Dynamically Integrated Manufacturing Systems (DIMS)—A Multiagent Approach

Manufacturing businesses in today's market are facing immense pressures to react rapidly to dynamic variations in demand distributions across products and changing product mixes. To cope with the pressures requires dynamically integrated manufacturing systems (DIMS) that can manage optimal fulfillment of customer orders while simultaneously considering alternative system structures to suit changing conditions. This paper presents a multiagent approach to DIMS, where production planning and control decisions are integrated with systems reconfiguration and restructure. A multiagent framework, referred to as a hierarchical autonomous agent network, is proposed to model complex manufacturing systems, their structures, and constraints. It allows the hierarchical structures of complex systems to be modeled while avoiding centralized control in classical hierarchical/hybrid frameworks. Subsystems interact heterarchically with product orders to carry out optimal planning and scheduling. An agent coordination algorithm, operating iteratively under the control of a genetic algorithm, is developed to enable optimal planning and control decisions for order fulfillment to be made through interactions between agents. This algorithm also allows the structural constraints of systems to be relaxed gradually during agent interaction, so that planning and control are first carried out under existing constraints, but when satisfactory solutions cannot be found, subsystems are allowed to regroup to form new configurations. Frequently used configurations are detected and evaluated for system restructure. The approach also enables Petri-net models of new system structures to be generated dynamically and the structures to be evaluated through agent-based discrete event simulation.     

Simulation of intelligent hierarchical flexible manufacturing:batch job routing in operation overlapping

We present an approach to embedding expert systems within an object-oriented simulation environment that facilitates the creation of classes of expert system model elements that can be interfaced with other model components. Previous work has shown how distributed expert systems can be defined as modular components of simulations models. This article illustrates their usefulness in fractal architectures for flexible manufacturing, as proposed in the literature. Alternate structures (reconfigured structures) of a proposed hierarchical factory architecture can be generated through the recursive pruning process. Such rapid prototyping should greatly enhance the ability to investigate alternative architectural solutions to manufacturing problems in a timely manner     

An agent-based approach for e-manufacturing and supply chain integration

A major problem facing manufacturing organisations is how to provide efficient and cost-effective responses to the unpredictable changes taking place in a global market. This problem is made difficult by the complexity of supply chain networks coupled with the complexity of individual manufacturing systems within supply chains. Current systems such as manufacturing execution systems (MES), supply chain management (SCM) systems and enterprise resource planning (ERP) systems do not provide adequate facilities for addressing this problem. This paper presents an approach that would enable manufacturing organisations to dynamically and cost-effectively integrate, optimise, configure, simulate, restructure and control not only their own manufacturing systems but also their supply networks, in a co-ordinated manner to cope with the dynamic changes occurring in a global market. This is realised by a synergy of two emerging manufacturing concepts: Agent-based agile manufacturing systems and e-manufacturing. The concept is to represent a complex manufacturing system and its supply network with an agent-based modelling and simulation architecture and to dynamically generate alternative scenarios with respect to planning, scheduling, configuration and restructure of both the manufacturing system and its supply network based on the coordinated interactions amongst agents.     

Distributed evolutionary algorithms for simulation optimization

The optimization of such complex systems as manufacturing systems often necessitates the use of simulation. In this paper, the use of evolutionary algorithms is suggested for the optimization of simulation models. Several types of variables are taken into account. The reduction of computing cost is achieved through the parallelization of this method, which allows several simulation experiments to be run simultaneously. Emphasis is put on a distributed approach where several computers manage both their own local population of solutions and their own simulation experiments, exchanging solutions using a migration operator. After a first evaluation through a mathematical function with a known optimum, the benefits of this new approach are demonstrated through the example of a transport lot sizing and transporter allocation problem in a manufacturing flow shop system, which is solved using a distributed software implemented on a network of eight Sun workstations     

Agent-based modeling and simulation of an autonomic manufacturing execution system

