Manufacturing Grid System Research Articles

An Algorithm of Attribute Reduction Based on Granular Computing in Manufacturing Grid System

An Algorithm of Attribute Reduction Based on Granular Computing in Manufacturing Grid System

A service oriented manufacturing grid system with uncertain information

Purpose – The increase in demand variability created by manufacturing enterprises presents new challenges for increasing resource usage and sharing flexibility. For this reason, it is of great importance to research manufacturing grids and their service modes. The purpose of this paper is to establish a systematic strategy and a system tool for manufacturing grid systems. Design/methodology/approach – A manufacturing service oriented manufacturing grid (MSoMG) system is presented with open grid service architecture as the system architecture and GT3.9 as a development tool. A framework is proposed to support MSoMG by providing advisory tools and methods for uncertain information analysis and processing, multi-objective decision making of manufacturing grid service execution, manufacturing grid service performance prediction based on knowledge template, and flexible manufacturing grid service scheduling and solution. The methodology of the adopted rough set is discussed in detail. Finally, the design support strategies for MSoMG are investigated to guide the coordination of manufacturing activities. Findings – Many conventional methods and models become very limited for manufacturing grid service with uncertain information. The processing of uncertain information and reasonable application flow can help to improve the completion rate and reliability of manufacturing grid services. Practical implications – This research provides a solid foundation for manufacturing gird operations and can promote the use of a manufacturing grid mode. Originality/value – A MSoMG system is presented. The manufacturing grid service with uncertain information is considered as well as design support strategies.

A hybrid chaotic quantum evolutionary algorithm for resource combinatorial optimization in manufacturing grid system

Resource composition in manufacturing grid (MGrid) system is one of the recent critical issues of MGrid researches. Especially, resource combinatorial optimization (RCO) becomes more challenging when multiple optimal criteria are considered in MGrid system. Based on the quantum evolution theory, we propose a hybrid chaotic quantum evolutionary algorithm (CQEA) for RCO problems. We also propose a novel resource encoding method for CQEA, which is dynamic and flexible. The experimental results show that the proposed CQEA is effective, efficient, and scalable for the RCO problem in MGrid system.

Search Technology of Resource Service in Manufacturing Grid Based on Ant Colony Optimization Algorithm

In Manufacturing Grid (MG) system, there are primarily two kinds of users: resource service consumer and resource service provider. For a resource service request task, the MG system should search the services which are qualified for the requirements of consumer and then choose the optimal one to execute it. In according to the distributed system structure of MG and node routing model influenced by several factors (e.g., time minimization, cost minimization, bandwidth minimization), the searching technology based on web service technology and ant colony optimization (ACO) algorithm has been proposed in this paper. The basic evaluation models and formulations are described, and then the algorithms are presented to minimize the expenses. The experimental results also show that the proposed method is useful in solving the searching problems in MG system.

Resource service optimal-selection based on intuitionistic fuzzy set and non-functionality QoS in manufacturing grid system

In manufacturing grid (MGrid) system, according to functional requirements of a task, there exist a lot of resource services which have similar functional characteristics. Multiple resource services with similar functional characteristics raise the concern over resource service optimal-selection (RSOS). It is important to select the optimal resource service according to their non-functionality characteristics or quality of service (QoS). However, QoS attributes are not easy to measure due to their complexity and involvement of ill-structured information. In this study, user’s feeling is taken into account in RSOS in an MGrid system. The non-functionality QoS evaluation of resource services is based on users’ feeling and transaction experiences using intuitionistic fuzzy set (IFS). Furthermore, the dynamics of non-functionality QoS is considered, and a time-decay function is introduced into non-functionality QoS evaluation. A new method is proposed for RSOS based on IFS and non-functionality QoS, and the procedures are presented in detail. A practice case study is used to illustrate the proposed method and procedure. The performance and advantage of the proposed method are discussed.

Research on co-reservation in the manufacturing grid system

According to the features of manufacturing grid (MGrid) resources, some resources should be reserved jointly to schedulers before executing a complex MGrid task. We define it as a co-reservation. In order to support co-reservation, we design a framework, a workflow, and a series of application programming interfaces of co-reservation in the MGrid system. The processing of co-reservation requests may be expensive due to a number of cell reservations, the complex relationships, and the large number of eligible resources in the MGrid system. In this paper, the processing of co-reservation requests is transferred to the subgraph isomorphism problem and an improved algorithm is introduced to solve it efficiently. Finally, we implement a prototype of co-reservation in the magnetic bearing resource and service sharing platform under MGrid. The experiment results show that the improved algorithm is effective to co-reservation.

Application and modeling of resource service trust-QoS evaluation in manufacturing grid system

Resource scheduling is the bottleneck in MGrid; the current research on resource scheduling strategy is mainly based on resource performance-QoS (quality of service), but the factor of trust-QoS is ignored, which will result in unreasonable and unpractical scheduling results. In order to enhance the validity and success rate of resource scheduling in a manufacturing grid (MGrid) system, provide high credible resource service abilities and results to the user, the concept of resource service trust-QoS is presented; trust-QoS was introduced into MGrid resource service scheduling and the important roles it plays emphasized. The trust problems existing in the resource service transaction between resource service demanders (RSD) and resource service providers (RSP) are put forward. The trust-QoS relationship model which is capable of capturing a comprehensive range of trust relationships which exist in the MGrid system is put forward. Then a two-layer resource service trust-QoS evaluation model is put forward, including an intra-domain trust-QoS evaluation model and an inter-domain trust-QoS evaluation model. The quantitative evaluating algorithms of trust-QoS degree value are proposed and described in detail, as well as the value of real-time and dynamic updating algorithms of trust-QoS degree. Finally, an application prototype, namely MBRSPP-MGrid, is developed. The experimental results of the case study show that the proposed models and algorithms are effective and useful.

