Modeling of Resources Capability for Manufacturing Equipments in Cloud Manufacturing

2012 ◽  
Vol 271-272 ◽  
pp. 447-451 ◽  
Author(s):  
Yuan Yuan Zhao ◽  
Quan Liu ◽  
Wen Jun Xu ◽  
Lu Gao
Keyword(s):  
Web Service ◽  
Cloud Manufacturing ◽  
Enterprise Group ◽  
Functional Capability ◽  
Manufacturing Equipment ◽  
Service Platform ◽  
Production Capability ◽  
Manufacturing Capability ◽  
Proposed Model ◽  
Functional Attribute

Being a kind of actual resources, manufacturing equipment resources (MERs) need to be virtualized and encapsulated into services. Our proposed works mainly focus on manufacturing capability of MERs that is consisted of two aspects: static functional capability and dynamic production capability, and relationship between related concepts so as to model MERs by ontology web language (OWL) that is based on semantic. In this paper, firstly, ontology based methodology within manufacture field is developed according to cloud manufacturing characters. Secondly, manufacturing capability is studied from functional attribute capability and production capability, then, the related concepts classes and relationship are analyzed, with the special properties defined to describe these classes based on semantic. Thirdly, the built in model is described by OWL (ontology web language) using protégé tool and an instance of MER is built based on the proposed model to express its manufacturing capability. Finally, this model is applied to Cloud MERs service platform, which is constructed for a given enterprise group, to provide MERs services. Moreover, Web Service is used in the platform to realize the sharing of the provided services.

Research on Mass Manufacturing Resource Sensory Data Management Based on Hadoop

2016 ◽  
Vol 693 ◽  
pp. 1880-1885 ◽  
Author(s):  
Kai Kai Su ◽  
Wen Sheng Xu ◽  
Jian Yong Li
Keyword(s):  
Distributed Storage ◽  
Cloud Manufacturing ◽  
Distributed File System ◽  
Service Platform ◽  
Sensory Data ◽  
Computing Model ◽  
Hadoop Distributed File System ◽  
Manufacturing Resource ◽  
Manufacturing Resources ◽  
Management Method

Aiming at the management issue of mass sensory data from the manufacturing resources in cloud manufacturing, a management method for mass sensory data based on Hadoop is proposed. Firstly, characteristics of sensory data in cloud manufacturing are analyzed, meanings and advantages of Internet of Things and cloud computing are elaborated. Then the structure of the cloud manufacturing service platform is proposed based on Hadoop, the information model of manufacturing resources in cloud manufacturing is defined, and the data cloud in the cloud manufacturing service platform is designed. The distributed storage of mass sensory data is implemented and a universal distributed computing model of mass sensory data is established based on the characteristics of Hadoop Distributed File System (HDFS).

Dynamic Manufacturing Capability Assessment of Industrial Robots Based on Feedback Information in Cloud Manufacturing

2017 ◽  
Author(s):  
Zeyu Zhang ◽  
Wenjun Xu ◽  
Quan Liu ◽  
Zude Zhou ◽  
Duc Truong Pham
Keyword(s):  
Manufacturing Industry ◽  
Dynamic Assessment ◽  
Cloud Manufacturing ◽  
Industrial Robots ◽  
Assessment Model ◽  
Advanced Technology ◽  
Distribution Model ◽  
Information Feedback ◽  
Optimal Solutions ◽  
Manufacturing Capability

With the development of information and computer network technology, cloud manufacturing has been developing rapidly, industrial robots (IRs) as a vital symbol and an advanced technology of manufacturing industry, in scheduling service, the constantly changing information data will result in the corresponding vary of the manufacturing capability. Under a fixed constraint of some capability service request, this will decrease the number of the optimal solutions and provide the inaccurate service to users. So it is important to make the manufacturing capability stable and obtain more optimal solutions to satisfy the constraint, thus the dynamic assessment of manufacturing capability based on information feedback is investigated in this paper. A set of indicators is established considering the IRs’ manufacturing capability and a new dynamic assessment model is proposed to achieve the actual data and the expected data information feedback, using the “normal distribution” model, which can correct the assessment weight. By the way, a case study is simulated in the MATLAB, which shows the reliability and reasonability of this method in evaluate the manufacturing capability in IR.

CLUeFARM: Integrated web-service platform for smart farms

2018 ◽  
Vol 154 ◽  
pp. 134-154 ◽  
Author(s):  
Madalin Colezea ◽  
George Musat ◽  
Florin Pop ◽  
Catalin Negru ◽  
Alexandru Dumitrascu ◽  
...  
Keyword(s):  
Web Service ◽  
Service Platform

A Practical Approach to Enhancement of Accuracy of Similarity Model Using WordNet towards Semantic Service Discovery

2014 ◽  
pp. 245-265
Author(s):  
Chellammal Surianarayanan ◽  
Gopinath Ganapathy ◽  
Manikandan Sethunarayanan Ramasamy
Keyword(s):  
Web Service ◽  
Service Discovery ◽  
Service Providers ◽  
Computation Time ◽  
Proposed Model ◽  
Similarity Model ◽  
Domain Ontologies ◽  
Semantic Service ◽  
General Ontology ◽  
Semantic Web Service Discovery

Semantic Web service discovery provides high retrieval accuracy. However, it imposes an implicit constraint to service clients that the clients must express their queries with the same domain ontologies as used by the service providers. Fulfilling this criterion is very tedious. Hence, a WordNet (general ontology)-based similarity model is proposed for service discovery, and its accuracy is enhanced to a level comparable to the accuracy of computing similarity using service specific ontologies. This is done by optimizing similarity threshold, which refers to a minimum similarity that is required to decide whether a given pair of services is similar or not. The proposed model is implemented and results are presented. The approach warrants clients to express their queries without specifying any ontology and alleviates the problem of maintaining complex domain ontologies. Moreover, the computation time of WordNet-based model is very low when compared to specific ontology-based model.

Trapping Runtime Faults from Web Service Fault Ontology

2020 ◽  
Vol 17 (8) ◽  
pp. 3759-3764
Author(s):  
K. Jayashree
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Users ◽  
Intended Behavior ◽  
Proposed Model ◽  
Different Types ◽  
Service Application ◽  
Common Understanding ◽  
Types Of Faults ◽  
The Web

The ontology offers a clear considerate of the runtime faults in web services and helps to share this common understanding with users and applications. This paper presents Web Service Fault Ontology and to trap the runtime faults from the Web Services Fault Ontology. Web Service Fault Ontology has been developed to represent the different types of faults that can occur during the interactions between service users, service publishers and service registries: publishing, discovery, binding and execution of web services. Ontology has been proposed to define the intended behavior of web services from the service provider. A sample web service application was developed for testing the proposed model.

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