컬럼명칭 통일 C-xxxxx + SIGPIPE 대응 + SteamAdvisor/FF 개선

=== 컬럼명칭 통일 (c{prefix} → C-{prefix}11) === Python 분석스크립트: data pkl 경로 → gen_temp_profiles: tempref 파일명 → SteamAdvisorController: TagsFor() 숫자서픽스 → 풀컬럼키(C-6111), ToSuffix() 변환 steam.js: ST_TEMP_COLS ['61',...] → ['C-6111',...], selectbox defaultColumn appsettings.json: Columns 키 c61/c62/... → C-6111/C-6211/..., DefaultColumn c6111→C-6111 run_column.py: 추출/분석시 col_key = f"C-{{prefix}}11" C-{x}11_{model,tempref}.json: 신규 명칭 기준 기준프로파일/모델 7컬럼분 === SteamAdvisor 수정 === SteamModel: [JsonPropertyName] 매핑(snake_case → PascalCase 역직렬화) 예외처리: LinearCoeffs.Count < 3 방어코드 steam.js: catch(_) {} → 에러메시지 표시, missing_tags 응답처리 === Feedforward Controller 개선 === ff.js: 상승/하강 양방향 램프 confirm, 방향뱃지(↑↓), Normal 모드 표시 FeedforwardController: 업램프 단독제한 제거(양방향), tcReturnTcTarget/Band 노출 === DB === Hc900DbContext: realtime_table_tagname_key 레거시 UNIQUE 제약/인덱스 DROP 로직 Hc900Controllers: ToDictionaryAsync → GroupBy 변환 (중복 tagname 대응) === SIGPIPE 대응 === gateway.cpp: signal(SIGPIPE, SIG_IGN) 메인스레드 설치 modbus_tcp.cpp: send() flags 0 → MSG_NOSIGNAL (EPIPE 복구) sigpipe_ignore.c: LD_PRELOAD 우회 공유라이브러리 Hc900GatewayProcessService: LD_PRELOAD 환경변수 설정
2026-06-07 00:29:47 +09:00
parent 7b21c35af6
commit 7409fabc58
42 changed files with 1483 additions and 79 deletions
--- a/scripts/analysis/C-10111_model.json
+++ b/scripts/analysis/C-10111_model.json
@@ -0,0 +1,34 @@
+{
+  "column": "C-10111",
+  "features": [
+    "feed",
+    "product",
+    "T_C"
+  ],
+  "linear_coeffs": [
+    -0.4608333188018109,
+    0.030778679890158908,
+    8.364320439105626
+  ],
+  "intercept": 284.18717440136294,
+  "linear_r2": 0.2019,
+  "gbm_r2": 0.9981,
+  "valve_poly": [
+    -1.4012718976320648e-07,
+    0.0003106626129801823,
+    -0.18598847329591273,
+    85.81924723424272
+  ],
+  "envelope_lo": {
+    "feed": 693.5,
+    "product": 104.9,
+    "T_C": 58.8
+  },
+  "envelope_hi": {
+    "feed": 1264.4,
+    "product": 1005.0,
+    "T_C": 81.8
+  },
+  "n_operating_points": 23,
+  "n_prod_rows": 5098
+}
--- a/scripts/analysis/C-10111_tempref.json
+++ b/scripts/analysis/C-10111_tempref.json
@@ -0,0 +1,67 @@
+{
+  "column": "C-10111",
+  "stages_order": [
+    "reb_temp",
+    "T_B",
+    "T_C",
+    "T_D"
+  ],
+  "n_products": 2,
+  "period": "2026-02-20~2026-04-13",
+  "products": [
+    {
+      "label": "P0",
+      "n_rows": 361,
+      "span_AD": 9.02,
+      "vacuum": {
+        "median": 45.12,
+        "std": 13.38
+      },
+      "stages": {
+        "reb_temp": {
+          "median": 78.78,
+          "std": 4.2
+        },
+        "T_B": {
+          "median": 77.64,
+          "std": 11.64
+        },
+        "T_C": {
+          "median": 71.75,
+          "std": 8.56
+        },
+        "T_D": {
+          "median": 69.84,
+          "std": 8.77
+        }
+      }
+    },
+    {
+      "label": "P1",
+      "n_rows": 4897,
+      "span_AD": 3.22,
+      "vacuum": {
+        "median": 76.95,
+        "std": 3.59
+      },
+      "stages": {
+        "reb_temp": {
+          "median": 84.3,
+          "std": 0.67
+        },
+        "T_B": {
+          "median": 83.46,
+          "std": 3.33
