SURVEY OF DYNAMIC SCHEDULING IN MANUFACTURING SYSTEMS <s> 13 <s> Abstract There is increasing trend towards more autonomous and distributed shop-floor organisations. Operational characteristics of such a shop-floor will derive from independently acting but cooperating entities. These would have capabilities for scheduling in relative isolation while resolving conflicts among themselves to maintain consistency between local schedules. We review both negotiation and the emerging behaviour-based methods for scheduling and coordinating distributed entities within both hierarchical and heterarchical control structures. The approaches are reviewed with a focus on the issues that are of practical importance. <s> BIB001 </s> SURVEY OF DYNAMIC SCHEDULING IN MANUFACTURING SYSTEMS <s> 13 <s> Agent technologies have steadily matured in moving from the research laboratory to industrial application over the last ten years. Numerous systems have been deployed or are under advanced development with strong industrial support. These systems suggest important lessons for both industry and researchers. From an industrial perspective, these examples reflect trends in both business and technology that make agents an increasingly attractive commercial tool. From a research perspective, these examples identify important gaps in agent technology that merit the attention of academicians. <s> BIB002 </s> SURVEY OF DYNAMIC SCHEDULING IN MANUFACTURING SYSTEMS <s> 13 <s> Abstract This discussion paper examines the role of hierarchy within the domain of shop floor control in manufacturing plants. Specifically, three distinct structures for shop floor control are considered, namely, hierarchical, heterarchical and holonic control systems. Holonic manufacturing is a novel paradigm for manufacturing that tries to merge the best properties of both hierarchical and heterarchical systems, namely, a high and predictable performance with a high robustness against disturbances. The paper identifies the concept of hierarchy in distributed shop floor control as one of the key contributions of holonic manufacturing. In a holonic architecture, the mapping of functions to control units remains flexible, such that decision power can be distributed over these units as needed. Based on the invariants concept of computer science, a modelling framework is proposed to identify the decision making needs of each unit. It can be used not only to describe the behaviour of the system, but also to impose performance and operational guarantees. <s> BIB003 </s> SURVEY OF DYNAMIC SCHEDULING IN MANUFACTURING SYSTEMS <s> 13 <s> Abstract The requirement for adaptable and re-configurable control systems for manufacturing has highlighted the inadequacies of traditional centralised control approaches, leading researchers to focus on decentralised approaches. The question of what is the most appropriate control architecture for a given system has led industrial and academic researchers to develop a spectrum of decentralised control architectures ranging from hierarchical to non-hierarchical structures. While current research has confirmed the potential of decentralised architectures, neither extreme of this control architecture spectrum has proven to be the most appropriate choice for a given manufacturing system. Recent research into providing an objective comparison of alternative control architectures has shown that some degree of hierarchy is important for distributed manufacturing control architectures. This paper is concerned with our current investigations into why these partial hierarchies appear to display superior performance. <s> BIB004 </s> SURVEY OF DYNAMIC SCHEDULING IN MANUFACTURING SYSTEMS <s> 13 <s> Agent technology has been considered as an important approach for developing distributed intelligent manufacturing systems. A number of researchers have attempted to apply agent technology to manufacturing enterprise integration, supply chain management, manufacturing planning, scheduling and control, materials handling, and holonic manufacturing systems. This paper gives a brief survey of some related projects in this area, and discusses some key issues in developing agent-based manufacturing systems such as agent technology for enterprise integration and supply chain management, agent encapsulation, system architectures, dynamic system reconfiguration, learning, design and manufacturability assessments, distributed dynamic scheduling, integration of planning and scheduling, concurrent scheduling and execution, factory control structures, potential tools and standards for developing agent-based manufacturing systems. An extensive annotated bibliography is provided. <s> BIB005
A common architecture gives a central computer responsibility for scheduling, dispatching resources, monitoring any deviation, and dispatching corrective actions. Centralised and hierarchical scheduling systems present a number of drawbacks  BIB001 BIB005 BIB003 BIB004 ). The primary drawback is the existence of a central computer, which constitutes a bottleneck that can limit the capacity of the shop, and it is a single point of failure that can bring down the entire shop. Furthermore, modifying the configuration of hierarchically controlled manufacturing systems is expensive and time consuming as it involves expensive software rewriting. The hierarchical scheduling manufacturing systems are becoming increasingly complex with the integration of manufacturing system components. Another disadvantage is that the up and down flow of information increases the latency time of decisionmaking. Moreover practical experience has indicated that hierarchical centralised scheduling systems tend to have problems reacting to disturbances and may fail to respond effectively to the presence of real-time events. When a disturbance occurs, it is fed back to the high level in the hierarchy, and only after the scheduler has been adapted, the new schedule triggers a new flow of commands that forms the reaction to the disturbance. This up and down movement of information results in a slow response time leading to a low robustness. Despite the fact that centralised and hierarchical scheduling systems may provide globally better schedules in environments where real-time disturbances are rare, increasingly they are being found to be inefficient to respond to highly dynamic environments. Therefore, centralised and hierarchical scheduling is complex, difficult to maintain and reconfigure, inflexible, costly, and slow to satisfy the needs of today's complex manufacturing environments. Global competitive pressure in manufacturing has resulted in fundamental changes in the operation of manufacturing systems. Today's systems must rapidly adapt to disturbances while maintaining shorter product cycles, improving productivity, and increasing operational flexibility. To face this challenge, the current trend has been towards highly automated systems that are intended to offer robustness, stability, adaptability, and efficient use of available resources through a modular and distributed design (Parunak, 1996; BIB004 Shen et al., 2001 ). There is a growing trend towards distributed shop floor organisations as a result of the need for enhanced levels of responsiveness from the shop floor to changes in markets and technologies. The primary motivation in designing these systems is to decentralise the control of the manufacturing system, thereby reducing the complexity and cost, increasing flexibility, and enhancing fault tolerance. There is a substantial evidence that multi-agent systems one of the most promising approach to building complex, robust, and cost-effective next-generation manufacturing scheduling systems because of their autonomous, distributed and dynamic nature, and robustness against failures  BIB002 Shen et al., 2001; BIB004 (1996) .The use of multi-agent systems to solve the problem of dynamic scheduling is motivated by the following key points  BIB002 BIB005  BIB004 Shen et al., 2001 ). First, multi-agent-based scheduling systems recognise that data and control are distributed through the factory. These systems are composed of autonomous agents attached to each physical or functional manufacturing entity in the facility (resources, operators, parts, jobs, etc.). Local autonomy allows the agents to take the responsibility for carrying out local scheduling for one or more entities in the production process and to respond locally and efficiently to local variations, increasing the robustness and the flexibility of the system. Secondly, these individual agents have considerable latitude in responding to local conditions and interacting and cooperating with each other in order to achieve global optimal and robust schedules. The overall system performance is not globally planned, but emerges through the dynamic interaction of the agents in real-time. Thus the system emerges from the concurrent independent local decisions of the agents. Thirdly, the software for each agent is much shorter and simpler than it would be for a centralised approach, and as a result is easier to write, install and maintain. Furthermore, it is possible to integrate new resources or remove existing ones with their attached agents to from the factory floor without any changes in existing software in the shop, simply by connecting them to the factory network.