Development of a parallel processing multi-agent architecture for a virtual CIM system

Global manufacturing enterprises tend to rely on fully integrated manufacturing systems to satisfy constantly changing market requirements. In addition, small to medium enterprises are in a dilemma when competing with large organizations. Virtual computer-integrated manufacturing (VCIM) is a realistic concept that can provide the integration requirements for the globally distributed manufacturing resources and it has the potential to satisfy the market requirements of small to medium enterprises. The vision of the VCIM is to improve the efficiency and effectiveness of manufacturing enterprises by seamlessly integrating globally distributed manufacturing resources as much as possible. Meanwhile, intelligent agent technology provides a better means to implement distributed components as integrated application systems. The paper provides a parallel processing multi-agent architecture to support a global integrated manufacturing system in the form of the VCIM. In this architecture, a three-layered structure is proposed to accommodate all the agents no matter where they are located. Multiple Facilitator agents are proposed with similar functionalities to smooth the information flow across the integrated system in a parallel connection manner. In addition, a multi-agent VCIM model that describes the agent identification approaches for VCIM, Java environment implementation approaches and a simulation system to demonstrate the parallel processing multi-agent architecture are also discussed.     

Multi-agent-based approach to solve part selection and task allocation problem in flexible manufacturing systems

Agent technology is currently being considered as an important approach for developing intelligent manufacturing systems. It offers a new way of thinking about many of the classical problems in manufacturing engineering. A multi-agent-based approach for solving the part allocation problems in flexible manufacturing systems (FMS) is presented that can easily cope with the dynamic environment. Four agents were involved in carrying out the tasks of allocating parts on different machines: communicator, machine, part and material handling device (MHD). Upon arrival in the manufacturing facility, the part informs the communicator agent about the task requirements. The communicator agent divides the task into subtasks and sends a call-for-bids message to the machine and MHD agents. Each machine responds in accordance with its process capabilities and buffer limit. This response may be for the whole task or for one or more subtasks and it contains the price and cost details for these subtasks along with the performance index and acceptance ratio of the machine. The final allocation is made based on the objective function that includes processing and transportation costs and time. An algorithm is presented that is used by the communicator agent for allocating parts to different machines. An illustrative example is given to solve the task allocation on five machines, with each machine having different performance index and acceptance ratio.     

An agent-based negotiation approach to integrate process planning and scheduling

This paper presents the development of an agent-based negotiation approach to integrate process planning and scheduling (IPPS) in a job shop kind of flexible manufacturing environment. The agent-based system comprises two types of agents, part agents and machine agents, to represent parts and machines respectively. For each part, all feasible manufacturing processes and routings are recorded as alternative process plans. Similarly, alternative machines for an operation are also considered. With regard to the scheduling requirements and the alternative process plans of a part, the proposed agent-based IPPS system aims to specify the process routing and to assign the manufacturing resources effectively. To establish task allocations, the part and machine agents have to engage in bidding. Bids are evaluated in accordance with a currency function which considers an agent's multi-objectives and IPPS parameters. A negotiation protocol is developed for negotiations between the part agents and the machine agents. The protocol is modified from the contract net protocol to cater for the multiple-task and many-to-many negotiations in this paper. An agent-based framework is established to simulate the proposed IPPS approach. Experiments are conducted to evaluate the performance of the proposed system. The performance measures, including makespan and flowtime, are compared with those of a search technique based on a co-evolutionary algorithm.     

A coordination strategy for distributed multi-agent manufacturing systems

This paper proposes a distributed multi-agent approach for dynamic part routing in automated manufacturing systems. In particular, each part in the system is associated to an intelligent software agent that must select its next destination autonomously (i.e. ignoring the actions of the other agents) and in real time (i.e. at each time it completes an operation on a workstation). Differently from other existing approaches, we overcome the typical myopia of negotiation algorithms based on dispatching rules by allowing the part agents to take decisions not only about the imminent operation, but also for the subsequent ones. The anticipated decisions are transmitted to workstation agents, which are also designated to detect and resolve conflicts by modifying part agents’ decisions. To describe the single agents and their interaction schemes in a formal way, we take advantage of DEVS discrete-event modelling tools, which also allow us to develop a detailed simulation platform for our multi-agent system. The simulation experiments obtained on a detailed model of a manufacturing system derived from the literature confirm the effectiveness of the proposed approach.     

A review of “Advances in Computer-Integrated Manufacturing.” Edited by Peter J. Sacket (JAI Press Ltd., 1990) [pp. 188]. Price £ 48, US $ 81·95.

