Cloud manufacturing service platform for small- and medium-sized enterprises

Huang, Biqing; Li, Chenghai; Yin, Chao; Zhao, Xinpei

doi:10.1007/s00170-012-4255-4

Cited by 167 publications

(76 citation statements)

References 51 publications

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“…In the monitoring of non-functional aspects, the service collaborative monitoring method based on dynamic AOP technology is collect all kinds of situation information, including the statistical service called time, service execution reliability, etc [14].…”

Section: ) Situational-oriented Monitoring and Adaptive Recovery Mecmentioning

confidence: 99%

“…In recent decades, many experts and scholars, as well as enterprises themselves from all over the world, have been devoted to exploring and studying how to solve the problem of a lack of capital, technology, personnel and equipment, so as to improve their business management model [1]. In order to improve the intangible assets and comprehensive competitiveness of enterprises, we propose an idea that transforms a vertical department management based on the principle of "division of labor" and "institutionalized management theory" into business process management based on cloud manufacturing (CMfg) in this paper [2].…”

Section: Introductionmentioning

confidence: 99%

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Modeling and Analysis of 3d Printing Ws-Bpel Business Processes Based on Servicenet

et al. 2017

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Abstract-To solve the problem that whether the described Web service by business process execution language were interactive compatible, a method of WS-BPEL(Web Services Business Process Execution Language) parsing and execution was proposed. The service compatibility checking algorithm based on the Mediation model, which can provide multi-level service checking compatibility, and realize the goal of Service Cooperation or the demand of ValueAdded Services. Based on BPMN specification, a task modeling and management tool was proposed to support the service components for assembly component. It supports both Web service automatic retrieval and service content analysis based on QoS information, and the task execution model between the BPMN specification task descriptions was transformed into the BPEL specification task description model. Finally, a model transformation strategy based on meta-model mapping was put forward. The algorithm was designed and examples were given to demonstrate the efficiency of 3D Printing WS-BPEL. 1Introduction

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Section: ) Situational-oriented Monitoring and Adaptive Recovery Mecmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling and Analysis of 3d Printing Ws-Bpel Business Processes Based on Servicenet

et al. 2017

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“…The formal operation process to complete a customer request in MC is presented in Figure 1. As seen in Figure 1, if the request is too large for an enterprise to complete it (e.g., the request requires various resources or a lot of resources), MC finds and selects two or more enterprises and composes a network of enterprises [8]. Cloud manufacturing is defined by many researchers: Xu [9] defined CM as "a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable manufacturing resources (e.g., manufacturing software tools, manufacturing equipment, and manufacturing capabilities) that can be rapidly provisioned and released with minimal management effort or service provider interaction".…”

Section: Introductionmentioning

confidence: 99%

The Dynamic Enterprise Network Composition Algorithm for Efficient Operation in Cloud Manufacturing

2016

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Abstract:As a service oriented and networked model, cloud manufacturing (CM) has been proposed recently for solving a variety of manufacturing problems, including diverse requirements from customers. In CM, on-demand manufacturing services are provided by a temporary production network composed of several enterprises participating within an enterprise network. In other words, the production network is the main agent of production and a subset of an enterprise network. Therefore, it is essential to compose the enterprise network in a way that can respond to demands properly. A properly-composed enterprise network means the network can handle demands that arrive at the CM, with minimal costs, such as network composition and operation costs, such as participation contract costs, system maintenance costs, and so forth. Due to trade-offs among costs (e.g., contract cost and opportunity cost of production), it is a non-trivial problem to find the optimal network enterprise composition. In addition, this includes probabilistic constraints, such as forecasted demand. In this paper, we propose an algorithm, named the dynamic enterprise network composition algorithm (DENCA), based on a genetic algorithm to solve the enterprise network composition problem. A numerical simulation result is provided to demonstrate the performance of the proposed algorithm.

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“…Enterprises are trying to gain competitive advantage in global markets by using the latest technologies, along with advanced networks, to create collaboration (Huang et al, 2013;Zhang et al, 2014;.…”

Section: Introductionmentioning

confidence: 99%