Fauziah, Ade Nurul (2021) Optimasi Karakteristik Kualitas Bata Ringan PT XYZ Menggunakan Metode Taguchi dengan Pendekatan Grey Relational Analysis (GRA) dan Principal Component Analysis (PCA). Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Karakteristik kualitas yang sangat diperhatikan dalam proses produksi bata ringan, yaitu kuat tekan, berat jenis, dan kadar air. Kualitas produksi bata ringan dipengaruhi oleh komposisi semen, kapur, fresh slurry, dan return slurry. Saat ini belum diketahui level keempat komposisi yang menghasilkan kualitas bata ringan yang optimal dan masih terdapat karakteristik kualitas di luar nilai yang ditetapkan perusahaan. Oleh karena itu, perlu dilakukan optimasi untuk menentukan level keempat komposisi yang dapat mengoptimalkan ketiga karakteristik kualitas. Metode optimasi yang digunakan pada penelitian ini adalah metode Taguchi dengan pendekatan kombinasi grey relational analysis (GRA) dan principal component analysis (PCA). GRA digunakan untuk mengoptimasi karakteristik kualitas yang bersifat multirespon dan PCA digunakan untuk menaksir nilai pembobot yang sesuai sehingga karakteristik yang relatif penting dapat tepat dijelaskan. Hasil analisis menunjukkan bahwa, level faktor yang dapat mengoptimalkan kuat tekan, densitas, dan kadar air secara simultan adalah ketika digunakan komposisi semen 460-480 kg, komposisi kapur sebesar 200-220 kg, komposisi fresh slurry sebesar 2316-2482 kg, dan komposisi return slurry sebesar 939-1058 kg. Ketika digunakan level optimum diperoleh estimasi kuat tekan antara 4,81 N/mm2 sampai 5,11 N/mm2, berat jenis antara 562,39 kg/m3 sampai 582,54 kg/m3, dan kadar air antara 19,63% sampai 22,61%. Hasil estimasi ketiga respon berada dalam batas spesifikasi yang ditetapkan oleh perusahaan. Faktor yang berpengaruh pada respon secara simultan adalah komposisi semen.
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The quality characteristics that are highly considered in the production process of light bricks are compression, density, and water content. The quality of light brick is affected by the composition of cement, calcium, fresh slurry, and return slurry. Currently, the level of those four compositions resulting-in optimal light brick quality is unknown and there are quality characteristics beyond the range value specified by the company. Therefore, optimization needs to be done to determine the level of the four compositions that can optimize the three quality characteristics. The optimization method used in this study is the Taguchi method with combination of grey relational analysis (GRA) and principal component analysis (PCA) approach. GRA is utilized to optimize the multiresponse quality characteristics and PCA is used to estimate proper weighting values, so that the relatively important quality characteristic can be described precisely. Based on the analysis result, the level of the factors that can optimize compression, density, and water content simultaneously is when the compositions consist of 460-480 kilos cement, 200-220 kilos calcium, 2316-2482 kilos fresh slurry, and 939-1058 kilos return slurry are used. When the optimum level is used, the estimated compression is between 4.81 N/mm2 to 5.11 N/mm2, the density is between 562.39 kg/m3 to 582.54 kg/m3, and the water content is between 19.63% to 22.61%. The result of those estimated values are within the specification limits determined by the company. Factor that influence the responses simultaneously is the composition of cement.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Berat Jenis, Grey Relational Analysis, Kadar Air, Kuat Tekan, Optimasi, Principal Component Analysis, Taguchi, Density, Grey Relational Analysis, Compressive, Optimization, Principal Component Analysis, Taguchi, Water Content. |
| Subjects: | H Social Sciences > HA Statistics > HA29 Theory and method of social science statistics H Social Sciences > HA Statistics > HA31.35 Analysis of variance Q Science > Q Science (General) Q Science > QA Mathematics > QA278.5 Principal components analysis. Factor analysis. Correspondence analysis (Statistics) |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Ade Nurul Fauziah |
| Date Deposited: | 25 Aug 2021 02:19 |
| Last Modified: | 25 Aug 2021 02:19 |
| URI: | http://repository.its.ac.id/id/eprint/90125 |
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