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update formula and top 10 remaining life

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main
MrWaradana 4 weeks ago
parent 46a2727f69
commit c1d087611a
9 changed files with 985 additions and 1174 deletions
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4
src/equipment/service.py
Unescape Escape View File

@ -391,7 +391,7 @@ async def get_top_10_economic_life(*, db_session: DbSession, common) -> list[Equ
(current_year - Equipment.minimum_eac_year),
),
else_=0,
).label("economic_life")
).label("remaining_life")
)
.filter(Equipment.minimum_eac_year != None)
.filter((Equipment.minimum_eac != None) & (Equipment.minimum_eac != 0))
@ -423,7 +423,7 @@ async def get_top_10_replacement_priorities(*, db_session: DbSession, common) ->
(current_year - Equipment.minimum_eac_year),
),
else_=0,
).label("economic_life")
).label("remaining_life")
)
.filter(Equipment.minimum_eac_year != None)
.filter((Equipment.minimum_eac != None) & (Equipment.minimum_eac != 0))

207
src/modules/equipment/Prediksi.py
Unescape Escape View File

@ -101,9 +101,7 @@ class Prediksi:
raw_predictive_material_cost AS predictive_material_cost,
raw_predictive_labor_time AS predictive_labor_time,
raw_predictive_labor_human AS predictive_labor_human,
raw_predictive_interval AS predictive_interval,
"raw_loss_output_MW" AS loss_output_mw,
raw_loss_output_price AS loss_price
raw_predictive_interval AS predictive_interval
FROM lcc_equipment_tr_data
WHERE assetnum = %s
and is_actual=1
@ -199,10 +197,9 @@ class Prediksi:
raw_pm_material_cost, raw_pm_labor_time, raw_pm_labor_human,
raw_oh_interval, raw_oh_material_cost, raw_oh_labor_time, raw_oh_labor_human,
raw_predictive_interval, raw_predictive_material_cost, raw_predictive_labor_time, raw_predictive_labor_human,
"raw_loss_output_MW", raw_loss_output_price
, created_by, created_at
created_by, created_at
) VALUES (
%s, %s, 0, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, 'Sys', NOW()
%s, %s, 0, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, 'Sys', NOW()
)
"""
@ -431,112 +428,6 @@ class Prediksi:
if connection:
connection.close()
# Fungsi untuk mengambil labour cost
def __get_labour_cost(self, equipment_id, worktype, existing_connection=None):
"""Return labour cost totals per tahun for the given worktype."""
labour_costs = {}
connection = existing_connection
cursor = None
close_connection = False
try:
if connection is None:
connections = get_production_connection()
connection = connections[0] if isinstance(connections, tuple) else connections
close_connection = True
if connection is None:
print("Database connection failed.")
return labour_costs
cursor = connection.cursor()
worktype_upper = (worktype or "").upper()
worktype_condition = "AND a.worktype IN ('CM', 'PROACTIVE', 'WA')"
params = [equipment_id]
if worktype_upper != "CM":
worktype_condition = "AND a.worktype = %s"
params.append(worktype_upper)
exclude_condition = "AND a.wojp8 != 'S1'" if worktype_upper == "CM" else ""
query = f"""
SELECT
EXTRACT(YEAR FROM x.reportdate)::int AS tahun,
SUM(x.upah_per_wonum) AS total_upah_per_tahun
FROM (
SELECT
bw.wonum,
bw.reportdate,
bw.jumlah_jam_kerja,
CASE
WHEN COUNT(b.laborcode) FILTER (WHERE b.laborcode IS NOT NULL) > 0 THEN
SUM(
COALESCE(emp_cost.salary_per_hour_idr,