Global competition and rapidly changing customer requirements are forcing major changes in the production styles and configuration of manufacturing organizations. Traditional centralized manufacturing systems are not able to meet such requirements. This paper proposes an agent-based approach for dynamically creating and managing agent communities in such widely distributed and everchanging manufacturing environments. After reviewing the research literature, an adaptive multi-agent manufacturing system architecture called MetaMorph is presented and its main features are described. Such architecture facilitates multi-agent coordination by minimizing communication and processing overheads. Adaptation is facilitated through organizational structural change and two learning mechanisms: learning from past experiences and learning future agent interactions by simulating future dynamic, emergent behaviours. The MetaMorph architecture also addresses other specific requirements for next generation manufacturing systems, including scalability, reliability, stability, maintainability, flexibility, real-time planning and scheduling, standardized communication, fault tolerance, and security. The proposed architecture is implemented as a multi-agent virtual manufacturing system, in simulation form, which incorporates heterogeneous manufacturing agents within different agent-based shop floors or factories. The experimental results have shown the potential of the agent-based approach for advanced manufacturing systems.     

Investigation of the reconfigurable control system for an agile manufacturing cell

A new type of manufacturing cell, with characteristics of reconfigurability, reusability and scalability, needs to be developed. To achieve the agile reconfiguration of a manufacturing cell, the cell control system must be rapidly and efficiently generated or modified. In this paper, a multi-agent based architecture is defined that supports the design and implementation of highly reconfigurable control systems for agile manufacturing cells, which are comprised of resource agents (material processing agents, material handling agents, and material storage agents), a control agent, and an information agent, in order to reduce costs and increase the control system's agility with respect to the changing environment. Different agents in the cell control system can be organized dynamically, communicate with each other through messages, and cooperate with each other to perform flexibly the task in the cell control system. The structure of the agents is proposed and the message-passing between agents is discussed in detail.     

Formal verification of negotiation protocols for multi-agent manufacturing systems

Formal verification is an important means of tackling behavioural problems such as deadlocks in multi-agent systems. This paper is concerned with the role played by formal verification in the simulation-based performance analysis of multi-agent manufacturing systems. A discrete-event simulation case study is presented to show how varying certain timing parameters of the agent negotiation protocol affects the performance of a multi-agent manufacturing system as well as the chance of getting deadlocks among the software agents. When one tries to determine the optimal values of these timing parameters based on the simulation results, formal verification can help refine the results by confirming whether deadlocks among software agents are indeed possible for particular parameter values. This involves modelling the system's real-time behaviour according to the simulation model and applying the techniques and tools of model checking.     

Agent-based manufacturing control based on distributed bid selection and publish-subscribe messaging: a simulation case study

Bidding-based negotiation schemes play a major role in multi-agent manufacturing systems research. Despite some concerns with message congestion, researchers have been proposing and studying negotiation schemes based on the contract net protocol (CNP). On the other hand, research in robotics has considered a variant of CNP based on publish-subscribe messaging designed for multi-robot coordination. A distinct feature of this variant involves distributing the bid evaluation and selection functions among robot agents. This paper discusses our adaptation of this design variant for multi-agent manufacturing systems and examines its performance implications. Using discrete-event simulation, we study how the adapted CNP design can help address the message congestion problem by cutting down on negotiation slack time. Our case study results show that it can enhance the resilience of the agent negotiation process to message congestion, thereby contributing to the overall performance of a multi-agent manufacturing system.     

Optimal resource assignment through negotiation in a multi-agent manufacturing system

Research studies on multi-agent systems have been recently boosted by manufacturing and logistics with deep motivations like the presence of independent human deciders with individual goals, the aspiration to dominate the complexity of decision-making in large organizations, the simplicity and robustness of self-reacting distributed systems. After a survey of the multi-agent paradigm and its applications, the paper introduces the notion of hybrid holonic system to study the effect of supervision on a system whose elements negotiate and cooperate in a rule-settled environment to obtain resources for system operation. The supervisor can spur or disincentive agents by assigning/denying resources to them. A simple single-decider optimization model referred to a real application is described, and solution methodologies for optimal resource allocation fitting different scenarios (centralized, distributed, multi-agent) are discussed, identifying ranges of autonomy, quantifying rewarding and defining a negotiation protocol between the agents and the supervisor. Aim of the paper is to describe through an example a general methodology for quantitative decision-making in multi-agent organizations.     

A multi-agent model for the reasoning of uncertainty information in supply chains

In order to simulate the real world effectively, this paper proposes a multi-agent model that integrates a price negotiation support system based on the use of intelligent agents capable of processing information uncertainty. The certainty factor is integrated in expert systems to support the decision of agents. In the model, each agent is integrated with an expert system to deal with the uncertainty information. A real example of supply chains is chosen to show the validity of the proposed multi-agent model. Virtual companies can use the uncertainty information to support decisions. Multiple experiments are conducted to work on the coordination of the supply chain. The selling and purchasing prices in the supply chain are proposed in the experimental results. These prices are similar with the data in a real supply chain and are the optimal price strategy for the supply chain. The model was programmed using Jess and Swarm, which was run on Windows XP. The multi-agent model in the paper is beneficial to the reasoning of uncertainty information in multi-agent systems.     

