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PENENTUAN SETTING VARIABEL PROSES PEMBAKARAN YANG MENGOPTIMALKAN (CO) DAN TEMPERATUR GAS BUANG PADA BOILER ABB-CE DENGAN METODE TAGUCHI DAN TOPSIS (STUDI KASUS DI PLTU PAITON SWATA PHASA 11) Heru Darsanto; Haryono Haryono
Jurnal Teknobisnis Vol 1, No 2 (2005): Jurnal TEKNOBISNIS
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat- Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1111.814 KB) | DOI: 10.12962/j24609463.v1i2.2805

Abstract

Paiton Phasa 11 Independent Power Producer (IPP) is a coal power station that operates 2x610 MW net steam turbine generators. This research is focused on lowest efficiency of transformation from chemical enerv to thermal energy in the steam generator (boiler). Based on information technology provided by ABB CE, there are four process variables affecting the combustion i.e. tilting (nozzle angle), air distribution, combination of elevation and furnace draft. Beside, there are two responses that represent the combustion performance i.e. [CO] gas and furnace exit temperature. The other variable that influences the combustion but is not controlled is type of coal called noise variable. The aim of this research is to find which process variables that have the most significant effect to the responses and identify the existing interaction among them. The second aim is to find the optimal combustion setting and calculate the improvement efficiency. In order to achieve that purpose, the Experiment Matrix called Orthogonal Array (04) developed by Taguchi is used. The result of this experiment matrix will be brought in to the signal ratio to noise (SIN) that transfer data in to a value that represents a measure of variance (precision and accurate). The next step is analysing data using Analysis of Variance (ANOVA). The result of SN ratio and ANOVA is a setting that results in an optimal solution of [CO] and furnace exit temperature individually. The TOPSIS (Technique for Order Preference by Similarly to Ideal Solution) is than used to get the only one setting producing optimal solution for both responses (multi responses optimation).