Resource Service Composition and Its Optimal-Selection Based on Particle Swarm Optimization in Manufacturing Grid System

In distributed manufacturing systems, especially in a manufacturing grid (MGrid) system, there are primarily two kinds of manufacturing tasks (or resource service requests): (1) single resource service request task (SRSRTask), which can be completed by invoking only one resource service, and (2) multi-resource service request task (MRSRTask), which is completed by invoking several resource services in a certain sequence. For an SRSRTask, the system searches the resource services that are qualified for its function requirements and chooses the optimal one to execute it. For an MRSRTask, in addition to the search for all qualified resource services according to each subtask, the system selects one candidate resource service for each subtask. Then the system generates a new composite resource service (CRS) and selects the optimal resource service composite path from all possible paths to execute the task with the given multi-objective (e.g., time minimization, cost minimization, and reliability maximization) and constraints. The above problem is defined as multi-objective MGrid resource service composition and optimal-selection (MO-MRSCOS) problem in this paper. The formulation is presented for an MO-MRSCOS problem to minimize execution time and cost, and maximize the reliability. The basic resource service composite modes (RSCM) for CRS are described, and the principles for translating a complicated RSCM into a simple sequence RSCM are presented for simplifying the resolving process and complexity of MO-MRSCOS. A new MGrid resource service composition and optimal-selection method, based on the principles of particle swarm optimization (PSO), is then proposed. The PSO follows a collaborative population-based search, which models based on the social behavior of bird flocking and fish schooling. The case study demonstrates that the proposed method is useful in solving MO-MRSCOS problems. The experimental results and performance comparison show that the proposed method is both effective and efficient.

Study of failure detection and recovery in manufacturing grid resource service scheduling

A Manufacturing Grid (MGrid) system is different from a conventional distributed computing system due to its focus on larger-scale, distributed and heterogeneous manufacturing resource and service sharing, including equipment resources, application system resources, material resources, technical resources, public service resources, etc., where remote resource service scheduling (e.g., remote accessing, information communication) has a large influence on the MGrid quality of service (QoS). The probability of failure is higher in MGrid resource service scheduling and failures affect task execution and the quality of service of the MGrid fatally. Therefore, this paper focuses on failures in the MGrid resource service scheduling process. The potential failures that can occur during MGrid resource service scheduling are investigated. Thirteen failures are first defined in detail and are classified into four categories: (a) virtual-link-related failures, (b) resource-service-related failures, (c) task-related failures, and (d) application-related failures. A failure management system of the MGrid system is presented associated with its architecture. Corresponding detection mechanisms and methods for each defined failure are presented in detail, as well as the corresponding failure recovery methods. The implementation and simulation results indicate that our approaches are sound for promoting a successful scheduling rate and shortening the total execution time of the MGrid resource service.

Study on resource service match and search in manufacturing grid system

Resource service match and search (RSMS) is the core to realize manufacturing grid (MGrid) resource scheduling. In order to realize effectively RSMS between resource demanders and providers, a RSMS framework is proposed and the key technologies to realize it are studied. The describing information of resource services are classified into four categories: (a) word concept information, (b) sentence information, (c) number information, including number interval and fuzzy number, and (d) entity class (or data structure) information. The similarity matching algorithms of each kind of describing information are investigated, respectively, including word matching algorithms, sentence matching algorithms, number matching algorithms, and entity class matching algorithms. Based on the proposed matching algorithms, the match and search processes of MGrid resource services are divided into four phases: first, matching the basic information of resource services, such as service name and service description, namely, basic matching; second, matching the inputs and outputs information of resource services, namely, I/O matching; third, matching the quality of service (QoS) information of resource services, namely QoS matching; last, combining the above three matching results and generating an integrated matching result, namely, integrated matching. The matching functions and algorithms of each phase are described in detail. A case study illustrates the application of proposed methods, and the accuracy and efficiency of the proposed method are measured.

Multilevel manufacturing system of virtual enterprise based on manufacturing grid and strategies for member enterprise selection and task assignment

In order to improve efficiency of virtual enterprise, a manufacturing grid and multilevel manufacturing system of virtual enterprise is built up. When selecting member enterprises and task assignment based on the manufacturing grid, key activities are assigned to the suitable critical member enterprises by task decomposition, enterprise node searching and characteristic matching of manufacturing resources according to the characteristic matching strategy. By task merger, some ordinary activities are merged with corresponding key activities and assigned to corresponding critical member enterprises. However, the other ordinary activities are assigned to the related ordinary member enterprises with enterprise node searching and characteristic matching of manufacturing resources. Finally, an example of developing the artificial hip joint in the virtual enterprise is used to demonstrate that efficiency of the virtual enterprise is improved by using the manufacturing grid and the proposed strategies for member enterprise selection and task assignment.