Dynamic production control with dispatching within pre-emption

This paper deals with a production control problem for the testing and rework cell in a dynamic and stochastic computer integrated manufacturing (CIM) system. This research first defines dispatching within pre-emption for an extended form of pre-emption. A dynamic controller called competitive decision selector (CDS) is then modified and extended as CDSplus to handle three different production control decisions; dispatching, pre-emption, and dispatching within pre-emption. It observes the status of the system and jobs at every decision point, and makes its three different decisions in real time. The CDSplus dynamic control shows better performance than static control rules with respect to the number of tardy jobs.     

基于元结构的螺杆转子磨床床身动静态特性分析与优化

摘 要：螺杆转子磨床床身是关键的承载大件,其动静态性能的好坏将直接影响整机的加工精度和稳定性。为实现床身的快速动态优化设计,首先基于元结构理论,使用ANSYS软件仿真分析了床身筋格元结构各主要参数对其动态特性的影响。在此基础上,以提高床身低阶模态固有频率和降低床身重量为目标,对床身的结构参数进行优化,同时通过静力分析验证了优化方案的可行性。优化后,床身低阶固有频率得到了较大幅度的提高,其中一阶固有频率提高了22.3%,床身的重量下降了8.39%,同时静刚度也有明显提高,改善了床身的动静态特性,节约了制造成本。该方法对其他类似关键零部件的动态优化设计具有一定的借鉴意义。     

Agent-based distributed scheduling for virtual job shops

Nowadays, market globalisation and stiff world-wide competition require flexible, demand-driven, and reconfigurable production systems that can adapt to the requirements of the increasing reduction in product life cycle and rapid changes in market demand. The advent and development of network technology (especially the Internet) and distributed computing technology make it possible for geographically dispersed manufacturing resources to be integrated and deployed effectively and efficiently. In addition, manufacturing enterprises can expand their throughput within a short time and rapidly reduce the production cycle via transferring certain jobs to other available manufacturing resources in the globalised manufacturing environment, viz., manufacturing enterprises can expand their throughput through the dynamic formation of virtual job shops according to the production requirements. Owing to more open manufacturing environments and rapid changes of market demands, the traditional centralised scheduling approaches are not suitable for this open distributed manufacturing environment. This paper proposes a distributed scheduling approach in which a multi-agent solution towards a ‘task-machine’ assignment is presented. The main points of discussion are the formation of a virtual job shop that is based on market mechanism and the distributed scheduling approach based on negotiation.     

Using a multi-agent system to optimise resource utilisation in multi-site manufacturing facilities

Due to cost economies and better serving the global market, many enterprises expanded their manufacturing environment from a localised, single-site facility to more globalised, multi-site facilities. In order to take advantage of operating multi-site facilities, it is vital to make optimisation decisions of resource utilisation as if these facilities situated across different geographical locations are one integrated facility and take into account of the extended multi-site constraints and variables. This paper proposes a multi-agent system, using its characteristics of autonomy and intelligence, to integrate process planning and production scheduling across different facilities, so as to secure the most efficient and cost-effective plan and schedule to meet the demand. A currency-based agent iterative bidding mechanism is developed to facilitate the co-ordination of agents to achieve the goal. A genetic algorithm is employed to tune the currency values for agent bidding. In this paper, a case study is used for simulation in order to demonstrate the effectiveness and performance of the proposed agent system.     

Reactive scheduling in a dynamic and stochastic FMS environment

In this paper, we study the reactive scheduling problems in a dynamic and stochastic manufacturing environment. Specifically, we develop a simulation-based scheduling system for flexible manufacturing systems. We also propose several reactive scheduling policies (i.e. when-to-schedule and how-to-schedule policies) and test their performances under various experimental conditions, processing time variations, and machine breakdowns. Moreover, we compare offline and online scheduling schemes in a dynamic manufacturing environment. The results of extensive simulation experiments indicate that the variable-time-response is better than the fixed-time-response. The full scheduling scheme generally performs better than the partial scheduling. Finally, the online scheduling is more robust to uncertainty and variations in processing times than the optimum-seeking offline scheduling. A comprehensive bibliography is also provided in the paper.     

