OPTIMASI PENJADWALAN PEMELIHARAAN PREDIKTIF POMPA KILANG MIGAS MENGGUNAKAN ALGORITMA GENETIKA
DOI:
https://doi.org/10.53026/prosidingsntem.v5i1.667Keywords:
Algoritma Genetika, Pompa Kilang, Predictive Maintenance, Optimasi Penjadwalan, Efisiensi OperasionalAbstract
Pompa merupakan aset kritis kilang migas yang menyumbang lebih dari 35% potensi downtime dengan kerugian ekonomi USD 20.000-30.000 per jam. Jadwal pemeliharaan berbasis waktu terbukti tidak optimal karena mengabaikan kondisi aktual peralatan, menimbulkan risiko over-maintenance atau under-maintenance. Penelitian ini mengembangkan model optimasi penjadwalan pemeliharaan prediktif berbasis Algoritma Genetika (GA) untuk pompa sentrifugal kilang migas. GA mengevaluasi kombinasi interval pemeliharaan dengan mempertimbangkan biaya perawatan, probabilitas kegagalan berbasis distribusi Weibull, dan Mean Time Between Failure (MTBF). Fungsi fitness dirancang meminimalkan biaya total sambil memaksimalkan reliabilitas sistem. Simulasi menggunakan data aktual pompa kilang dengan konfigurasi population=60 dan generations=50 menunjukkan konvergensi optimal pada generasi ke-20. Hasil optimasi menunjukkan penurunan biaya pemeliharaan total 18,7%, pengurangan downtime tidak terencana 22,4%, dan peningkatan MTBF sebesar 8,3% dibanding metode preventif konvensional. Reliabilitas sistem meningkat hingga 90% dengan umur operasional pompa bertambah rata-rata 1,4 bulan. Validasi statistik menggunakan uji Kolmogorov-Smirnov menunjukkan model valid (D_KS=0,072<D_krit=0,118). Integrasi Predictive Maintenance dengan GA terbukti efektif meningkatkan keandalan, efisiensi biaya, dan keberlanjutan operasional kilang migas.
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