+        },
+        "T_C": {
+          "median": 81.71,
+          "std": 4.32
+        },
+        "T_D": {
+          "median": 81.28,
+          "std": 7.14
+        }
+      }
+    }
+  ]
+}
--- a/scripts/analysis/C-10211_model.json
+++ b/scripts/analysis/C-10211_model.json
@@ -0,0 +1,34 @@
+{
+  "column": "C-10211",
+  "features": [
+    "feed",
+    "product",
+    "T_C"
+  ],
+  "linear_coeffs": [
+    0.9294864374761924,
+    -0.15452592481820945,
+    -4.355733003639835
+  ],
+  "intercept": 51.96343762286648,
+  "linear_r2": 0.2824,
+  "gbm_r2": 0.999,
+  "valve_poly": [
+    6.752259912738752e-08,
+    -0.00010864860285235597,
+    0.0801331606949025,
+    7.741006044043883
+  ],
+  "envelope_lo": {
+    "feed": 590.9,
+    "product": 271.8,
+    "T_C": 78.1
+  },
+  "envelope_hi": {
+    "feed": 838.3,
+    "product": 760.9,
+    "T_C": 79.4
+  },
+  "n_operating_points": 30,
+  "n_prod_rows": 20701
+}
--- a/scripts/analysis/C-10211_tempref.json
+++ b/scripts/analysis/C-10211_tempref.json
@@ -0,0 +1,67 @@
+{
+  "column": "C-10211",
+  "stages_order": [
+    "reb_temp",
+    "T_B",
+    "T_C",
+    "T_D"
+  ],
+  "n_products": 2,
+  "period": "2026-05-26~2026-06-02",
+  "products": [
+    {
+      "label": "P0",
+      "n_rows": 19649,
+      "span_AD": 4.62,
+      "vacuum": {
+        "median": 49.97,
+        "std": 0.22
+      },
+      "stages": {
+        "reb_temp": {
+          "median": 82.45,
+          "std": 0.79
+        },
+        "T_B": {
+          "median": 81.52,
+          "std": 0.87
+        },
+        "T_C": {
+          "median": 78.91,
+          "std": 0.65
+        },
+        "T_D": {
+          "median": 78.03,
+          "std": 0.97
+        }
+      }
+    },
+    {
+      "label": "P1",
+      "n_rows": 1080,
+      "span_AD": 23.54,
+      "vacuum": {
+        "median": 49.97,
+        "std": 0.16
+      },
+      "stages": {
+        "reb_temp": {
+          "median": 87.58,
+          "std": 1.08
+        },
+        "T_B": {
+          "median": 85.04,
+          "std": 1.58
+        },
+        "T_C": {
+          "median": 78.36,
+          "std": 2.07
+        },
+        "T_D": {
+          "median": 64.54,
+          "std": 4.55
+        }
+      }
+    }
+  ]
+}
--- a/scripts/analysis/C-6111_model.json
+++ b/scripts/analysis/C-6111_model.json
@@ -0,0 +1,34 @@
+{
+  "column": "C-6111",
+  "features": [
+    "feed",
+    "product",
+    "T_C"
+  ],
+  "linear_coeffs": [
+    0.7327615829237054,
+    -0.02428538513646001,
+    7.063793833539203
+  ],
+  "intercept": -585.4115834877662,
+  "linear_r2": 0.9861,
+  "gbm_r2": 0.9949,
+  "valve_poly": [
+    4.5825416007577506e-07,
+    -0.000721366513035835,
+    0.41181608994764535,
+    -42.70089479377073
+  ],
+  "envelope_lo": {
+    "feed": 380.5,
+    "product": 329.2,
+    "T_C": 83.9
+  },
+  "envelope_hi": {
+    "feed": 911.8,
+    "product": 824.0,
+    "T_C": 86.1
+  },
+  "n_operating_points": 479,
+  "n_prod_rows": 333626
+}
--- a/scripts/analysis/C-6111_tempref.json
+++ b/scripts/analysis/C-6111_tempref.json
@@ -0,0 +1,67 @@
+{
+  "column": "C-6111",
+  "stages_order": [
+    "reb_temp",
