Using Taguchi methods to determine/optimize robot process capability for path following

C. M. Wu; J. T. Black; B. C. Jiang

doi:10.1016/0736-5845(91)90003-B

Using Taguchi methods to determine/optimize robot process capability for path following

C. M. Wu
, J. T. Black
, B. C. Jiang

Department of Business Management

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

A methodology based on Taguchi methods was implemented to determined/optimize robot process capability (RPC) for path following. The methodology consists of the characterization of the robot path data, the experimental design, the data analysis procedure, and the verification of the results. Four figures of merit (FOMs) for accuracy and four FOMs for repeatability were used to characterize a robot's controlled path capability. The experiment considered seven controllable factors (i.e. load, speed, shape, size, direction, orientation, and height) and used an L₂₇(3¹³) orthogonal array. From the results of the data analysis, the optimal factor-level combinations for the best path capability and minimum process variation were determined. The experimental runs were verified. The recommended methodology has the advantages of cost effectiveness, efficiency, data compression, and flexibility.

Original language	English
Pages (from-to)	9-25
Number of pages	17
Journal	Robotics and Computer-Integrated Manufacturing
Volume	8
Issue number	1
DOIs	https://doi.org/10.1016/0736-5845(91)90003-B
State	Published - 1991

Bibliographical note

Funding Information:
Acknowledgements--This project was supported by National Science Foundation Grant No. DMC-8519778 and the Advanced Manufacturing Technology Center at Auburn University. Special thanks go to Mary Jo Mykytka and Dana Garrett for the preparation of this manuscript.

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10.1016/0736-5845(91)90003-B

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title = "Using Taguchi methods to determine/optimize robot process capability for path following",

abstract = "A methodology based on Taguchi methods was implemented to determined/optimize robot process capability (RPC) for path following. The methodology consists of the characterization of the robot path data, the experimental design, the data analysis procedure, and the verification of the results. Four figures of merit (FOMs) for accuracy and four FOMs for repeatability were used to characterize a robot's controlled path capability. The experiment considered seven controllable factors (i.e. load, speed, shape, size, direction, orientation, and height) and used an L27(313) orthogonal array. From the results of the data analysis, the optimal factor-level combinations for the best path capability and minimum process variation were determined. The experimental runs were verified. The recommended methodology has the advantages of cost effectiveness, efficiency, data compression, and flexibility.",

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Using Taguchi methods to determine/optimize robot process capability for path following

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