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docs(config): 발주 주기가 월 단위 정기 발주임을 근거로 기록 (이슈 #54 요청 1번) #64

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choigod1023 merged 2 commits into from
Aug 16, 2026
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docs(config): 발주 주기가 월 단위 정기 발주임을 근거로 기록 (이슈 #54 요청 1번) #64

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docs(config): 발주 주기가 월 단위 정기 발주임을 상수 옆에 근거로 기록 (이슈 #54)
choigod1023 Aug 10, 2026
743537f
docs: 정기검토 확정 상태 반영, DB 재계산은 별도 PR임을 명시 (ai#64 리뷰 반영)
choigod1023 Aug 13, 2026
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10 changes: 10 additions & 0 deletions src/config.py
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Original file line number Diff line number Diff line change
Expand Up @@ -396,6 +396,16 @@ def _bulk_approval_is_active() -> bool:
DEMAND_RISK_BUFFER_RATE = 0.20
SUPPLY_RISK_BUFFER_RATE = 0.20
MATERIAL_RISK_BUFFER_RATE = 0.10

# 발주 주기 — 보건기관은 재고 소진 시 수시 발주가 아니라 월 단위로 정기 발주한다.
# 확인: 2026-07-30 reo-23, 이슈 #54 (조달 실무 확인 결과)
# 그래서 재고 모형은 연속검토(ROP 도달 시 발주)가 아니라 정기검토를 쓴다.
# 보호기간 = 검토주기 + 리드타임 이며 src/modeling/inventory_policy.py 가 이를 따른다.
#
# ⚠️ backend 는 연속검토 식(SS = z·σ·√L, ROP = μ·L + SS)으로 운영 DB 를 채워 왔다.
# 두 모형이 공존하던 문제가 #54 이고, 실무 확인으로 정기검토가 정본임이 확정됐다.
# 운영 DB 재산정은 별도 PR 로 다룬다 — src/loading/apply_inventory_policy.py 는
# 그때까지 ss/rop/target/status/order_recommendation 을 쓰지 않는다.
DEFAULT_REVIEW_PERIOD_DAYS = 30
DEFAULT_LEAD_TIME_DAYS = 15

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14 changes: 9 additions & 5 deletions src/loading/apply_inventory_policy.py
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@@ -1,13 +1,17 @@
"""Apply AI demand statistics to DB inventory without choosing an SS/ROP model.

Issue #54 records an unresolved policy conflict:
Issue #54 recorded a policy conflict between two models:

* backend: continuous review, ``SS=z*sigma*sqrt(L)``, ``ROP=mu*L+SS``
* AI: periodic review plus lead time, fixed/risk-adjusted target stock

Until the ordering cadence and one canonical policy are approved, this loader
updates only demand statistics and classification fields. It deliberately does
not write ``ss``, ``rop``, ``target``, ``status`` or ``order_recommendation``.
The cadence question is resolved (ai#54 request 1, 2026-07-30 confirmation from
reo-23): institutions place orders on a monthly cadence, so periodic review is
the canonical model. What is NOT yet done is applying that decision to the DB —
the SS/ROP recalculation itself is a separate, still-pending PR. Until that PR
lands, this loader updates only demand statistics and classification fields. It
deliberately does not write ``ss``, ``rop``, ``target``, ``status`` or
``order_recommendation``.

Run with ``DRY_RUN=1`` first. ``DRY_RUN=0`` commits the restricted update.
"""
Expand Down Expand Up @@ -121,7 +125,7 @@ def main() -> None:
)
print(
"보호 범위: SS/ROP/target/status/order_recommendation "
"(ai#54 결정 전 미변경)"
"(정기검토 모형 확정됨(ai#54 요청1) — DB 재계산은 별도 PR 대기, 이 로더는 미변경)"
)

with psycopg.connect(os.environ["DATABASE_URL"]) as conn:
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