(SELECT salary_per_hour_idr FROM lcc_manpower_cost WHERE UPPER(staff_job_level) = UPPER('Junior') LIMIT 1))
* bw.jumlah_jam_kerja
)
ELSE
3 * (SELECT salary_per_hour_idr FROM lcc_manpower_cost WHERE UPPER(staff_job_level) = UPPER('Junior') LIMIT 1) * bw.jumlah_jam_kerja
END AS upah_per_wonum
FROM (
SELECT
a.wonum,
a.reportdate,
CASE
WHEN (EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0) = 0
THEN 1
ELSE (EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0)
END AS jumlah_jam_kerja
FROM public.wo_maximo a
WHERE
a.asset_unit = '3'
AND a.wonum NOT LIKE 'T%'
AND a.asset_assetnum = %s
AND (EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0) <= 730
{worktype_condition}
{exclude_condition}
) bw
LEFT JOIN public.wo_maximo_labtrans b ON b.wonum = bw.wonum
LEFT JOIN lcc_ms_manpower emp ON UPPER(TRIM(emp."ID Number")) = UPPER(TRIM(b.laborcode))
LEFT JOIN lcc_manpower_cost emp_cost ON UPPER(TRIM(emp_cost.staff_job_level)) = UPPER(TRIM(emp."Position"))
GROUP BY bw.wonum, bw.reportdate, bw.jumlah_jam_kerja
) x
GROUP BY 1
ORDER BY 1;
"""
cursor.execute(query, tuple(params))
rows = cursor.fetchall()
for tahun, total in rows:
try:
year_int = int(tahun) if tahun is not None else None
except (TypeError, ValueError):
year_int = None
if year_int is None:
continue
try:
labour_costs[year_int] = float(total) if total is not None else 0.0
except (TypeError, ValueError):
labour_costs[year_int] = 0.0
return labour_costs
except Exception as e:
print(f"Error saat mendapatkan labour cost dari database: {e}")
return labour_costs
finally:
if cursor:
try:
cursor.close()
except Exception:
pass
if close_connection and connection:
try:
connection.close()
except Exception:
pass
# Fungsi untuk menghapus data proyeksi pada tahun tertentu
def __update_data_lcc(self, equipment_id):
@ -555,27 +446,14 @@ class Prediksi:
cursor = connection.cursor(cursor_factory=DictCursor)
labour_cost_maps = {
"CM": self.__get_labour_cost(equipment_id, "CM", production_connection),
"PM": self.__get_labour_cost(equipment_id, "PM", production_connection),
"PDM": self.__get_labour_cost(equipment_id, "PDM", production_connection),
"OH": self.__get_labour_cost(equipment_id, "OH", production_connection),
}
cm_labour_costs = labour_cost_maps.get("CM", {}) or {}
pm_labour_costs = labour_cost_maps.get("PM", {}) or {}
pdm_labour_costs = labour_cost_maps.get("PDM", {}) or {}
oh_labour_costs = labour_cost_maps.get("OH", {}) or {}
# Ambil semua baris untuk assetnum
select_q = '''
SELECT id, seq, tahun,
raw_cm_interval, raw_cm_material_cost, raw_cm_labor_time, raw_cm_labor_human,
raw_pm_interval, raw_pm_material_cost, raw_pm_labor_time, raw_pm_labor_human,
raw_predictive_interval, raw_predictive_material_cost, raw_predictive_labor_time, raw_predictive_labor_human,
raw_oh_interval, raw_oh_material_cost, raw_oh_labor_time, raw_oh_labor_human,
raw_predictive_interval, raw_predictive_material_cost, raw_predictive_labor_time, raw_predictive_labor_human,
"raw_loss_output_MW" as raw_loss_output_mw, raw_loss_output_price,
raw_operational_cost, raw_maintenance_cost,
raw_cm_interval, raw_cm_material_cost, rc_cm_labor_cost,
raw_pm_interval, raw_pm_material_cost, rc_pm_labor_cost,
raw_predictive_interval, raw_predictive_material_cost, rc_predictive_labor_cost,
raw_oh_interval, raw_oh_material_cost, rc_oh_labor_cost,
raw_predictive_interval, raw_predictive_material_cost, rc_predictive_labor_cost,
