Cloud manufacturing and simulation for complex products

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: closed (15 August 2022) | Viewed by 2211

Special Issue Editors


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Guest Editor
School of Automation Science and Electrical Engineering, Beihang Universiy, Beijing, China
Interests: service-oriented modeling and simulation; cloud manufacturing and simulation; model engineering and cyber-physical systems

E-Mail Website
Guest Editor
School of Automation Science and Electrical Engineering, Beihang Universiy, Beijing, China
Interests: configurable intelligent optimization algorithm; robot disassembly modeling and optimization for remanufacturing; pattern discovery and evaluation of multi-agent systems; and adaptive online incremental learning

Special Issue Information

Dear Colleagues,

As a service-oriented, networked, and intelligent manufacturing paradigm, cloud manufacturing maps are creating resources and capabilities for the cloud, using technologies such as cloud computing, Internet of Things, service computing, and artificial intelligence. This forms a cyber-physical-human system with interactions between virtual worlds and reality, which enables cloud-based sharing, collaboration, and on-demand use of manufacturing resources and capabilities, and provides intelligent, efficient on-demand services over the full lifecycle of manufacturing.

Modeling and simulation (M&S) technology plays an irreplaceable role during the development of manufacturing systems. M&S has been widely applied in all phases of the whole product lifecycle, i.e., design, manufacturing, testing, sales, maintenance, and other phases. Cloud-based environments and technologies bring more opportunities and challenges for the development of M&S technology, in return, M&S provides a more powerful capability for cloud manufacturing to complete a high-quality manufacturing task.

Topics of interest include but are not limited to the following:

  • Architecture, models, standards, and criteria for CMfg
  • Cloud service management of manufacturing resources and capabilities
  • M&S for manufacturing lifecycle in the cloud
  • M&S as a service
  • Cloud-edge collaborative manufacturing and simulation
  • New generation IT (big data, AI, cyber-physical system, Internet of Things, blockchain, etc.) for manufacturing and simulation
  • Model engineering for manufacturing
  • Simulation optimization in CMfg
  • Cloud-based M&S platform
  • Modeling and simulation language for complex product lifecycle
  • High-performance simulation and optimization

Prof. Dr. Lin Zhang
Dr. Yuanjun Laili
Guest Editors

Manuscript Submission Information

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Keywords

  • Cloud manufacturing
  • Modeling and simulation
  • Complex product lifecycle

Published Papers (1 paper)

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Research

14 pages, 6748 KiB  
Article
Matching of Manufacturing Resources in Cloud Manufacturing Environment
by Yanjuan Hu, Leiting Pan, Dongwei Gu, Zhanli Wang, Hongliang Liu and Yilin Wang
Symmetry 2021, 13(10), 1970; https://0-doi-org.brum.beds.ac.uk/10.3390/sym13101970 - 19 Oct 2021
Cited by 7 | Viewed by 1587
Abstract
With the introduction and application of new information technology in manufacturing, various advanced manufacturing models and national strategies have received more and more attention. The goal of cloud manufacturing is to closely link the resources and capabilities of manufacturers through a variety of [...] Read more.
With the introduction and application of new information technology in manufacturing, various advanced manufacturing models and national strategies have received more and more attention. The goal of cloud manufacturing is to closely link the resources and capabilities of manufacturers through a variety of services to create a dedicated platform for complex manufacturing process needs. How to achieve effective matching of various manufacturing resources and capabilities in the form of services will be a common problem in the future. In order to effectively improve cloud manufacturing tasks and resource matching efficiency and save resources, this study considers the common aspects of cloud manufacturing resource matching as service quality indicators, and extends the scope to the requirements of manufacturing resources, and the matching pattern of traditional service resources. There are additional restrictions on the resource service matching process. At the same time, the resource service matching is usually asymmetric. Therefore, we introduce the concept of task complexity of demand resources, and propose a combination system based on task complexity and service quality evaluation. The artificial bee colony algorithm (ABC) is used for analysis and verification. The experimental paper further validates the proposed the feasibility and efficiency of the method. Full article
(This article belongs to the Special Issue Cloud manufacturing and simulation for complex products)
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