Simulasi Peristiwa Diskret dengan Python
Diogo Costa (PhD, MSc)
Adjunct Professor, University of Saskatchewan, Canada & CEO of ImpactBLUE-Scientific

Contoh: Pengelolaan arus penumpang di bandara
Proses deterministik
Contoh: Mesin las
Waktu pemrosesan = Panjang garis las x Kecepatan mesin las
Proses non-deterministik

Contoh: Lini perakitan dengan pengelasan
welding_1welding_2
welding_1
Nama proses: Welding component A
Waktu pemrosesan: 5 jam
welding_2length * hours_per_lengthMembuat dictionary untuk tiap proses:
welding_1 = {
"name": "Welding component A",
"time_hours": 5
}
length = 20 # meters
hours_per_length = 0.2 # hours
welding_2 = {
"name": "Welding component B",
"time_hours": length * hours_per_length
}
Contoh: Lini perakitan
manual_assembly_1manual_assembly_2
manual_assembly_1
Rata-rata waktu pemrosesan: 80 jam
Simpangan baku: 5 jam
manual_assembly_220 jam2 jamMembuat dictionary untuk tiap proses:
manual_assembly_1 = {
"name": "Manual Assembly A",
"time_hours": 80,
"std_hours": 5
}
manual_assembly_2 = {
"name": "Manual Assembly B",
"time_hours": 20,
"std_hours": 2}
Urutan proses manufaktur

Model peristiwa-diskret
# Inisiasi variabel pelacak waktu time = numpy.zeros(number_of_processes)# Perkembangan waktu peristiwa berikutnya time[0] = 0 time[1] = time[0] + welding_1["time_hours"] time[2] = time[1] + rd.gauss(manual_assembly_1["time_hours"], manual_assembly_1["std_hours"]) time[3] = time[2] + rd.gauss(manual_assembly_2["time_hours"], manual_assembly_2["std_hours"]) time[4] = time[3] + welding_2["time_hours"] time[5] = time[4]
Simulasi Peristiwa Diskret dengan Python