Optimal variable screening in automotive crankshaft remanufacturing process using statistical pattern recognition approach in the Mahalanobis-Taguchi system

Wan Zuki Azman Wan Muhamad, Khairur Rijal Jamaludin, Mohd Nabil Muhtazaruddin, Zainor Ridzuan Yahya, Faizir Ramlie, N. Harudin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The Mahalanobis-Taguchi System (MTS) refers to a newly-developed technique based on statistics that integrates a number of mathematical concepts to be applied for classification and diagnosis purposes within systems that are comprised of multiple dimensions. The MTS has been proven to be an exceptional technique that can be employed in numerous fields. In MTS, it is essential to choose the variables in order to enhance the accuracy in classifying via orthogonal array (OA) and Signal-to-Noise (S/N) ratios. However, the penalty for over-fitting or regularization is not included in the feature selection process for the MTS classifier. Hence, this paper investigated the combination between MTS and statistical pattern recognition approach applied to automotive crankshaft remanufacturing as an automated decision-making tool for classification purposes. The outcomes revealed that MTS displayed better classification performance for both training and test datasets, besides eliminating redundant and irrelevant parameters better than the conventional approach did.

Original languageEnglish
Title of host publicationProceeding of the International Conference on Mathematics, Engineering and Industrial Applications 2018, ICoMEIA 2018
EditorsShazalina Mat Zin, Nur' Afifah Rusdi, Khairul Anwar Bin Mohamad Khazali, Nooraihan Abdullah, Nurshazneem Roslan, Noor Alia Md Zain, Rasyida Md Saad, Nornadia Mohd Yazid
PublisherAmerican Institute of Physics Inc.
ISBN (Print)9780735417298
DOIs
Publication statusPublished - 02 Oct 2018
EventInternational Conference on Mathematics, Engineering and Industrial Applications 2018, ICoMEIA 2018 - Kuala Lumpur, Malaysia
Duration: 24 Jul 201826 Jul 2018

Publication series

NameAIP Conference Proceedings
Volume2013
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Other

OtherInternational Conference on Mathematics, Engineering and Industrial Applications 2018, ICoMEIA 2018
CountryMalaysia
CityKuala Lumpur
Period24/07/1826/07/18

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

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    Muhamad, W. Z. A. W., Jamaludin, K. R., Muhtazaruddin, M. N., Yahya, Z. R., Ramlie, F., & Harudin, N. (2018). Optimal variable screening in automotive crankshaft remanufacturing process using statistical pattern recognition approach in the Mahalanobis-Taguchi system. In S. M. Zin, N. A. Rusdi, K. A. B. M. Khazali, N. Abdullah, N. Roslan, N. A. M. Zain, R. M. Saad, & N. M. Yazid (Eds.), Proceeding of the International Conference on Mathematics, Engineering and Industrial Applications 2018, ICoMEIA 2018 [020031] (AIP Conference Proceedings; Vol. 2013). American Institute of Physics Inc.. https://doi.org/10.1063/1.5054230