Evaluasi Performa Coal Gasification Furnace (Cgf) Menggunakan Integrasi Rca-Mlr (Root Cause Analysis - Multiple Linear Regression)

Najib, Davi Khoirun (2022) Evaluasi Performa Coal Gasification Furnace (Cgf) Menggunakan Integrasi Rca-Mlr (Root Cause Analysis - Multiple Linear Regression). Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pengembangan industri Renewable Energy kedepan mulai berkembang, salah satunya yaitu pengembangan hilirisasi batubara. Dewasa ini industri hilirisasi batubara memiliki tantangan besar dalam menciptakan teknologi industri berbasis energi bersih seperti gasifikasi batubara. Perusahaan Smelter Grade Alumina (PSGA) sebagai salah satu industri yang mengembangkan teknologi tersebut memiliki beberapa permasalahan diantaranya kualitas produk rendah dengan nilai Heating Value Coal Gas < 5550 kJ/m3 , Efek GHG (Greenhouse gas) dengan kontribusi CO2 yang dihasilkan sebesar ± 354.956,85 ton/tahun, masalah slagging yang berdampak pada Furnace Downtime selama ± 3-4 minggu, dan masalah ash handling pada Fly Ash hasil aktifitas Gasifikasi Batubara sejumlah ± 62.000 ton/tahun. Dari keempat permasalahan tersebut berdampak pada penurunan kinerja Coal Gasification Furnace (CGF). Penelitian ini bertujuan untuk mengidentifikasi indikator yang paling berpengaruh pada kinerja CGF, Melakukan optimasi proses produksi untuk meningkatkan kinerja CGF, dan memberikan rekomendasi perbaikan pada CGF untuk mewujudkan produksi syngas berkelanjutan. Metode yang digunakan pada penelitian ini adalah integrasi metode RCA-MLR (Root Cause Analysis – Multiple Linier Regression). Metode RCA digunakan untuk menguraikan dan mendapatkan akar permasalahan dari penurunan performa CGF. Kemudian dari akar masalah terpilih, dilakukan optimasi indikator proses produksi dengan melihat hubungan dependent variabel dan independent variabel melalui model regresi linier berganda (MLR). Hasil dari penelitian ini didapatkan akar masalah dari penurunan kinerja Coal Gasification Furnace (CGF) yaitu belum adanya mekanisme atau standard yang mengatur terkait pengaturan suhu CGF secara optimal dengan estimasi kebutuhan independent variable. Selanjutnya melalui pendekatan MLR menggunakan uji Anova didapatkan tiga independent variable yang berpengaruh signifikan pada peningkatan suhu CGF diantaranya steam, angin gasifikasi, angin fluidisasi, dan jenis tungku dengan nilai p-value < 0.05. Melalui model regresi linier berganda didapatkan hasil kualitas produk Coal Gas tinggi dengan nilai Heating Value Coal Gas sebesar 5595 kJ/m3 dan tidak terjadi Downtime untuk CGF karena masalah slagging. Selain itu dengan penerapan model regresi linier berganda dapat menghemat biaya Rp 2.607.942.761,-/bulan.
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The development of the Renewable Energy industry in future is starting to to grow rapidly, especially in coal downstream industry. Now coal downstream industry has big challenge to create clean energy industry such as coal gasification. The Smelter Grade Alumina (PSGA) company as one of the industry that developed this technology has several problems including low product quality with a Heating Value Coal Gas value of < 5550 kJ/m3, GHG (Greenhouse gas) effect with a CO2 contribution of ± 354,956.85 tons/year, slagging problems that affect Furnace Downtime for ± 3-4 weeks, and ash handling problems in Fly Ash as a result of Coal Gasification activities amounting to ± 62,000 tons/year. From the problems, impact on the performance of Coal Gasification Furnace (CGF) decreases. This study aims to identify the indicators that have the most influence on CGF performance, optimize the production process to improve CGF performance, and provide recommendations for improvements to CGF to realize sustainable syngas production. The method used in this research is the integration of the RCA-MLR (Root Cause Analysis – Multiple Linear Regression) method. The RCA method is used to describe and get the root cause of the decline in CGF performance. Then from the root of the problem selected, the production process indicators were optimized by looking at the relationship between the dependent variable and the independent variable through multiple linear regression (MLR) models. The results of this study found the root cause of the decline in the performance of the Coal Gasification Furnace (CGF), namely the absence of a mechanism or standard that regulates the optimal CGF temperature regulation with the estimated needs of independent variables. Furthermore, through the MLR approach using the Anova test, three independent variables were found that had a significant effect on increasing the CGF temperature including steam, gasification wind, fluidization wind, and type of furnace with p-value < 0.05. Through multiple linear regression model, the results obtained are high quality Coal Gas products with a Heating Value of Coal Gas of 5595 kJ/m3 and there is no downtime for CGF due to slagging problems. In addition, the application of multiple linear regression models can save costs of Rp. 2,607,942,761,-/month.

Item Type:	Thesis (Masters)
Additional Information:	RTMT 658.312 5 Naj e-1 2022
Uncontrolled Keywords:	Coal Gasification Furnace, RCA, MLR, syngas.
Subjects:	T Technology > T Technology (General)
Divisions:	Interdisciplinary School of Management and Technology (SIMT) > 61101-Master of Technology Management (MMT)
Depositing User:	Mr. Marsudiyana -
Date Deposited:	08 Jul 2026 07:02
Last Modified:	08 Jul 2026 07:02
URI:	http://repository.its.ac.id/id/eprint/134520

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