+    "T_B",
+    "T_C",
+    "T_D"
+  ],
+  "n_products": 2,
+  "period": "2026-02-05~2026-06-05",
+  "products": [
+    {
+      "label": "P0",
+      "n_rows": 171623,
+      "span_AD": 1.69,
+      "vacuum": {
+        "median": 112.99,
+        "std": 0.38
+      },
+      "stages": {
+        "reb_temp": {
+          "median": 84.81,
+          "std": 0.5
+        },
+        "T_B": {
+          "median": 84.33,
+          "std": 0.43
+        },
+        "T_C": {
+          "median": 84.07,
+          "std": 0.28
+        },
+        "T_D": {
+          "median": 83.12,
+          "std": 0.15
+        }
+      }
+    },
+    {
+      "label": "P1",
+      "n_rows": 162003,
+      "span_AD": 4.56,
+      "vacuum": {
+        "median": 113.01,
+        "std": 0.68
+      },
+      "stages": {
+        "reb_temp": {
+          "median": 87.48,
+          "std": 0.69
+        },
+        "T_B": {
+          "median": 86.54,
+          "std": 0.56
+        },
+        "T_C": {
+          "median": 85.48,
+          "std": 0.39
+        },
+        "T_D": {
+          "median": 82.92,
+          "std": 0.1
+        }
+      }
+    }
+  ]
+}
--- a/scripts/analysis/C-6211_model.json
+++ b/scripts/analysis/C-6211_model.json
@@ -0,0 +1,34 @@
+{
+  "column": "C-6211",
+  "features": [
+    "feed",
+    "product",
+    "T_C"
+  ],
+  "linear_coeffs": [
+    0.4192774636696495,
+    -0.0031327650421361097,
+    56.90599492143593
+  ],
+  "intercept": -4696.245060756706,
+  "linear_r2": 0.9965,
+  "gbm_r2": 0.998,
+  "valve_poly": [
+    3.2700894960484994e-07,
+    -0.0005053236912242627,
+    0.31737798932141487,
+    -3.9334436250422447
+  ],
+  "envelope_lo": {
+    "feed": 391.1,
+    "product": 355.8,
+    "T_C": 84.0
+  },
+  "envelope_hi": {
+    "feed": 906.3,
+    "product": 823.4,
+    "T_C": 86.9
+  },
+  "n_operating_points": 479,
+  "n_prod_rows": 332544
+}
--- a/scripts/analysis/C-6211_tempref.json
+++ b/scripts/analysis/C-6211_tempref.json
@@ -0,0 +1,67 @@
+{
+  "column": "C-6211",
+  "stages_order": [
+    "reb_temp",
+    "T_B",
+    "T_C",
+    "T_D"
+  ],
+  "n_products": 2,
+  "period": "2026-02-05~2026-06-05",
+  "products": [
+    {
+      "label": "P0",
+      "n_rows": 264621,
+      "span_AD": 2.09,
+      "vacuum": {
+        "median": 113.01,
+        "std": 0.33
+      },
+      "stages": {
+        "reb_temp": {
+          "median": 85.41,
+          "std": 0.78
+        },
+        "T_B": {
+          "median": 84.86,
+          "std": 0.93
+        },
+        "T_C": {
+          "median": 84.19,
+          "std": 0.8
+        },
+        "T_D": {
+          "median": 83.25,
+          "std": 1.19
+        }
+      }
+    },
+    {
+      "label": "P1",
+      "n_rows": 68534,
+      "span_AD": 7.58,
+      "vacuum": {
+        "median": 113.01,
+        "std": 0.32
+      },
+      "stages": {
+        "reb_temp": {
+          "median": 90.43,
+          "std": 1.1
+        },
+        "T_B": {
+          "median": 88.21,
+          "std": 0.55
+        },
+        "T_C": {
+          "median": 86.72,
+          "std": 0.44
+        },
+        "T_D": {
+          "median": 82.85,
