Disassembly task evaluation by muscle fatigue estimation in a virtual reality environment

  • Jingtao ChenEmail author
  • Peter Mitrouchev
  • Sabine Coquillart
  • Franck Quaine


Today, disassembly operations play a very important role during the initial design phase of industrial products considering the role played by these operations throughout the product life cycle. Current simulation platforms do not offer the necessary information and versatility required for a complete disassembly process simulation, including human/operator physiological data management. The paper deals with a new method for disassembly sequence evaluation. It is based on metabolic energy expenditure and muscle fatigue estimation. For this purpose, the analytical model for mechanical energy expenditure is proposed. In this model, the required mechanical work is used as a parameter that allows comparing the relationships among fatigue levels when performing disassembly sequences. Then, the fatigue levels are evaluated by analyzing the recorded electromyography signal on an operator’s arm. The proposed method is validated by a set of experimental disassembly tests performed in a virtual reality environment. The comparison of the analytical and experimental results has shown good correlation between them. The main result of this study is the proposed model for assessing muscle fatigue and its validation by experimental procedure. The proposed method provides the feasibility to integrate human muscle fatigue into disassembly sequence evaluation via mechanical energy expenditure when performing disassembly operation simulations.


Disassembly sequences evaluation Muscle metabolic energy Mechanical energy Muscle fatigue Virtual reality environment 


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Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  • Jingtao Chen
    • 1
    • 2
    • 3
    • 4
    Email author
  • Peter Mitrouchev
    • 1
  • Sabine Coquillart
    • 2
    • 3
  • Franck Quaine
    • 4
  1. 1.Univ. Grenoble Alpes, CNRS, Lab. G-SCOPGrenobleFrance
  2. 2.INRIA–LIG MontbonnotSaint-IsmierFrance
  3. 3.Univ. Grenoble Alpes, CNRS, Lab, LIG GrenobleFrance
  4. 4.Univ. Grenoble Alpes, CNRS, Lab, GIPSA GrenobleFrance

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