Modeling Pinhole Phenomenon in Sanitary Porcelains Case Study: Isatis Sanitary Porcelain Plant, Yazd, Iran

DOI

10.2991/jsta.2018.17.3.11How to use a DOI?

Keywords

sanitary porcelain; pinhole; artificial neural networks; regression; correlation coefficient

Abstract

Sanitary porcelain products might have several defects, causing potential high-grade desirable products be converted into low-grade ones. Some of the defects are such that a few of them in the products will result in a great fall of product rating and consequently reduction of its value and price. Among these defects is a defect called pinhole. In this article, it has been tried to identify, from a list of factors, the most influential factors of the production process which cause the pinhole defect affecting the product rating. It then tries to present a prediction model for the number of pinholes. For this purpose, initially seven factors were chosen to help presenting a suitable prediction model and several statistical tools and artificial intelligence prediction tools were investigated to present a suitable prediction model. The presented model could be used by the company to enhance the product rating through choosing right value for the right factors causing the pinhole defect and to decrease the wastes and the expenditures.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

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

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TY  - JOUR
AU  - H. Bazargan
AU  - A. Dehghanzadeh
PY  - 2018
DA  - 2018/09/30
TI  - Modeling Pinhole Phenomenon in Sanitary Porcelains Case Study: Isatis Sanitary Porcelain Plant, Yazd, Iran
JO  - Journal of Statistical Theory and Applications
SP  - 572
EP  - 586
VL  - 17
IS  - 3
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.2018.17.3.11
DO  - 10.2991/jsta.2018.17.3.11
ID  - Bazargan2018
ER  -