KAJIAN LITERATUR: STUDI LITERATUR PENGGUNAAN DSP DALAM ANALISIS GETARAN MESIN ROTARI DI INDUSTRI PUPUK KIMIA DI INDONESIA
Keywords:
Digital Signal Processing, analisis getaran, mesin rotari, industri pupuk kimia, pemeliharaan prediktif, Wavelet Transform.Abstract
Industri pupuk kimia di Indonesia sangat bergantung pada keandalan mesin-mesin rotari seperti pompa, kompresor, dan turbin yang beroperasi dalam kondisi ekstrem. Deteksi dini terhadap potensi kerusakan mekanis menjadi krusial guna mendukung efisiensi operasional dan mencegah downtime. Salah satu pendekatan yang berkembang pesat adalah pemanfaatan teknologi Digital Signal Processing (DSP) dalam analisis getaran mesin. Penelitian ini bertujuan untuk mengkaji secara sistematis penggunaan teknik DSP seperti Fast Fourier Transform (FFT), Wavelet Transform (WT), dan Hilbert Huang Transform (HHT) dalam mendeteksi kerusakan dini mesin rotari di industri pupuk kimia. Metode penelitian yang digunakan adalah studi literatur dengan menelaah berbagai sumber ilmiah terbitan 2013–2023 yang relevan. Hasil kajian menunjukkan bahwa DSP, khususnya WT dan pendekatan hybrid dengan machine learning, mampu meningkatkan akurasi dan sensitivitas dalam mendeteksi gangguan mekanis seperti misalignment, bearing fault, dan ketidakseimbangan. Namun, adopsi teknologi ini di industri pupuk Indonesia masih bervariasi, tergantung pada tingkat modernisasi dan investasi masing-masing pabrik. Studi ini menyoroti pentingnya integrasi DSP dalam strategi pemeliharaan prediktif, serta perlunya riset empiris dan kebijakan pendukung untuk mendorong transformasi digital yang lebih merata di sektor industri pupuk nasional.
Kata kunci: Digital Signal Processing, analisis getaran, mesin rotari, industri pupuk kimia, pemeliharaan prediktif, Wavelet Transform.
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