efdh_equivalent_forced_derated_hours, foh_forced_outage_hours
FROM lcc_equipment_tr_data
WHERE assetnum = %s;
@ -623,30 +501,12 @@ class Prediksi:
seq = int(r.get("seq") or 0) if isinstance(r, dict) else int(r[1] or 0)
raw_cm_interval = float(r.get("raw_cm_interval") or 0.0)
raw_cm_labor_time = float(r.get("raw_cm_labor_time") or 0.0)
raw_cm_labor_human = float(r.get("raw_cm_labor_human") or 0.0)
raw_pm_interval = float(r.get("raw_pm_interval") or 0.0)
raw_pm_material_cost = float(r.get("raw_pm_material_cost") or 0.0)
raw_pm_labor_time = float(r.get("raw_pm_labor_time") or 0.0)
raw_pm_labor_human = float(r.get("raw_pm_labor_human") or 0.0)
raw_predictive_interval = float(r.get("raw_predictive_interval") or 0.0)
raw_pm_material_cost = float(r.get("raw_pm_material_cost") or 0.0)
raw_predictive_material_cost = float(r.get("raw_predictive_material_cost") or 0.0)
raw_predictive_labor_time = float(r.get("raw_predictive_labor_time") or 0.0)
raw_predictive_labor_human = float(r.get("raw_predictive_labor_human") or 0.0)
raw_oh_interval = float(r.get("raw_oh_interval") or 0.0)
raw_oh_material_cost = float(r.get("raw_oh_material_cost") or 0.0)
raw_oh_labor_time = float(r.get("raw_oh_labor_time") or 0.0)
raw_oh_labor_human = float(r.get("raw_oh_labor_human") or 0.0)
# raw_loss_output_mw = float(r.get("raw_loss_output_mw") or 0.0)
# raw_loss_output_price = float(r.get("raw_loss_output_price") or 0.0)
# raw_operational_cost = float(r.get("raw_operational_cost") or 0.0)
# raw_maintenance_cost = float(r.get("raw_maintenance_cost") or 0.0)
efdh_equivalent_forced_derated_hours = float(r.get("efdh_equivalent_forced_derated_hours") or 0.0)
foh_forced_outage_hours = float(r.get("foh_forced_outage_hours") or 0.0)
@ -654,13 +514,10 @@ class Prediksi:
# compute per-column costs using helpers
rc_cm_material = rc_cm_material_cost
rc_cm_labor = rc_labor_cost(raw_cm_interval, raw_cm_labor_time, raw_cm_labor_human, man_hour)
cm_labor_total = cm_labour_costs.get(yr)
if cm_labor_total is not None:
try:
rc_cm_labor = float(cm_labor_total)
except (TypeError, ValueError):
rc_cm_labor = 0.0
rc_cm_labor = float(r.get("rc_cm_labor_cost") or 0.0)
rc_pm_labor = float(r.get("rc_pm_labor_cost") or 0.0)
rc_predictive_labor = float(r.get("rc_predictive_labor_cost") or 0.0)
rc_oh_labor = float(r.get("rc_oh_labor_cost") or 0.0)
try:
# if np.isfinite(raw_pm_interval) and raw_pm_interval != 0:
@ -669,13 +526,7 @@ class Prediksi:
rc_pm_material = raw_pm_material_cost
except Exception:
rc_pm_material = 0.0
rc_pm_labor = rc_labor_cost(raw_pm_interval, raw_pm_labor_time, raw_pm_labor_human, man_hour)
pm_labor_total = pm_labour_costs.get(yr)
if pm_labor_total is not None:
try:
rc_pm_labor = float(pm_labor_total)
except (TypeError, ValueError):
rc_pm_labor = 0.0
try:
# if np.isfinite(raw_predictive_interval) and raw_predictive_interval != 0:
@ -685,31 +536,7 @@ class Prediksi:
except Exception:
rc_predictive_material = 0.0
rc_predictive_labor = raw_predictive_labor_human
try:
rc_predictive_labor = rc_labor_cost(raw_predictive_interval, raw_predictive_labor_time, raw_predictive_labor_human, man_hour)
except Exception:
rc_predictive_labor = 0.0
predictive_labor_total = pdm_labour_costs.get(yr)
if predictive_labor_total is not None:
try:
rc_predictive_labor = float(predictive_labor_total)
