Multi-objective selection and structural optimization of the gantry in a gantry machine tool for improving static, dynamic, and

In this investigation, the multi­objective selection and optimization of a gantry machine tool  is  achieved  by  analytic  hierarchy  process,  multi­objective  genetic  algorithm,  and Pareto­Edgeworth­Grierson–multi­criteria  decision­making  method.  The  objectives include  maximum  static  deformation,  the  first  four  natural  frequencies,  mass,  and fabrication cost of the gantry. Further structural  optimization  of  the  best  configuration was  accomplished  using  multi­objective  genetic  algorithm  to  improve  all  objectives except cost. The result of sensitivity analysis reveals the major contribution of columns of  gantry  with  respect  to  the  crossbeam’s  contribution.  After  determining  the  most effective  geometrical  parameters  using  sensitivity  analysis,  multi­objective  genetic algorithm was performed to obtain the Pareto­optimal solutions. InÂ...

• Type: Journal
• Year: 2016
• Where: CERA
• Authors: S. R. Besharati, V. Dabbagh, H. Amini, Ahmed A. D. Sarhan, J. Akbari, M. Hamdi, Z. C. Ong
• Keywords: CERA 2016