Roundness inspection strategies for machine visions using non-linear programs and genetic algorithms

Mu-Chen Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

This study proposes the inspection strategies of computational metrology for roundness measurement and roundness feasibility analysis with respect to ANSI Y14.5M-1994 standard. The roundness measurements are formulated as constrained non-linear programs, and optimization techniques are applied to locate the optimality. Through reformulating the geometric conditions and adding further constraints to the roundness measurement problems, the analysis of roundness inspection can be made by only investigating the feasibility of the constrained non-linear programs instead of advancing to the optimality. Two approaches of computational metrology based on genetic algorithms (GAs) are proposed to explore the optimality of roundness measurements and the roundness feasibility analysis, respectively. Finally, real data generated from machine visions and simulation data generated from analytical curves are used to test the proposed GA-based roundness assessment approaches. The experimental results indicate that the proposed algorithms are practical for on-line implementation to the roundness measurement and roundness feasibility analysis. Furthermore, the proposed computational strategy for the roundness feasibility analysis performs efficiently if the tolerance size is adequately specified and the process capability is stable.

Original languageEnglish
Pages (from-to)2967-2988
Number of pages22
JournalInternational Journal of Production Research
Volume38
Issue number13
DOIs
StatePublished - 1 Jan 2000

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