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

[+] Author Affiliations
Zeyu Zhang, Wenjun Xu, Quan Liu, Zude Zhou

Wuhan University of Technology, Wuhan, China

Duc Truong Pham

University of Birmingham, Birmingham, UK

Paper No. MSEC2017-2704, pp. V003T04A027; 6 pages
  • ASME 2017 12th International Manufacturing Science and Engineering Conference collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing
  • Volume 3: Manufacturing Equipment and Systems
  • Los Angeles, California, USA, June 4–8, 2017
  • Conference Sponsors: Manufacturing Engineering Division
  • ISBN: 978-0-7918-5074-9
  • Copyright © 2017 by ASME


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.

Copyright © 2017 by ASME



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