Production management systems must constantly deal with unplanned disruptive events and disturbances such as arrivals of rush orders, raw material shortage/delays or equipment breakdowns along with a multitude of interactions in the supply chain which constantly demand on-line task rescheduling and order execution control. For responsiveness and agility at the shop-floor, a distributed design for manufacturing execution systems is proposed based on autonomic units that fill the gap between production planning and shop-floor control. An interaction mechanism designed around the concept of order and resource agents implementing the monitor-analyze-plan-execution loop is described. Generative simulation modeling of an autonomic manufacturing execution system (@MES) is proposed in order to evaluate emerging behaviors and macroscopic dynamics in a multiproduct batch plant. Results obtained for an industrial case study using a simulation model of the proposed @MES are presented. The usefulness of agent-based modeling and simulation as a tool for distributed MESs design and to verify performance, stability and disturbance rejection capability of an interaction mechanism is highlighted.     

Implementation of real-time distributed control for discrete event robotic systems using Petri nets

This article presents a systematic method of modeling and implementing real-time control for discrete-event robotic systems using Petri nets. Because, in complex robotic systems such as flexible manufacturing systems, the controllers are distributed according to their physical structure, it is desirable to realize real-time distributed control. In this article, the task specification of robotic processes is represented as a system control-level net. Then, based on the hierarchical approach, it is transformed into detailed subnets, which are decomposed and distributed into the local machine controllers. The implementation of real-time distributed control through communication between the system controller and the machine controllers on a microcomputer network is described for a sample robotic system. The proposed implementation method is sufficiently general, and can be used as an effective prototyping tool for consistent modeling, simulation, and real-time control of large and complex robotic systems.     

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.     

Dynamic structuring of distributed manufacturing systems

The paper addresses the problem of dynamic structuring of manufacturing systems. The approach presented in this paper is based on the decomposition of manufacturing objectives and the allocation of tasks to autonomous building blocks, i.e. work systems, in a dynamic environment. The allocation is based on a market mechanism that enables the self-structuring and optimization of a manufacturing system by evaluation and selection among competing work systems. The mechanism presented is based on logic relations and constraints. It enables the building of task-oriented manufacturing structures of work systems acting in series and/or in parallel. The approach is discussed in an example in the part fabrication domain.     

A distributed time-driven simulation method for enabling real-time manufacturing shop floor control

This paper proposes a distributed simulation approach for scheduling discrete-events in manufacturing shop floors. The proposed approach employs a time-driven method to simulate occurrence of discrete-events using distributed entities that replicate physical entities in the manufacturing shop floor. In specific, the proposed approach iteratively controls the timing of discrete-events occurrence using a control theoretic model. In this approach, changing the speed of the simulation clock, termed time-scaling factor, can accelerate or decelerate the simulation speed resulting in simpler synchronizations of discrete-events and faster simulation than standard distributed discrete-event simulations according to the capability of the communication networks. Computational experiments are conducted to test the performance of the proposed system with different values of the time-scaling factor, and the relationship between the system performance and the time-scaling factor is investigated through analysis of the system model. Results obtained from the computational experiments show significant successes in speeding up discrete-event simulations in such a way that the proposed approach can be used for the control of manufacturing shop floors, providing real-time decision supports.     

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.     

Performance improvement of Distributed Virtual Environments by exploiting objects’ attributes

Distributed virtual environments need to address issues related to the control of network traffic, resource management, and scalability. Given the distributed nature of these environments, the main problems they need to overcome are the efficient distribution of workload among the servers and the minimization of the communication cost. In this direction, a lot of work has been done and numerous relevant techniques and algorithms have been proposed. The majority of these approaches mainly focus on user entities and their interactions. However, most of actual DVE systems include additional and non-dynamic elements, denoted as objects, whose presence can affect users?? behavior. This paper introduces virtual objects?? attributes and proposes two approaches that exploit these attributes in order to handle workload assignment and communication cost in DVE systems. Both approaches take into account scenario-specific aspects of DVE systems, such as the impact that entities?? attributes have on each other and the way this impact can affect the system??s state. These scenario-specific aspects are then combined with quantitative factors of the system, such as workload, communication cost, and utilization. The experiments conducted in order to validate the behavior of the proposed approach show that the incorporation of object??s presence can improve the DVE system??s performance. More specifically, objects?? presence and their attributes can assist in the significant reduction in the communication cost along with effective workload distribution among the system??s servers.     

