delegation for agent-based systems

In this paper a theory of delegation is presented. There are at least three reasons for developing such a theory. First, one of the most relevant notions of “agent” is based on the notion of “task” and of “on behalf of”. In order to found this notion a theory of delegation among agents is needed. Second, the notion of autonomy should be based on different kinds and levels of delegation. Third, the entire theory of cooperation and collaboration requires the definition of the two complementary attitudes of goal delegation and adoption linking collaborating agents.

After motivating the necessity for a principled theory of delegation (and adoption) the paper presents a plan-based approach to this theory. We analyze several dimensions of the delegation/adoption (on the basis of the interaction between the agents, of the specification of the task, of the possibility to subdelegate, of the delegation of the control, of the help levels). The agent's autonomy and levels of agency are then deduced. We describe the modelling of the client from the contractor's point of view and vice versa, with their differences, and the notion of trust that directly derives from this modelling.

Finally, a series of possible conflicts between client and contractor are considered: in particular collaborative conflicts, which stem from the contractor's intention to help the client beyond its request or delegation and to exploit its own knowledge and intelligence (reasoning, problem solving, planning, and decision skills) for the client itself.