except (TypeError, ValueError):
rc_predictive_labor = 0.0
rc_oh_material = raw_oh_material_cost
rc_oh_labor = rc_labor_cost(raw_oh_interval, raw_oh_labor_time, raw_oh_labor_human, man_hour)
oh_labor_total = oh_labour_costs.get(yr)
if oh_labor_total is not None:
try:
rc_oh_labor = float(oh_labor_total)
except (TypeError, ValueError):
rc_oh_labor = 0.0
# rc_lost = rc_lost_cost(raw_loss_output_mw, raw_loss_output_price, raw_cm_interval)
# rc_operation = raw_operational_cost
# rc_maintenance = raw_maintenance_cost
asset_criticality_data = self.__get_asset_criticality_params(equipment_id)
asset_criticality_value = 0.0
@ -734,9 +561,6 @@ class Prediksi:
rc_pm=rc_pm_material + rc_pm_labor + ac_multiplier,
rc_predictive=rc_predictive_material + rc_predictive_labor + ac_multiplier,
rc_oh=rc_oh_material + rc_oh_labor + ac_multiplier,
# rc_lost=rc_lost,
# rc_operation=rc_operation,
# rc_maintenance=rc_maintenance,
)
id_val = r.get("id") if isinstance(r, dict) else r[0]
@ -752,9 +576,6 @@ class Prediksi:
rc_predictive_labor,
rc_oh_material,
rc_oh_labor,
# rc_lost,
# rc_operation,
# rc_maintenance,
total,
id_val,
),

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src/modules/equipment/acquisition_cost_progress.csv
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240
src/modules/equipment/insert_actual_data.py
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@ -150,78 +150,90 @@ def get_labour_cost_totals(cursor, assetnum: str, worktype: str) -> dict:
if not assetnum or not worktype:
return {}
worktype_condition = "AND a.worktype IN ('CM', 'PROACTIVE', 'WA')"
worktype_params = [assetnum]
if worktype.upper() != "CM":
worktype_condition = "AND a.worktype = %s"
worktype_params.append(worktype.upper())
exclude_condition = "AND a.wojp8 != 'S1'" if worktype.upper() == "CM" else ""
query = f"""
SELECT
EXTRACT(YEAR FROM x.reportdate)::int AS tahun,
SUM(x.upah_per_wonum) AS total_upah_per_tahun
FROM (
SELECT
EXTRACT(YEAR FROM x.reportdate)::int AS tahun,
SUM(x.upah_per_wonum) AS total_upah_per_tahun
bw.wonum,
bw.reportdate,
bw.jumlah_jam_kerja,
CASE
WHEN COUNT(b.laborcode) FILTER (WHERE b.laborcode IS NOT NULL) > 0 THEN
SUM(
COALESCE(emp_cost.salary_per_hour_idr, (select salary_per_hour_idr from lcc_manpower_cost where upper(staff_job_level)= upper('Junior') limit 1))
* bw.jumlah_jam_kerja
)
ELSE
3 * (select salary_per_hour_idr from lcc_manpower_cost where upper(staff_job_level)= upper('Junior') limit 1) * bw.jumlah_jam_kerja
END AS upah_per_wonum
FROM (
SELECT
bw.wonum,
bw.reportdate,
bw.jumlah_jam_kerja,
a.wonum,
a.reportdate,
CASE
WHEN COUNT(b.laborcode) FILTER (WHERE b.laborcode IS NOT NULL) > 0 THEN
SUM(
COALESCE(emp_cost.salary_per_hour_idr,
(SELECT salary_per_hour_idr FROM lcc_manpower_cost WHERE UPPER(staff_job_level) = UPPER('Junior') LIMIT 1))
* bw.jumlah_jam_kerja
)
ELSE
3 * (SELECT salary_per_hour_idr FROM lcc_manpower_cost WHERE UPPER(staff_job_level) = UPPER('Junior') LIMIT 1) * bw.jumlah_jam_kerja
END AS upah_per_wonum
FROM (
SELECT
a.wonum,
a.reportdate,
CASE
WHEN (EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0) = 0
THEN 1
ELSE (EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0)
END AS jumlah_jam_kerja
FROM public.wo_maximo a
WHERE
a.asset_unit = '3'
AND a.wonum NOT LIKE 'T%'
AND a.asset_assetnum = %s
AND (EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0) <= 730