Simulation of service-oriented and distributed manufacturing systems

In this paper modeling and simulation is discussed in the context of distributed manufacturing systems (DiMS). The DiMS concept aims towards efficient and innovative collaboration that integrates design and development activities of manufacturing systems. A DiMS, described formally as a digital manufacturing system, is a competent basis for the modeling and simulation of manufacturing systems. The activities of the simulation model are described on the basis of a service-oriented approach in which content of the services is completely known. Micro, meso, and macro manufacturing levels are applied to the modeling and simulation. By means of these levels the hierarchy of the communication of the services is illustrated. An example is described in which modeling and simulation is used to proceed from ideas to efficiently operated manufacturing systems.     

Simulation aided design of organizational structures in manufacturing systems using structuring strategies

This paper presents a simulation aided approach for designing organizational structures in manufacturing systems. The approach is based on a detailed modeling and characterization of the forecasted order program, especially of elementary processes, activity networks and manufacturing orders. Under the use of the organization modeling system FORM, that has been developed at the ifab-Institute of Human and Industrial Engineering of the University of Karlsruhe, structuring strategies—e.g., a process-oriented strategy—can be applied in order to design organizational structures in manufacturing systems in a flexible and efficient way. Following that, a dynamical analysis of the created manufacturing structures can be carried out with the simulation tool FEMOS, that has also been developed at the ifab-Institute. The evaluation module of FEMOS enables to measure the designed solutions with the help of logistical—e.g., lead time degree—and organizational—e.g., degree of autonomy—key data. This evaluation is the basis for the identification of effective manufacturing systems and also of improvement potentialities. Finally, a case study is presented in this paper designing and analyzing different organizational structures of a manufacturing system where gear boxes and robot grip arms were manufactured.     

A knowledge-based simulation environment for hierarchical flexiblemanufacturing

This article presents an approach to embedding expert systems within an object oriented simulation environment. The basic idea is to create classes of expert system models that can be interfaced with other model classes. An expert system shell is developed within a knowledge-based design and simulation environment which combines artificial intelligence and systems modeling concepts. In the given framework, interruptible and distributed expert systems can be defined as components of simulations models. This facilitates simulation modeling of knowledge-based controls for flexible manufacturing and many other autonomous intelligent systems. Moreover, the structure of a system can be specified using a recursive system entity structure (SES) and unfolded to generate a family of hierarchical structures using an extension of SES pruning called recursive pruning. This recursive generation of hierarchical structures is especially appropriate for design of multilevel flexible factories. The article illustrates the utility of the proposed framework within the flexible manufacturing context     

Economics‐inspired decentralized control approach for adaptive grid services and applications

Grid technologies facilitate innovative applications among dynamic virtual organizations, while the ability to deploy, manage, and properly remain functioning via traditional approaches has been exceeded by the complexity of the next generation of grid systems. An important method for addressing this challenge may require nature‐inspired computing paradigms. This technique will entail construction of a bottom‐up multiagent system; however, the appropriate implementation mechanism is under consideration in order for the autonomous and distributed agents to emerge as a controlled grid service or application. A credit card management service in economic interactions is considered in this article for a decentralized control approach. This consideration is based on a preliminarily developed ecological network‐based grid middleware that has features desired for the next generation grid systems. The control scheme, design, and implementation of the credit card management service are presented in detail. The simulation results show that (1) agents are accountable for their activities such as behavior invocation, service provision, and resource utilization and (2) generated services or applications adapt well to dynamically changing environments such as agent amounts as well as partial failure of agents. The approach presented herein is beneficial for building autonomous and adaptive grid applications and services. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 1269–1288, 2006.     