+          "std": 0.08
+        }
+      }
+    }
+  ]
+}
--- a/scripts/analysis/C-8111_model.json
+++ b/scripts/analysis/C-8111_model.json
@@ -0,0 +1,34 @@
+{
+  "column": "C-8111",
+  "features": [
+    "feed",
+    "product",
+    "T_C"
+  ],
+  "linear_coeffs": [
+    0.07625525560006084,
+    0.039701856173688654,
+    13.98648334581965
+  ],
+  "intercept": -960.7734208999705,
+  "linear_r2": 0.659,
+  "gbm_r2": 0.8313,
+  "valve_poly": [
+    1.8890153721106516e-06,
+    -0.0015596046011240288,
+    0.5296293071190988,
+    -14.478452900869977
+  ],
+  "envelope_lo": {
+    "feed": 650.8,
+    "product": 581.9,
+    "T_C": 83.3
+  },
+  "envelope_hi": {
+    "feed": 781.4,
+    "product": 707.5,
+    "T_C": 86.5
+  },
+  "n_operating_points": 280,
+  "n_prod_rows": 199945
+}
--- a/scripts/analysis/C-8111_tempref.json
+++ b/scripts/analysis/C-8111_tempref.json
@@ -0,0 +1,67 @@
+{
+  "column": "C-8111",
+  "stages_order": [
+    "reb_temp",
+    "T_B",
+    "T_C",
+    "T_D"
+  ],
+  "n_products": 2,
+  "period": "2026-03-27~2026-06-05",
+  "products": [
+    {
+      "label": "P0",
+      "n_rows": 28459,
+      "span_AD": 15.16,
+      "vacuum": {
+        "median": 49.97,
+        "std": 0.14
+      },
+      "stages": {
+        "reb_temp": {
+          "median": 93.38,
+          "std": 1.02
+        },
+        "T_B": {
+          "median": 91.57,
+          "std": 0.91
+        },
+        "T_C": {
+          "median": 83.97,
+          "std": 0.54
+        },
+        "T_D": {
+          "median": 78.22,
+          "std": 0.13
+        }
+      }
+    },
+    {
+      "label": "P1",
+      "n_rows": 171490,
+      "span_AD": 16.36,
+      "vacuum": {
+        "median": 49.97,
+        "std": 0.18
+      },
+      "stages": {
+        "reb_temp": {
+          "median": 94.92,
+          "std": 0.66
+        },
+        "T_B": {
+          "median": 93.05,
+          "std": 0.62
+        },
+        "T_C": {
+          "median": 85.18,
+          "std": 0.51
+        },
+        "T_D": {
+          "median": 78.56,
+          "std": 0.12
+        }
+      }
+    }
+  ]
+}
--- a/scripts/analysis/C-9111_model.json
+++ b/scripts/analysis/C-9111_model.json
@@ -0,0 +1,34 @@
+{
+  "column": "C-9111",
+  "features": [
+    "feed",
+    "product",
+    "T_C"
+  ],
+  "linear_coeffs": [
+    0.07154616245940783,
+    0.41909641263227626,
+    -23.77111363563102
+  ],
+  "intercept": 2169.7017492750356,
+  "linear_r2": 0.746,
+  "gbm_r2": 0.9968,
+  "valve_poly": [
+    5.592609787272492e-09,
+    -8.2019564706617e-06,
+    0.03620454531728825,
+    17.7448717037642
+  ],
+  "envelope_lo": {
+    "feed": 254.0,
+    "product": 176.7,
+    "T_C": 73.5
+  },
+  "envelope_hi": {
+    "feed": 1427.6,
+    "product": 1342.0,
+    "T_C": 82.5
+  },
+  "n_operating_points": 161,
+  "n_prod_rows": 107198
+}
--- a/scripts/analysis/C-9111_tempref.json
+++ b/scripts/analysis/C-9111_tempref.json
@@ -0,0 +1,40 @@
+{
+  "column": "C-9111",
+  "stages_order": [
+    "reb_temp",
+    "T_B",
+    "T_C",
+    "T_D"
+  ],
+  "n_products": 1,
+  "period": "2026-02-26~2026-06-05",
+  "products": [
+    {
