Prediction Experiments for Reliability of Machine Tool by Product Performance Data

DOI

10.2991/emcm-15.2016.58How to use a DOI?

Keywords

Prediction; Reliability; Machine tool; Measurement uncertainty; Fuzzy set theory.

Abstract

For processing mass high quality products, it is crucial that the machine tool can keep a good running in the manufacturing process. In order that the product percent of pass is up to the standard of production, it needs to predict the reliability of the machine tool as soon as possible, which belongs to the probability distribution unknown. Based on the fuzzy set theory, prediction experiments for the reliability of the machine tool by product performance data can be realized. Prediction experiment of judging the reliability of the machine tool shows that under the confidence level P = 95.44%, if the relative error of the measurement uncertainty of the experimental data is not more than 45%, the machine tool is reliable; otherwise, the machine tool is not reliable. Prediction experiment of evaluating the reliability of the machine tool shows that it can be accurately predicted the reliability of the machine tool according to the fuzzy set theory.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xintao Xia
AU  - Wenhuan Zhu
AU  - Zhen Chang
PY  - 2016/02
DA  - 2016/02
TI  - Prediction Experiments for Reliability of Machine Tool by Product Performance Data
BT  - Proceedings of the International Conference on Electronics, Mechanics, Culture and Medicine
PB  - Atlantis Press
SP  - 309
EP  - 313
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcm-15.2016.58
DO  - 10.2991/emcm-15.2016.58
ID  - Xia2016/02
ER  -