Paper Info
Title
Task Decomposition Based On Cloud Manufacturing Platform
Abstract
As a new service-oriented manufacturing paradigm, cloud manufacturing (CMfg) realizes the optimal allocation of resources in the product manufacturing process through the network. Task decomposition is a key problem of the CMfg system for resource scheduling. A high-quality task decomposition method can shorten product development time, reduce costs for resource service providers, and provide technical support for the application of CMfg. However, a cloud manufacturing system has to manage the allocation the correct amount of manufacturing resources, complex production processes, and highly dynamic production environments. At the same time, the tasks issued by service demanders are usually asymmetric and tightly coupled. We solve the complex task decomposition problem by using the traditional methods, that are hard to complete in CMfg. To overcome the shortcomings of CMfg, this paper proposed a task decomposition method based on the cloud platform. For achieving modular production, this approach creatively divides the product production process into four stages: design, manufacturing, transportation, and maintenance. Then a hybrid method, which combines with depth-first search algorithm, fast modular optimization algorithm, and artificial bee colony algorithm, is introduced. The method can obtain a multi-stage task optimization decomposition plan in CMfg. Simulation results demonstrate the proposed method can achieve complex task optimization decomposition in a CMfg environment.
Year
DOI
Venue
2021
10.3390/sym13081311
SYMMETRY-BASEL
Keywords
DocType
Volume
cloud manufacturing, asymmetric, task decomposition, depth first search, fast modular, artificial bee colony
Journal
13
Issue
Citations 
PageRank 
8
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Yanjuan Hu142.43
Ziyu Zhang211210.19
Jinwu Wang300.34
Zhan-Li Wang432.09
Hongliang Liu500.68