+      "label": "P0",
+      "n_rows": 163236,
+      "span_AD": 2.29,
+      "vacuum": {
+        "median": 76.99,
+        "std": 6.51
+      },
+      "stages": {
+        "reb_temp": {
+          "median": 83.63,
+          "std": 1.82
+        },
+        "T_B": {
+          "median": 83.49,
+          "std": 2.31
+        },
+        "T_C": {
+          "median": 82.16,
+          "std": 3.69
+        },
+        "T_D": {
+          "median": 81.54,
+          "std": 4.32
+        }
+      }
+    }
+  ]
+}
--- a/scripts/analysis/C-9211_model.json
+++ b/scripts/analysis/C-9211_model.json
@@ -0,0 +1,34 @@
+{
+  "column": "C-9211",
+  "features": [
+    "feed",
+    "product",
+    "T_C"
+  ],
+  "linear_coeffs": [
+    0.22082559721551914,
+    0.41742853431313043,
+    6.570197052019047
+  ],
+  "intercept": -479.59199642741356,
+  "linear_r2": 0.5715,
+  "gbm_r2": 0.9835,
+  "valve_poly": [
+    5.864565272695953e-07,
+    -0.0006161781631431878,
+    0.28501938580083425,
+    -15.01586412685447
+  ],
+  "envelope_lo": {
+    "feed": 269.7,
+    "product": 98.7,
+    "T_C": 74.7
+  },
+  "envelope_hi": {
+    "feed": 453.6,
+    "product": 397.4,
+    "T_C": 90.2
+  },
+  "n_operating_points": 242,
+  "n_prod_rows": 165829
+}
--- a/scripts/analysis/C-9211_tempref.json
+++ b/scripts/analysis/C-9211_tempref.json
@@ -0,0 +1,94 @@
+{
+  "column": "C-9211",
+  "stages_order": [
+    "reb_temp",
+    "T_B",
+    "T_C",
+    "T_D"
+  ],
+  "n_products": 3,
+  "period": "2026-02-26~2026-06-04",
+  "products": [
+    {
+      "label": "P0",
+      "n_rows": 8412,
+      "span_AD": 10.75,
+      "vacuum": {
+        "median": 40.13,
+        "std": 3.79
+      },
+      "stages": {
+        "reb_temp": {
+          "median": 85.1,
+          "std": 2.34
+        },
+        "T_B": {
+          "median": 83.29,
+          "std": 2.14
+        },
+        "T_C": {
+          "median": 77.03,
+          "std": 1.44
+        },
+        "T_D": {
+          "median": 74.15,
+          "std": 1.57
+        }
+      }
+    },
+    {
+      "label": "P1",
+      "n_rows": 138164,
+      "span_AD": 9.43,
+      "vacuum": {
+        "median": 50.01,
+        "std": 3.82
+      },
+      "stages": {
+        "reb_temp": {
+          "median": 88.31,
+          "std": 0.79
+        },
+        "T_B": {
+          "median": 87.03,
+          "std": 0.72
+        },
+        "T_C": {
+          "median": 81.37,
+          "std": 0.97
+        },
+        "T_D": {
+          "median": 78.88,
+          "std": 1.79
+        }
+      }
+    },
+    {
+      "label": "P2",
+      "n_rows": 19405,
+      "span_AD": 12.77,
+      "vacuum": {
+        "median": 79.57,
+        "std": 14.99
+      },
+      "stages": {
+        "reb_temp": {
+          "median": 93.72,
+          "std": 1.99
+        },
+        "T_B": {
+          "median": 92.58,
+          "std": 2.04
+        },
+        "T_C": {
+          "median": 89.38,
+          "std": 3.57
+        },
+        "T_D": {
+          "median": 79.21,
+          "std": 5.1
+        }
+      }
+    }
+  ]
+}
--- a/scripts/analysis/c6111_export_model.py