{worktype_condition}
{exclude_condition}
) bw
LEFT JOIN public.wo_maximo_labtrans b ON b.wonum = bw.wonum
LEFT JOIN lcc_ms_manpower emp ON UPPER(TRIM(emp."ID Number")) = UPPER(TRIM(b.laborcode))
LEFT JOIN lcc_manpower_cost emp_cost ON UPPER(TRIM(emp_cost.staff_job_level)) = UPPER(TRIM(emp."Position"))
GROUP BY bw.wonum, bw.reportdate, bw.jumlah_jam_kerja
) x
GROUP BY 1
ORDER BY 1;
WHEN (EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0) = 0
THEN 1
ELSE (EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0)
END AS jumlah_jam_kerja
FROM public.wo_maximo a
WHERE
a.asset_unit = '3'
AND a.wonum NOT LIKE 'T%'
AND a.asset_assetnum = '{assetnum}'
AND (EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0) <= 730
AND a.worktype = '{worktype}'
AND (
a.description NOT ILIKE '%U4%'
OR (
a.description ILIKE '%U3%'
AND a.description ILIKE '%U4%'
)
)
) bw
LEFT JOIN public.wo_maximo_labtrans b
ON b.wonum = bw.wonum
LEFT JOIN lcc_ms_manpower emp
ON UPPER(TRIM(emp."ID Number")) = UPPER(TRIM(b.laborcode))
LEFT JOIN lcc_manpower_cost emp_cost
ON UPPER(TRIM(emp_cost.staff_job_level)) = UPPER(TRIM(emp."Position"))
GROUP BY
bw.wonum, bw.reportdate, bw.jumlah_jam_kerja
) x
GROUP BY 1
ORDER BY 1;
"""
try:
cursor.execute(query, tuple(worktype_params))
cursor.execute(query)
rows = cursor.fetchall()
except Exception as exc:
print(f"Error fetching labour cost for {assetnum} ({worktype}): {exc}")
return {}
labour_costs = {}
for tahun, total in rows:
for row in rows:
if isinstance(row, dict):
tahun_value = row.get("tahun")
total_value = row.get("total_upah_per_tahun")
else:
try:
tahun_value, total_value = row[0], row[1]
except (IndexError, TypeError):
continue
try:
year_int = int(tahun) if tahun is not None else None
year_int = int(tahun_value) if tahun_value is not None else None
except (TypeError, ValueError):
year_int = None
if year_int is None:
continue
try:
labour_costs[year_int] = float(total) if total is not None else 0.0
labour_costs[year_int] = float(total_value) if total_value is not None else 0.0
except (TypeError, ValueError):
labour_costs[year_int] = 0.0
@ -331,8 +343,6 @@ def _build_tr_row_values(
"raw_predictive_material_cost": 0,
"raw_predictive_labor_time": 0,
"raw_predictive_labor_human": 0,
"raw_loss_output_MW": 0,
"raw_loss_output_price": 0,
"rc_cm_material_cost": 0,
"rc_cm_labor_cost": 0,
"rc_pm_material_cost": 0,
@ -371,17 +381,6 @@ def _build_tr_row_values(
data_predictive_row, "raw_predictive_labor_human"
)
# raw_loss_output_MW = (
# data_tahunan_row.get("total_lost")
# if data_tahunan_row and data_tahunan_row.get("total_lost") is not None
# else 0
# )
# raw_loss_output_price = (
# data_tahunan_row.get("rp_per_kwh")
# if data_tahunan_row and data_tahunan_row.get("rp_per_kwh") is not None
# else 0
# )
man_hour_value = (
data_tahunan_row.get("man_hour")
if data_tahunan_row and data_tahunan_row.get("man_hour") is not None
@ -389,48 +388,48 @@ def _build_tr_row_values(
)
rc_cm_material_cost = raw_cm_material_cost_total
rc_cm_labor_cost = (
data_cm_row.get("raw_cm_labor_time")
* data_cm_row.get("rc_cm_labor_human")
* man_hour_value
if data_cm_row
and data_cm_row.get("rc_cm_labor_cost")
and data_cm_row.get("rc_cm_labor_human")
and man_hour_value is not None
else 0
)
