his.sePublications
Change search
Refine search result
1 - 3 of 3
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Wang, Lihui
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Givehchi, Mohammad
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Adamson, Göran
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Holm, Magnus
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    A sensor-driven 3D model-based approach to remote real-time monitoring2011In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 60, no 1, p. 493-496Article in journal (Refereed)
    Abstract [en]

    This paper presents an integrated approach for remote real-time monitoring of manufacturing operations. It is enabled by using virtual 3D models driven by real sensor data. The objectives of this research are twofold: (1) to significantly reduce network traffic for real-time monitoring over the Internet: and (2) to increase the controllability of manufacturing systems from anywhere in a decentralised environment. Particularly, this paper covers the principle of the approach, system architecture, prototype implementation, and a case study of remote control of a robotic assembly cell. Compared with camera-based monitoring systems, our approach only consumes less than 1% of its network bandwidth, feasible and practical as a web-based portable solution. (C) 2011 CIRP.

  • 2.
    Wang, Lihui
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Holm, Magnus
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Adamson, Göran
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Embedding a process plan in function blocks for adaptive machining2010In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 59, no 1, p. 433-436Article in journal (Refereed)
    Abstract [en]

    This paper presents a function block enabled approach towards adaptive process planning and machining. A two-layer structure of supervisory planning and operation planning is proposed to separate generic data from machine-specific ones. The supervisory planning is only performed once, in advance, at the shop level to generate machine-neutral process plans, whereas the operation planning is carried out at runtime at the machine level to determine machine-specific operations. Such adaptive decision making is facilitated by event-driven algorithms embedded in the function blocks. It is expected that the new approach can greatly enhance the dynamism of fluctuating job-shop machining operations.

  • 3.
    Wang, Lihui
    et al.
    Department of Production Engineering, KTH Royal Institute of Technology, Sweden.
    Wang, Wei
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Department of Production Engineering, KTH Royal Institute of Technology, Sweden.
    Liu, Dawei
    AVIC Chengdu Aircraft Industrial (Group) Ltd. Co., China.
    Dynamic feature based adaptive process planning for energy-efficient NC machining2017In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 66, no 1, p. 441-444Article in journal (Refereed)
    Abstract [en]

    This paper presents a dynamic feature based adaptive process planning approach that can optimise machining cost, machining time and energy consumption simultaneously. The material removal volume of a dynamic feature is refined into non-overlapping volumes removed respectively by a single machining operation in which unified cutting mode is performed. Benefitting from this refinement, energy consumption is estimated analytically based on instantaneous cutting force as a function of real cutting parameters. Moreover, the cutting parameters assigned to each machining operation are optimised effectively in the unified cutting mode. This novel approach enhances the energy efficiency of NC machining through process planning.

1 - 3 of 3
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf