Pengedalian Mutu Batubara Dengan Teknik Distribusi Normal

Kemas Muhammat Abdul Fatah, Wisnaningsih Wisnaningsih, Wisnaningsih Wisnaningsih

Abstract


ABSTRAK

 

Batubara jenis thermal coal paling banyak digunakan pada Pembangkit Listrik Tenaga Uap (PLTU). Batubara yang dipasok ke PLTU memiliki spesifikasi tertentu yang sesuai dengan spesifikasi boiler, pemilihan batubara yang tidak tepat akan menimbulkan masalah pada boiler. Pemasok batubara bagi PLTU harus melakukan pengendalian mutu untuk meminimalkan risiko berupa penyesuaian harga atau penolakan melalui analisis proksimat, analisis ultimat, dan analisis calorific value. Penelitian ini ditujukan untuk mengolah data hasil analisis sehingga diketahui kondisi batubara existing dan prediksi harga batubara. Dari hasil pengolahan data dengan teknik distribusi normal, mutu batubara existing termasuk spesifikasi medium calorific value ditinjau dari parameter Gross Calorific Value (GCV), Total Moisture (TM), dan Volatile Matter (VM). Ditinjau dari parameter GCV, batubara existing termasuk batubara bituminus yang sesuai dengan kebutuhan PLTU. Dengan asumsi harga dasar $308/ton, akibat mutu batubara existing pada parameter nilai GCV, diprediksi harga batubara existing lebih rendah dari harga dasar, 68.92% seharga $224.106/ton, 30.84% seharga $263.081/ton, dan 0.01% seharga $282.569/ton.

 

Kata Kunci: batubara, distribusi normal, pengendalian mutu

 

ABSTRACT

Coal Quality Control with Normal Distribution. The thermal coal type is most widely used in Steam Power Plants (PLTU). The coal supplied to the PLTU has certain specifications that are in accordance with the boiler specifications. Improper coal selection will cause problems in the boiler. Coal suppliers for PLTUs must carry out quality control to minimize the risk, such as: price adjustments or rejection through proximate analysis, ultimate analysis and calorific value analysis. This research is aimed at processing data from the analysis so that the condition of existing coal is known and predictions of coal prices are known. From the results of data processing using normal distribution techniques, the quality of existing coal includes medium calorific value specifications in terms of the parameters Gross Calorific Value (GCV), Total Moisture (TM), and Volatile Matter (VM). Judging from the GCV parameters, the existing coal includes bituminous coal which is in accordance with the needs of the PLTU. Assuming a base price of $308/ton, due to the quality of existing coal in the GCV value parameters, it is predicted that the existing coal price will be lower than the base price, 68.92% at $224,106/ton, 30.84% at $263,081/ton, and 0.01% at $282,569/ton.

 

Keywords: coal, normal distribution, quality control


Keywords


batubara, distribusi normal, pengendalian mutu

Full Text:

PDF

References


Bureska-Joleska, L. (2017). Influence of coal quality to the boiler efficiency and opportunity for its improvement. Termotehnika, 43(1–4), 59–65.

Dai, B., Wu, X., Zhang, J., Ninomiya, Y., Yu, D., & Zhang, L. (2020). Characteristics of iron and sulphur in high-ash lignite (Pakistani lignite) and their influence on long-term T23 tube corrosion under super-critical coal-fired boiler conditions. Fuel, 264(October 2019), 116855.

Dai, W., Yoshigoe, K., & Parsley, W. (2018). Improving Data Quality Through Deep Learning and Statistical Models.

Di Gianfrancesco, A. (2017). Worldwide overview and trend for clean and efficient use of coal. In Materials for Ultra-Supercritical and Advanced Ultra-Supercritical Power Plants. Elsevier.

Fernandez-Anez, N., Castells Somoza, B., Amez Arenillas, I., & Garcia-Torrent, J. (2020). Explosion Risk of Solid Biofuels. Springer.

Godina, R., Pimentel, C., Silva, F. J. G., & Matias, J. C. O. (2018). Improvement of the Statistical Process Control Certainty in an Automotive Manufacturing Unit. Procedia Manufacturing, 17, 729–736.

Guan, G. (2017). Clean coal technologies in Japan: A review. Chinese Journal of Chemical Engineering, 25(6), 689–697.

Guan, J., Yuan, P., Hu, X., Qing, L., & Yao, X. (2019). Statistical analysis of concrete fracture using normal distribution pertinent to maximum aggregate size. Theoretical and Applied Fracture Mechanics, 101(March), 236–253.

Gui, W., Hu, X., & Liang, L. (2020). Normal distribution analysis of fracture parameters of alkali-activated slag seawater column coral aggregate concrete. Theoretical and Applied Fracture Mechanics, 110(February), 102794.

Salmi, S., & Nuraini, A. A. (2020). Effect of Coal with High Moisture Content on Boiler Operation Parameters at Thermal Coal Fired Power Plant. 17(6), 6236–6247.

Xi-jin, G., Ming, C., & Jia-wei, W. (2009). Coal blending optimization of coal preparation production process based on improved GA. Procedia Earth and Planetary Science, 1(1), 654–660.

Zhang, C., Hu, X., Sercombe, T., Li, Q., Wu, Z., & Lu, P. (2018). Prediction of ceramic fracture with normal distribution pertinent to grain size. Acta Materialia, 145, 41–48.

Zhang, C., & Yang, S. (2019). Probabilistic prediction of strength and fracture toughness scatters for ceramics using normal distribution. Materials, 12(5).

Zhu, Q. (2010). Coal sampling and analysis standards. In IEA Clean Coal Centre (Issue 2014). IEA Clean Coal Centre.




DOI: https://doi.org/10.33024/jrets.v8i2.16306

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Jurnal Rekayasa, Teknologi, dan Sains

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Jurnal Rekayasa, Teknologi, dan Sains View My Stats

 Jurnal Rekayasa, Teknologi, dan Sains  indexed by:


Secretariat Office:
UNIVERSITAS MALAHAYATI
Mail  : Jl. Pramuka No. 27, Kemiling, Kota Bandar Lampung
Telp  : 0811729009
email: jurnalrts.ft@malahayati.ac.id

<" Copyright UNIVERSITAS MALAHAYATI
 
Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License