A robust optimization approach using Taguchi's loss function for solving nonlinear optimization problems

Balaji Ramakrishnan, S. S. Rao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The application of the concept of robust design, based on Taguchi’s loss function, in formulating and solving nonlinear optimization problems is investigated. The effectiveness of the approach is illustrated with two examples. The first example is a machining parameter optimization problem wherein the production cost, tool life and production rate are optimized with limitations on machining characteristics such as cutting power, cutting tool temperature and surface finish. The second example is a welded beam design problem where the dimensions of the weldment and the beam are found without exceeding the limitations stated on the shear stress in the weld, normal stress in the beam, buckling load on the beam and tip deflection of the beam. The results are highlighted by comparing the solutions of the robust formulation with those obtained from the conventional formulation. The methodology presented in this work is expected to be useful in the design of products and processes which are least sensitive to the noises and which reflect in higher quality.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence; Expert Systems; CAD/CAM/CAE; Computational Fluid/Thermal Engineering
PublisherAmerican Society of Mechanical Engineers (ASME)
Pages241-248
Number of pages8
ISBN (Electronic)9780791806227, 9780791897751
DOIs
StatePublished - 1991
EventASME 1991 Design Technical Conferences, DETC 1991 - Miami, United States
Duration: Sep 22 1991Sep 25 1991

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume1

Conference

ConferenceASME 1991 Design Technical Conferences, DETC 1991
CountryUnited States
CityMiami
Period9/22/919/25/91

ASJC Scopus subject areas

  • Mechanical Engineering
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Modeling and Simulation

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