Probabilistic rule-based argumentation for norm-governed learning agents

This paper proposes an approach to investigate norm-governed learning agents which combines a logic-based formalism with an equation-based counterpart. This dual formalism enables us to describe the reasoning of such agents and their interactions using argumentation, and, at the same time, to capture systemic features using equations. The approach is applied to norm emergence and internalisation in systems of learning agents. The logical formalism is rooted into a probabilistic defeasible logic instantiating Dung??s argumentation framework. Rules of this logic are attached with probabilities to describe the agents?? minds and behaviours as well as uncertain environments. Then, the equation-based model for reinforcement learning, defined over this probability distribution, allows agents to adapt to their environment and self-organise.     

Integration of virtual and real environments for engineering service-oriented manufacturing systems

Engineering frameworks are currently required to support the easy, low-cost, modular and integrated development of manufacturing systems addressing the emergent requirements of re-configurability, responsiveness and robustness. This paper discusses the integration of 2D/3D digital software tools with Petri net based service-oriented frameworks to allow the design, configuration, analysis, validation, simulation, monitoring and control of manufacturing systems in a virtual environment and its posterior smooth migration into the real ??physical?? environment. An experimental case study was implemented to validate the proposed concepts, using the Continuum platform to design, compose, analyze, validate and simulate the Petri nets based service-oriented manufacturing control system, and the Delmia Automation^TM software suite to support the rapid prototyping and the easy simulation of the designed control solution. The experimental results prove several aspects of the proposed approach, notably the smooth migration between the design and the operation phases, one of the main objectives of the work.     

A fuzzy-based genetic approach to the diagnosis of manufacturing systems

This paper describes the development of a hybrid approach that integrates graph theory, fuzzy sets and genetic algorithms for the diagnosis of manufacturing systems. The approach enables the modelling of causal relations of system components in manufacturing systems. Based on the model thus established, a worst-first search technique has been proposed and developed for the identification of probable fault-propagation paths. As manufacturing diagnosis often involves the interpretation of uncertainty, fuzzy-set theory is employed for this purpose. Unlike conventional diagnostic systems which assume that all the system components or nodes of a manufacturing system model are measurable, the genetic-algorithm-based search engine developed in this work is able to deal with nodes that cannot be, or are not, measured. Details of the hybrid approach, the worst-first search technique and the genetic-algorithms-based search engine are discussed. The framework of a prototype fuzzy-based genetic diagnostic system is described. Details of the system validation are also presented.     

Distributed manufacturing execution systems: A workflow perspective

Research of manufacturing execution systems (MESs) has been conducted to integrate ERP and physical operational systems, so a fully automated and integrated manufacturing management environment can be developed. However, as subcontracting becomes common in industries, a single MES is not enough and it is necessary to develop distributed MESs to integrate the distributed operations. This research proposes a distributed workflow model to develop such a system. In the workflow model, there are three cooperation types for defining the relationships between an action and resources. Six relational patterns are defined for the relationships between actions. This research also reviews current information technologies, including data acquisition and control (DAC) components, control software's, ASP .NET, and CLIPS, for supporting the development of distributed workflow models. Additionally, this research proposes using a collaborative workflow-based protocol (CWP) to form a distributed workflow. CWP is based on the integration of Internet technology and CLIPS. It is found that the proposed structure may ease the decision process of forming a distributed workflow. In summary, this article reports a cutting edge approach for the development of distributed manufacturing execution systems. The results show solutions for integrating high-level planning systems, such as ERP, and low-level operational systems through information technologies.     

Modelling automated manufacturing systems using a modification of coloured petri nets

Automated manufacturing systems (AMS) are a class of systems exhibiting concurrency, asynchronicity and distributedness, and can be modelled using Petri nets. The advantage of using Petri nets is that they provide graphical models, with formal methods of analysis. However, graphical representation of Petri net models becomes difficult even for medium-sized systems since such graphs tend to become inconveniently large. Coloured Petri nets (CPN) are a variant which enables a more concise representation with the same modelling power. This paper develops a model for simulation of AMS whose correctness can be formally established, and which can be graphically represented and visually understood. It presents a modelling approach for AMS, based on a modified version of CPN, with enhanced modelling power. The proposed modifications result in highly compact graphical representations, and also render the model dynamic, i.e. capable of changing dynamically to reflect currently selected system parameters. These features make the proposed model ideally suited for discrete event simulation.