Exploring the state-of-the-art service composition approaches in cloud manufacturing systems to enhance upcoming techniques
| Autor: | Vahideh Hayyolalam, Ali Asghar Pourhaji Kazem, Behrouz Pourghebleh, Ali Ghaffari |
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| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Media management Computer science Mechanical Engineering Quality of service 02 engineering and technology Service composition Data science Manufacturing services Industrial and Manufacturing Engineering Field (computer science) Computer Science Applications Task (project management) 020901 industrial engineering & automation Control and Systems Engineering Selection (linguistics) State (computer science) Industrial and production engineering Cloud manufacturing Software |
| Zdroj: | The International Journal of Advanced Manufacturing Technology. 105:471-498 |
| ISSN: | 1433-3015 0268-3768 |
| DOI: | 10.1007/s00170-019-04213-z |
| Popis: | Cloud manufacturing (CMfg) is a new paradigm that has been known as a promising integrated technology in which distributed resources of manufacturing are integrated and transformed into manufacturing services and handled centrally. It permits multiple users to request services simultaneously by submitting required tasks to a manufacturing platform. The service composition and optimal selection (SCOS) is the fundamental issue of CMfg that aims to select appropriate services from available manufacturing cloud resources to complete the manufacturing task and satisfy the users. Surveying and analyzing the available studies on this NP-hard problem is highly desirable. Therefore, as far as we know, this paper is the first research that tries to investigate and discuss the CMfg-SCOS methods in a systematic way. In this regard, the selected studies have been classified into two distinct groups comprising multi-objective and single-objective techniques. Furthermore, this research provides a comprehensive investigation of the current articles and compares them from several aspects based on various factors such as QoS parameters, other criteria, their adopted datasets, simulation tools, and algorithms. Moreover, hot papers, journals, and authors in this field have been revealed. In addition, the open challenging and the lacks within this issue have been discussed which can be applied to upcoming research. |
| Databáze: | OpenAIRE |
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