A Bayesian Model of Machining Economics for Optimization by Adaptive ControlSource: Journal of Manufacturing Science and Engineering:;1970:;volume( 092 ):;issue: 003::page 628Author:Donald S. Ermer
DOI: 10.1115/1.3427825Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: A learning model of tool wear based on Bayesian statistical methods provides a means for regulating the optimum cutting conditions as periodic sampling data on flank wear become available during production under adaptive control. The sampling process is used to estimate the current parameters of the wear process, and by incorporating this updated information into the machining economics model, an optimal a posteriori program of cutting conditions can be determined to best match the current conditions of the tool, workpiece, and machine. The application of the Bayesian learning model is illustrated for a basic turning operation with minimum cost as the optimizing criterion.
keyword(s): Machining , Adaptive control , Economics , Optimization , Wear , Cutting , Sampling (Acoustical engineering) , Machinery AND Turning ,
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contributor author | Donald S. Ermer | |
date accessioned | 2017-05-09T00:41:43Z | |
date available | 2017-05-09T00:41:43Z | |
date copyright | August, 1970 | |
date issued | 1970 | |
identifier issn | 1087-1357 | |
identifier other | JMSEFK-27554#628_1.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/145057 | |
description abstract | A learning model of tool wear based on Bayesian statistical methods provides a means for regulating the optimum cutting conditions as periodic sampling data on flank wear become available during production under adaptive control. The sampling process is used to estimate the current parameters of the wear process, and by incorporating this updated information into the machining economics model, an optimal a posteriori program of cutting conditions can be determined to best match the current conditions of the tool, workpiece, and machine. The application of the Bayesian learning model is illustrated for a basic turning operation with minimum cost as the optimizing criterion. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | A Bayesian Model of Machining Economics for Optimization by Adaptive Control | |
type | Journal Paper | |
journal volume | 92 | |
journal issue | 3 | |
journal title | Journal of Manufacturing Science and Engineering | |
identifier doi | 10.1115/1.3427825 | |
journal fristpage | 628 | |
journal lastpage | 632 | |
identifier eissn | 1528-8935 | |
keywords | Machining | |
keywords | Adaptive control | |
keywords | Economics | |
keywords | Optimization | |
keywords | Wear | |
keywords | Cutting | |
keywords | Sampling (Acoustical engineering) | |
keywords | Machinery AND Turning | |
tree | Journal of Manufacturing Science and Engineering:;1970:;volume( 092 ):;issue: 003 | |
contenttype | Fulltext |