Analisis Pengukuran Produk HKZL PT.Gradien Manufaktur Indonesia Menggunakan Multivariat Gage, Repeatability and Reproducibility (GRR) Melalui Analisis Faktor


Selvi Marcelina(1*), Asep Solih Awalluddin(2), Arief Fathcul Huda(3), Rismawati Ramdani(4), Esih Sukaesih(5)

(1) ,  
(2) , Indonesia
(3) , Indonesia
(4) , Indonesia
(5) , Indonesia
(*) Corresponding Author

Abstract


Measurement data is often used in determining the quality of a product. Some of the results in measurement present multivariate properties, meaning that there are many characteristics of quality. Many variables are measured to be used as a reference in improving product quality on the company's predetermined standards. But in reality, there are variations in the size or size of products that do not meet the standard of measurement used by the company. In this case, the correlation structure between quality characteristics is often overlooked. Variables that correlate in a group, but with relatively small correlations between other groups are more suitable tasks for factor analysis. Therefore, to solve The purpose of multivariate GRR through factor analysis is to identify the covariance structure between several quality characteristics in improving product quality using multivariate Gage, Repeatability and Reproducibility (GRR) through factor analysis, and find out if the HKZL product measurement system is in PT. Indonesia's Manufacturing Gradient is accepted or does not use the multivariate Gage, Repeatability and Reproducibility (GRR) method through factor analysis. In practice, the analysis step has been prepared and applied to the measurement of HKZL products in PT. Indonesian Manufacturing Gradient. The results were obtained from the measurement system on HKZL products in PT. The Indonesian Manufacturing Gradient is not accepted, meaning that the resulting product is HKZL has quality beyond the company's standards (quality standards), so it can be concluded that the HKZL product making machine is in poor condition to use.


Keywords


Multivariat; Gage, Repeatability, and Reproducibility (GRR); Analisis Faktor

References


K. D. Majeske and K. D. Majeske, “Systems Approval Criteria for Multivariate Measurement Systems,” vol. 4065, 2017, doi: 10.1080/00224065.2008.11917721.

P. Taylor, F. Wang, C. Yang, and F. Wang, “Journal of the Chinese Institute of Industrial Engineers APPLYING PRINCIPAL COMPONENT ANALYSIS TO A GR & R STUDY APPLYING PRINCIPAL COMPONENT ANALYSIS TO A GR & R STUDY,” no. October 2014, pp. 37–41, 2010, doi: 10.1080/10170660709509032.

F. Wang and T. Chien, “Computers & Industrial Engineering Process-oriented basis representation for a multivariate gauge study,” Comput. Ind. Eng., vol. 58, no. 1, pp. 143–150, 2010, doi: 10.1016/j.cie.2009.10.001.

AIAG, Measurement system analysis: reference manual, Fourth edi. USA: Detroit, MI, 2010.

J. Supranto, Analisis Multivariat: Arti dan Interpretasi. Jakarta: PT. Rineka Cipta, 2004.

D. Susanti, Dewi Sri, Analisis Regresi dan Korelasi. Malang: CV IRDH, 2019.

F. Wang and T. Chien, “Computers & Industrial Engineering Process-oriented basis representation for a multivariate gauge study,” Comput. Ind. Eng., vol. 58, no. 1, pp. 143–150, 2010, doi: 10.1016/j.cie.2009.10.001.




DOI: https://doi.org/10.15575/kubik.v6i2.14555

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