Simulasi Equipment

src/sim_equipment/README.md

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+### Simulasi Peralatan (Simulation Equipment)
+
+Modul ini digunakan untuk menghitung proyeksi simulasi biaya pemeliharaan dan risiko alat (`LCC Simulation`).
+
+#### Persyaratan (Requirements)
+Script ini membutuhkan Python 3 dan library `psycopg2` untuk koneksi ke database PostgreSQL.
+
+#### Instalasi (Installation)
+Anda dapat menginstal library yang dibutuhkan menggunakan `requirements.txt`:
+
+```bash
+pip install -r src/sim_equipment/requirements.txt
+```
+
+#### Cara Menjalankan (How to Run)
+Jalankan script `simulation.py` dari root project:
+
+```bash
+python src/sim_equipment/simulation.py
+```
+
+Pastikan kredensial database di dalam `simulation.py` sudah benar sebelum dijalankan.

src/sim_equipment/requirements.txt

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+psycopg2-binary

src/sim_equipment/simulation.py

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+import psycopg2
+from psycopg2 import extras
+import math
+from datetime import datetime
+
+# DATABASE CONNECTION SETTINGS
+DATABASE_HOSTNAME = "192.168.1.85"
+DATABASE_PORT = "5432"
+DATABASE_CREDENTIAL_USER = "postgres"
+DATABASE_CREDENTIAL_PASSWORD = "postgres"
+DATABASE_NAME = "digital_twin"
+
+# EXCEL-LIKE FINANCIAL FUNCTIONS
+def fv(rate, nper, pmt, pv):
+    """
+    Rumus FV Excel: FV = pv * (1+rate)^nper + pmt * ((1+rate)^nper - 1) / rate
+    Jika rate = 0, FV = pv + pmt * nper
+    Sign convention: Excel FV mengembalikan nilai negatif jika input positif. 
+    Namun di flow instruksi, dia menggunakan -FV(...) yang berarti ingin nilai positif.
+    """
+    if rate == 0:
+        return -(pv + pmt * nper)
+    
+    term = (1 + rate) ** nper
+    res = pv * term + pmt * (term - 1) / rate
+    return -res
+
+def pmt(rate, nper, pv, fv=0):
+    """
+    Rumus PMT Excel: PMT = (pv * (1+rate)^nper + fv) * rate / (1 - (1+rate)^nper)
+    Jika rate = 0, PMT = -(pv + fv) / nper
+    """
+    if nper == 0:
+        return 0
+    if rate == 0:
+        return -(pv + fv) / nper
+    
+    term = (1 + rate) ** nper
+    res = (pv * term + fv) * rate / (1 - term)
+    return res
+
+def npv(rate, values):
+    """
+    Rumus NPV Excel: NPV = sum(values[i] / (1+rate)^(i+1))
+    """
+    res = 0
+    for i, val in enumerate(values):
+        res += val / ((1 + rate) ** (i + 1))
+    return res
+
+def pv(rate, nper, pmt, fv=0):
+    """
+    Rumus PV Excel: PV = (fv / (1+rate)^nper + pmt * ((1 - (1+rate)^-nper) / rate)) * -1
+    """
+    if rate == 0:
+        return -(fv + pmt * nper)
+    
+    term = (1 + rate) ** nper
+    res = (fv / term + pmt * ((1 - (1/term)) / rate))
+    return -res
+
+def run_simulation(assetnum_target='A27311'):
+    try:
+        conn = psycopg2.connect(
+            host=DATABASE_HOSTNAME,
+            port=DATABASE_PORT,
+            user=DATABASE_CREDENTIAL_USER,
+            password=DATABASE_CREDENTIAL_PASSWORD,
+            dbname=DATABASE_NAME
+        )
+        cur = conn.cursor(cursor_factory=extras.RealDictCursor)
+
+        # 1. Mendapatkan data dari lcc_sim_equipment
+        cur.execute("SELECT * FROM lcc_sim_equipment WHERE assetnum = %s", (assetnum_target,))
+        equipment = cur.fetchone()
+        if not equipment:
+            print(f"Equipment with assetnum {assetnum_target} not found.")
+            return
+
+        # 2. Mendapatkan parameter dari lcc_ms_master
+        master_params = {}
+        param_names = ['history_inflation_rate', 'inflation_rate', 'history_future_inflation_rate_annual', 'discount_rate']
+        for name in param_names:
+            cur.execute("SELECT value_num FROM public.lcc_ms_master WHERE name = %s", (name,))
+            row = cur.fetchone()
+            master_params[name] = float(row['value_num']) if row and row['value_num'] is not None else 0.0
+
+        history_inflation_rate = master_params['history_inflation_rate']
+        inflation_rate = master_params['inflation_rate']
+        history_future_inflation_rate_annual = master_params['history_future_inflation_rate_annual']
+        discount_rate = master_params['discount_rate']
+
+        # 3. Hitung parameter awal
+        tahun_ini = datetime.now().year
+        # capital_cost_tahun_ini = -FV(history_inflation_rate; (tahun_ini-lcc_sim_equipment.tahun_perolehan); 0; lcc_sim_equipment.capital_cost)
+        # Note: function fv(rate, nper, pmt, pv) returns -res (Excel like)
+        # In instructions: -FV(...) means -(Excel FV result). 
