Young Researcher Paper Award 2023
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Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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Sensors and Materials
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 35, Number 11(2) (2023)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 3607-3621
S&M3439 Research Paper https://doi.org/10.18494/SAM4689 Published: November 17, 2023 Application of Reliability and Quality Methods to Improving Mean Time Between Failures of Machine Tool Cooling System [PDF] Chun-Hao Chen and Kun-Ying Li (Received August 3, 2023; Accepted November 7, 2023) Keywords: reliability, MTBF, machine tool, cooling system
The thermal error of a machine tool can be regarded as an important index of machining accuracy. Such an error is reproducible and stable, meaning that machine tools can be easily maintained by thermal compensation, ensuring a long-term good machining quality. In this study, reliability engineering was applied to increase the mean time between failures (MTBF) of a cooling system to maintain the structure temperature and accuracy, and the MTBF was increased from 3787 h to more than 23041 h. In addition, the Taguchi method was used with the finite element method and multivariate regression analysis to obtain the optimal cooling conditions to reduce thermal deformation and stabilize the structure temperature. The variation of the temperature of the machine tool structure was improved from ±0.517 to ±0.367 ℃, a reduction of 29%.
Corresponding author: Kun-Ying Li  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Chun-Hao Chen and Kun-Ying Li, Application of Reliability and Quality Methods to Improving Mean Time Between Failures of Machine Tool Cooling System, Sens. Mater., Vol. 35, No. 11, 2023, p. 3607-3621. |
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