Implementasi Metode Taguchi Grey Relational Analysis Untuk Menurunkan Reject Produk Pada Proses Auto Spray Mold Machine

Asmoro, Satrio Aditya (2026) Implementasi Metode Taguchi Grey Relational Analysis Untuk Menurunkan Reject Produk Pada Proses Auto Spray Mold Machine. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 2040221120-Undergraduate_Thesis.pdf Restricted to Repository staff only Download (3MB) | Request a copy

Abstract

Konsistensi proses manufaktur merupakan faktor penting dalam menjaga kualitas produk pada proses perakitan baterai. Pada sistem automatic mold spray, perbedaan penggunaan parameter operasi dapat menyebabkan kualitas penyemprotan menjadi tidak konsisten sehingga meningkatkan potensi terjadinya cacat produk. Penelitian ini diawali dengan implementasi perbaikan sistem pada automatic mold spray machine untuk meningkatkan stabilitas proses penyemprotan. Selanjutnya dilakukan penentuan parameter proses menggunakan metode Taguchi yang diintegrasikan dengan Grey Relational Analysis (Taguchi-GRA) untuk optimasi multi-respons. Parameter yang dievaluasi meliputi suhu mold, durasi penyemprotan, dan air blow pressure menggunakan rancangan percobaan Orthogonal Array L9, sedangkan Analysis of Variance (ANOVA) digunakan untuk menganalisis kontribusi masing-masing parameter terhadap variasi kualitas proses. Hasil penelitian menunjukkan bahwa air blow pressure merupakan faktor yang berpengaruh dengan kontribusi sebesar 49,27%, diikuti oleh durasi spray dengan kontribusi 20,73% dan ambang batas suhu mold sebesar 14,53%. Berdasarkan analisis Taguchi-GRA diperoleh kombinasi parameter terbaik A2B1C3, yaitu suhu mold 160°C, durasi penyemprotan 1,5 detik, dan air blow pressure 1,0 MPa. Model kemudian divalidasi melalui proses pooling up untuk memperoleh estimasi error yang lebih representatif dalam perhitungan nilai prediksi Grey Relational Grade (GRG), Confidence Interval (CI), dan Prediction Interval (PI). Hasil eksperimen konfirmasi menghasilkan rata-rata GRG sebesar 0,8076 yang berada di dalam rentang CI (0,6997–1,000) dan PI (0,6445–1,000), sehingga menunjukkan bahwa model memiliki kemampuan prediksi yang baik. Selain itu, nilai rata-rata GRG meningkat sebesar 23,54% dibandingkan rata-rata seluruh kombinasi percobaan Taguchi L9. Implementasi kombinasi parameter juga mampu menurunkan jumlah reject cacat splash sebesar 100,00% dan cacat ketarik sebesar 78,57% berdasarkan perbandingan hasil produksi selama empat hari pada shift satu sebelum dan sesudah implementasi. Hasil penelitian ini menunjukkan bahwa metode Taguchi-GRA efektif dalam meningkatkan konsistensi proses penyemprotan serta meningkatkan performa kualitas proses automatic mold spray.
=======================================================================================================================================
Manufacturing process consistency is a critical factor in maintaining product quality during battery assembly. In automatic mold spray systems, variations in operating parameters can lead to inconsistent spraying quality, thereby increasing the likelihood of product defects. This study began by implementing system improvements on the automatic mold spray machine to enhance spraying process stability. Subsequently, process parameters were determined using the Taguchi method integrated with Grey Relational Analysis (Taguchi-GRA) for multi-response optimization. The parameters evaluated included mold temperature, spray duration, and air blow pressure, utilizing an L9 Orthogonal Array experimental design; Analysis of Variance (ANOVA) was employed to assess each parameter's contribution to process quality variation. The results indicate that air blow pressure was the most influential factor, contributing 49.27%, followed by spray duration (20.73%) and mold temperature (14.53%). The Taguchi-GRA analysis identified the optimal parameter combination as A2B1C3: a mold temperature of 160°C, a spray duration of 1.5 seconds, and an air blow pressure of 1.0 MPa. The model was validated using a "pooling up" process to obtain a more representative error estimate for calculating the predicted Grey Relational Grade (GRG), Confidence Interval (CI), and Prediction Interval (PI). Confirmation experiments yielded an average GRG of 0.8076, falling within the CI (0.6997–1.000) and PI (0.6445–1.000) ranges, demonstrating the model's strong predictive capability. Furthermore, the average GRG value showed a 23.54% improvement compared to the average of all L9 experimental combinations. Implementing this parameter combination also succeeded in eliminating "splash" defects (a 100.00% reduction) and reducing "drag" defects by 78.57%, based on a comparison of four days of production data from the first shift before and after implementation. The results of this study indicate that the Taguchi-GRA method is effective in enhancing the consistency of the spraying process and improving the quality performance of the automatic mold spray process.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Spray Mold, Cast On Strap(COS), Taguchi, Spray Mold, Cast On Strap(COS),Taguchi.
Subjects:	Q Science > Q Science (General) T Technology > TJ Mechanical engineering and machinery > TJ212 Control engineering systems. Automatic machinery (General) T Technology > TJ Mechanical engineering and machinery > TJ217.2 Robust control
Divisions:	Faculty of Vocational > 36304-Automation Electronic Engineering
Depositing User:	Satrio Aditya Asmoro
Date Deposited:	13 Aug 2026 01:02
Last Modified:	13 Aug 2026 01:02
URI:	http://repository.its.ac.id/id/eprint/144298

Actions (login required)

View Item