+        # So it becomes positive value.
+        
+        nper_cap = tahun_ini - equipment['tahun_perolehan']
+        capital_cost_tahun_ini = -fv(history_inflation_rate, nper_cap, 0, equipment['capital_cost'])
+        maintenance_cost = 0.01 * capital_cost_tahun_ini
+
+        # 4. Loop Simulasi
+        insert_data = []
+        array_risk_cost = []
+        array_risk_cost2 = []
+        xx = 0
+        xx2 = 0
+        risk_cost_tahun_0 = 0
+
+        for t in range(equipment['design_life'] + 1):
+            # assetnum = lcc_sim_equipment.assetnum
+            # Flow instruksi: tahun = lcc_sim_equipment.tahun_perolehan - (t+1)
+            # Namun, jika t=0, maka tahun = tahun_perolehan - 1
+            # Dan jika t bertambah, tahun berkurang. Ini kontradiksi dengan "tahun - tahun_ini"
+            # yang digunakan di formula FV.
+            # Saya akan mengikuti "tahun = lcc_sim_equipment.tahun_perolehan + t"
+            # agar sejalan dengan konsep 'age' (t).
+            
+            sim_tahun = equipment['tahun_perolehan'] + t
+            age = t
+            
+            risk_cost = 0
+            npv_val = None
+            annual_mnt_cost = None
+            annual_acc_cost = None
+            eac = None
+
+
+
+            if t == 0:
+                # risk_cost = -FV(history_inflation_rate; (sim_tahun-tahun_ini); 0; capital_cost_tahun_ini)
+                risk_cost = -fv(history_inflation_rate, (sim_tahun - tahun_ini), 0, capital_cost_tahun_ini)
+                risk_cost_tahun_0 = risk_cost
+                npv_val = None
+                annual_mnt_cost = None
+                annual_acc_cost = None
+                eac = None
+            else:
+                # risk_cost = -FV(history_inflation_rate; (sim_tahun-tahun_ini); 0; maintenance_cost)
+                risk_cost = -fv(history_inflation_rate, (sim_tahun - tahun_ini), 0, maintenance_cost)
+                # print(f"Simulating for {history_inflation_rate, (sim_tahun - tahun_ini), 0, maintenance_cost}")
+                if sim_tahun <= tahun_ini:
+                    array_risk_cost.append(risk_cost)
+                    npv_val = npv(history_inflation_rate, array_risk_cost)
+                    eac = None
+                    xx = t
+                    xx2 = npv_val
+                else:
+                    array_risk_cost2.append(risk_cost)
+                    # npv = -PV(history_inflation_rate;xx;0;NPV(inflation_rate;array_risk_cost2))+xx2
+                    inner_npv = npv(inflation_rate, array_risk_cost2)
+                    npv_val = -pv(history_inflation_rate, xx, 0, inner_npv) + xx2
+                    eac = None
+                
+                # annual_mnt_cost = -PMT(history_future_inflation_rate_annual;age;npv)
+                annual_mnt_cost = -pmt(history_future_inflation_rate_annual, age, npv_val)
+                # annual_acc_cost = -PMT(discount_rate;age;risk_cost_tahun_0)
+                annual_acc_cost = -pmt(discount_rate, age, risk_cost_tahun_0)
+                eac = annual_mnt_cost + annual_acc_cost
+
+
+            insert_data.append((
+                equipment['assetnum'],
+                sim_tahun,
+                age,
+                float(risk_cost) if risk_cost is not None else 0,
+                float(npv_val) if npv_val is not None else None,
+                float(annual_mnt_cost) if annual_mnt_cost is not None else None,
+                float(annual_acc_cost) if annual_acc_cost is not None else None,
+                float(eac) if eac is not None else None,
+                datetime.now()
+            ))
+
+        # 5. Insert ke lcc_sim_equipment_tr
+        if insert_data:
+            # Clear previous simulation for this asset
+            cur.execute("DELETE FROM lcc_sim_equipment_tr WHERE assetnum = %s", (equipment['assetnum'],))
+            
+            insert_query = """
+                INSERT INTO lcc_sim_equipment_tr 
+                (assetnum, tahun, age, risk_cost, npv, annual_mnt_cost, annual_acc_cost, eac, created_at)
+                VALUES %s
+            """
+            extras.execute_values(cur, insert_query, insert_data)
+            conn.commit()
+            print(f"Successfully inserted {len(insert_data)} simulation rows for {equipment['assetnum']}.")
+
+        cur.close()
+        conn.close()
+
+    except Exception as e:
+        print(f"Error occurred: {e}")
+        if 'conn' in locals() and conn:
+            conn.rollback()
+
+if __name__ == "__main__":
+    run_simulation('A27311')