ExPlanTech: Applying multi-agent systems in production planning

This paper presents work carried out within the 'ExPlanTech' project (IST-1999-20171) funded in part by the European Commission's Information Technologies Programme. The mission of the ExPlanTech technology transfer project is to introduce, customize and exploit the multi-agent production planning technology (ProPlanT multi-agent system research prototype) in two specific industrial enterprises. An agent-driven service negotiations and decision process, based on usagecentred knowledge about task requirements, substitutes the traditional production planning activity. We introduce a methodology for integration of the projectdriven production planning based on agent-based engineering within the existing enterprise resource planning system. This novel production planning technology will facilitate optimization of resource utilization and supplier chain while meeting the customer demands. This paper describes a FIPA-compliant implementation of the ExPlanTech technology at the LIAZ Pattern Shop manufacturing company. We describe the structure of the agent community, types of agents, implementation of the planning strategy and its incorporation within the real production environment.     

Autonomy and viability-measures for agent-based manufacturing systems

An Agent-Based Manufacturing System (ABMS), represented as a model of future manufacturing systems, is introduced in this article. In an ABMS, computerized agents are autonomous and working collaboratively through the regulation of structured dialogues. The autonomy functions of an agent are demonstrated by four internal functions: internal resource management, a reflexivity mechanism, a goal adjustment mechanism, and collaboration management. The four functions assist an agent in interacting with other agents and with the environment and to adjust itself to the situation in the dynamic environment. Agents are similar to living systems. Based on the concept of living systems, autonomy and viability at the agent level are proposed and defined as new measures for manufacturing systems. A theory of coexistence and parasitism of ABMS is developed to identify the coexistent and parasitic characteristics of ABMS. Applications of the theory to real cases are also illustrated. Finally, a road map for the future research of distributed, collaborative manufacturing organizations is shown, based on the ABMS model developed.     

System for early cost estimation of die-cast parts

Early cost estimate of a part is important information and forms a basis for preparing quotations, which are competitive from a market point of view. It is seen that a commonly adopted approach of variant cost estimation based only on geometric information of the component is not always accurate. This is also true in the case of die-cast parts. The geometric complexity of the part, tooling complexity, part and tool material, processing cost, and manufacturing resources for producing the part all need to be considered for accurate cost estimation. This paper deals with a comprehensive system developed to estimate and analyze the manufacturing cost of die-cast parts. A computer-aided cost-estimation system has been developed that applies manufacturing process as well as manufacturing resource considerations in addition to part feature complexity. Use of the proposed system is demonstrated in selecting the optimum number of cavities and the appropriate manufacturing resources under machine-related constraints. Further, the cost-estimation system developed herein is used for carrying out feature sensitivity analysis to identify design features that add significant cost to the part. The use of this system for optimal machine loading in multiple parts situation is also demonstrated.     

Incorporating dynamism in traditional machine loading problem: an AI-based optimisation approach

Machine breakdowns have been recognised in flexible manufacturing systems (FMS) as the most undesirable characteristic adversely affecting the overall efficiency. In order to ameliorate product quality and productivity of FMS, it is necessary to analyse, as well as to minimise the effect of breakdowns on the objective measures of various decision problems. This paper addresses the machine loading problem of FMS with a view to maximise the throughput and minimise the system unbalance and makespan. Moreover, insufficient work has been done in the domain of machine loading problem that considers effect of breakdowns. This motivation resulted in a potential model in this paper that minimises the effect of breakdowns so that profitability can be augmented. The present work employs an on-line machine monitoring scheme and an off-line machine monitoring scheme in conjunction with reloading of part types to cope with the breakdowns. The proposed model bears similarity with the dynamic environment of FMS, hence, termed as the dynamic machine loading problem. Furthermore, to examine the effectiveness of the proposed model, results for throughput, system unbalance and makespan on different dataset from previous literature has been investigated with application of intelligence techniques such as genetic algorithms (GA), simulated annealing (SA) and artificial immune systems (AIS). The results incurred under breakdowns validate the robustness of the developed model for dynamic ambient of FMS.     

Dynamic cellular manufacturing system design considering alternative routing and part operation tradeoff using simulated annealing based genetic algorithm

In this paper, an integrated mathematical model of multi-period cell formation and part operation tradeoff in a dynamic cellular manufacturing system is proposed in consideration with multiple part process route. This paper puts emphasize on the production flexibility (production/subcontracting part operation) to satisfy the product demand requirement in different period segments of planning horizon considering production capacity shortage and/or sudden machine breakdown. The proposed model simultaneously generates machine cells and part families and selects the optimum process route instead of the user specifying predetermined routes. Conventional optimization method for the optimal cell formation problem requires substantial amount of time and memory space. Hence a simulated annealing based genetic algorithm is proposed to explore the solution regions efficiently and to expedite the solution search space. To evaluate the computability of the proposed algorithm, different problem scenarios are adopted from literature. The results approve the effectiveness of the proposed approach in designing the manufacturing cell and minimization of the overall cost, considering various manufacturing aspects such as production volume, multiple process route, production capacity, machine duplication, system reconfiguration, material handling and subcontracting part operation.