# rc_cm_labor_cost = (
# data_cm_row.get("raw_cm_labor_time")
# * data_cm_row.get("rc_cm_labor_human")
# * man_hour_value
# if data_cm_row
# and data_cm_row.get("rc_cm_labor_cost")
# and data_cm_row.get("rc_cm_labor_human")
# and man_hour_value is not None
# else 0
# )
rc_pm_material_cost = raw_pm_material_cost
rc_pm_labor_cost = (
data_pm_row.get("raw_pm_labor_time")
* data_pm_row.get("rc_pm_labor_human")
* man_hour_value
if data_pm_row
and data_pm_row.get("rc_pm_labor_cost")
and data_pm_row.get("rc_pm_labor_human")
and man_hour_value is not None
else 0
)
# rc_pm_labor_cost = (
# data_pm_row.get("raw_pm_labor_time")
# * data_pm_row.get("rc_pm_labor_human")
# * man_hour_value
# if data_pm_row
# and data_pm_row.get("rc_pm_labor_cost")
# and data_pm_row.get("rc_pm_labor_human")
# and man_hour_value is not None
# else 0
# )
rc_oh_material_cost = raw_oh_material_cost
rc_oh_labor_cost = (
data_oh_row.get("raw_oh_labor_time")
* data_oh_row.get("rc_oh_labor_human")
* man_hour_value
if data_oh_row
and data_oh_row.get("rc_oh_labor_cost")
and data_oh_row.get("rc_oh_labor_human")
and man_hour_value is not None
else 0
)
# rc_oh_labor_cost = (
# data_oh_row.get("raw_oh_labor_time")
# * data_oh_row.get("rc_oh_labor_human")
# * man_hour_value
# if data_oh_row
# and data_oh_row.get("rc_oh_labor_cost")
# and data_oh_row.get("rc_oh_labor_human")
# and man_hour_value is not None
# else 0
# )
rc_predictive_labor_cost = (
data_predictive_row.get("raw_predictive_labor_human") * man_hour_value
if data_predictive_row
and data_predictive_row.get("rc_predictive_labor_cost")
and man_hour_value is not None
else 0
)
# rc_predictive_labor_cost = (
# data_predictive_row.get("raw_predictive_labor_human") * man_hour_value
# if data_predictive_row
# and data_predictive_row.get("rc_predictive_labor_cost")
# and man_hour_value is not None
# else 0
# )
if labour_cost_lookup and year is not None:
cm_lookup = labour_cost_lookup.get("CM", {})
@ -442,27 +441,10 @@ def _build_tr_row_values(
pm_value = pm_lookup.get(year)
oh_value = oh_lookup.get(year)
pdm_value = pdm_lookup.get(year)
if cm_value is not None:
try:
rc_cm_labor_cost = float(cm_value)
except (TypeError, ValueError):
rc_cm_labor_cost = 0.0
if pm_value is not None:
try:
rc_pm_labor_cost = float(pm_value)
except (TypeError, ValueError):
rc_pm_labor_cost = 0.0
if oh_value is not None:
try:
rc_oh_labor_cost = float(oh_value)
except (TypeError, ValueError):
rc_oh_labor_cost = 0.0
if pdm_value is not None:
try:
rc_predictive_labor_cost = float(pdm_value)
except (TypeError, ValueError):
rc_predictive_labor_cost = 0.0
rc_cm_labor_cost = float(cm_value) if cm_value is not None else 0.0
rc_pm_labor_cost = float(pm_value) if pm_value is not None else 0.0
rc_oh_labor_cost = float(oh_value) if oh_value is not None else 0.0
rc_predictive_labor_cost = float(pdm_value) if pdm_value is not None else 0.0
return {
"raw_cm_interval": raw_cm_interval,
@ -481,8 +463,6 @@ def _build_tr_row_values(
"raw_predictive_material_cost": raw_pdm_material_cost,
"raw_predictive_labor_time": raw_pdm_labor_time,
"raw_predictive_labor_human": raw_pdm_labor_human,
# "raw_loss_output_MW": raw_loss_output_MW,
# "raw_loss_output_price": raw_loss_output_price,
"rc_cm_material_cost": rc_cm_material_cost,
"rc_cm_labor_cost": rc_cm_labor_cost,
"rc_pm_material_cost": rc_pm_material_cost,
@ -931,7 +911,6 @@ async def query_data():
raw_pm_interval, raw_pm_material_cost, raw_pm_labor_time, raw_pm_labor_human,
raw_oh_interval, raw_oh_material_cost, raw_oh_labor_time, raw_oh_labor_human,
raw_predictive_interval, raw_predictive_material_cost, raw_predictive_labor_time, raw_predictive_labor_human,
"raw_loss_output_MW", raw_loss_output_price,
"rc_cm_material_cost", "rc_cm_labor_cost",
"rc_pm_material_cost", "rc_pm_labor_cost",
"rc_oh_material_cost", "rc_oh_labor_cost",
@ -946,7 +925,6 @@ async def query_data():
%s, %s,
%s, %s,
%s, %s,
%s, %s,
%s,
'Sys', NOW()
)
@ -972,8 +950,6 @@ async def query_data():
raw_predictive_material_cost = %s,
raw_predictive_labor_time = %s,
raw_predictive_labor_human = %s,
"raw_loss_output_MW" = %s,
raw_loss_output_price = %s,
"rc_cm_material_cost" = %s,
"rc_cm_labor_cost" = %s,
"rc_pm_material_cost" = %s,
@ -1114,8 +1090,6 @@ async def query_data():
row_values["raw_predictive_material_cost"],
row_values["raw_predictive_labor_time"],
row_values["raw_predictive_labor_human"],
row_values["raw_loss_output_MW"],
row_values["raw_loss_output_price"],
row_values["rc_cm_material_cost"],
row_values["rc_cm_labor_cost"],
row_values["rc_pm_material_cost"],
@ -1149,8 +1123,6 @@ async def query_data():
row_values["raw_predictive_material_cost"],
row_values["raw_predictive_labor_time"],
row_values["raw_predictive_labor_human"],
row_values["raw_loss_output_MW"],
row_values["raw_loss_output_price"],
row_values["rc_cm_material_cost"],
row_values["rc_cm_labor_cost"],
row_values["rc_pm_material_cost"],
@ -1162,6 +1134,8 @@ async def query_data():
year,
),
)
inserted_this_asset += 1
total_inserted += 1
seq = seq + 1
# commit per asset to persist progress and free transaction

6
src/modules/equipment/run.py
Unescape Escape View File

@ -23,12 +23,6 @@ async def main():
print(f"Error in query_data: {str(e)}")
return
try:
await insert_acquisition_cost_data()
except Exception as e:
print(f"Error in insert_acquisition_cost_data: {str(e)}")
return
try:
await predict_run()
except Exception as e:

28
src/modules/plant/run2.py
Unescape Escape View File

@ -349,9 +349,31 @@ def main():
revenue_c = price_c * production_netto * 1000 / 1000000
revenue_d = price_d * production_netto * 1000 / 1000000
cost_c_fuel = fuel_consumption * harga_bahan_bakar / 1000000
cost_bd_om = cost_bd_om # last value
cost_bd_pm_nonmi = cost_bd_pm_nonmi # last value
cost_bd_bd = cost_bd_bd # last value
# Linear prediction for cost_bd_om, cost_bd_pm_nonmi, cost_bd_bd
# Use last 2 actual values to predict next value (simple linear extrapolation)
def linear_predict(last_vals):
if len(last_vals) >= 2:
return last_vals[-1] + (last_vals[-1] - last_vals[-2])
elif len(last_vals) == 1:
return last_vals[-1]
else:
return 0
# Collect actual values up to now
if not hasattr(main, "_cost_bd_om_actuals"):
main._cost_bd_om_actuals = []
main._cost_bd_pm_nonmi_actuals = []
main._cost_bd_bd_actuals = []
# If actual, append to history
if data["is_actual"] == 1:
main._cost_bd_om_actuals.append(cost_bd_om)
main._cost_bd_pm_nonmi_actuals.append(cost_bd_pm_nonmi)
main._cost_bd_bd_actuals.append(cost_bd_bd)
else:
cost_bd_om = linear_predict(main._cost_bd_om_actuals)
cost_bd_pm_nonmi = linear_predict(main._cost_bd_pm_nonmi_actuals)
cost_bd_bd = linear_predict(main._cost_bd_bd_actuals)
net_capacity_factor = net_capacity_factor_v
eaf = eaf_v

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