+++ b/scripts/analysis/c6111_export_model.py
@@ -20,8 +20,8 @@ FEATURES = ["feed", "product", "T_C"]

 def main():
    parser = argparse.ArgumentParser()
-    parser.add_argument("--data", default=BASE + "c6111_data.pkl")
-    parser.add_argument("--prefix", default="c6111")
+    parser.add_argument("--data", default=BASE + "C-6111_data.pkl")
+    parser.add_argument("--prefix", default="C-6111")
    parser.add_argument("--output", help="JSON 출력 경로 (기본: scripts/analysis/{prefix}_model.json)")
    args = parser.parse_args()
    df = pd.read_pickle(args.data)
--- a/scripts/analysis/c6111_extract.py
+++ b/scripts/analysis/c6111_extract.py
@@ -241,7 +241,7 @@ def main():
    for m, n in vc.items():
        print(f"  {m:9s} {n:7d}  {100*n/len(df):5.1f}%  ≈ {n*30/3600:7.1f} h")

-    out = "/home/windpacer/projects/hc900_ax/scripts/analysis/c6111_data.pkl"
+    out = "/home/windpacer/projects/hc900_ax/scripts/analysis/C-6111_data.pkl"
    df.to_pickle(out)
    plot_timeline(df, "/home/windpacer/projects/hc900_ax/scripts/analysis/c6111_timeline.png")
    print(f"저장: {out}")
--- a/scripts/analysis/c6111_operator_assist.py
+++ b/scripts/analysis/c6111_operator_assist.py
@@ -127,8 +127,8 @@ class OperatorAssist:

 def main():
    parser = argparse.ArgumentParser()
-    parser.add_argument("--data", default=BASE + "c6111_data.pkl")
-    parser.add_argument("--prefix", default="c6111")
+    parser.add_argument("--data", default=BASE + "C-6111_data.pkl")
+    parser.add_argument("--prefix", default="C-6111")
    parser.add_argument("--live", help='JSON live_tags for single predict test')
    args = parser.parse_args()
    df = pd.read_pickle(args.data)
--- a/scripts/analysis/c6111_prodmap.py
+++ b/scripts/analysis/c6111_prodmap.py
@@ -25,7 +25,7 @@ OP_RESAMPLE = "6h"

 def load(data_path=None):
    if data_path is None:
-        data_path = BASE + "c6111_data.pkl"
+        data_path = BASE + "C-6111_data.pkl"
    df = pd.read_pickle(data_path)
    df = df[df["mode"] == "PROD"].copy()
    # 엔지니어링 피처: 온도 구배(분리도)
@@ -100,7 +100,7 @@ def regress(df):
    return ops, gbm, Xte, yte, gbm.predict(Xte), imp


-def plots(hb, ops, yte, pred, imp, prefix="c6111"):
+def plots(hb, ops, yte, pred, imp, prefix="C-6111"):
    fig, ax = plt.subplots(1, 4, figsize=(22, 5))
    ax[0].scatter(hb["op"], hb["flow"], s=20, c="k", label="mean")
    ax[0].plot(hb["op"], hb["flow_up"], "b.-", ms=4, label="OP rising")
@@ -121,8 +121,8 @@ def plots(hb, ops, yte, pred, imp, prefix="c6111"):

 def main():
    parser = argparse.ArgumentParser()
-    parser.add_argument("--data", default=BASE + "c6111_data.pkl")
-    parser.add_argument("--prefix", default="c6111")
+    parser.add_argument("--data", default=BASE + "C-6111_data.pkl")
+    parser.add_argument("--prefix", default="C-6111")
    args = parser.parse_args()
    df = load(args.data)
    print(f"PROD 정합데이터 {len(df)}행")
--- a/scripts/analysis/c6111_rolling.py
+++ b/scripts/analysis/c6111_rolling.py
@@ -18,8 +18,8 @@ RETRAIN_EVERY = "1D"

 def main():
    parser = argparse.ArgumentParser()
-    parser.add_argument("--data", default=BASE + "c6111_data.pkl")
-    parser.add_argument("--prefix", default="c6111")
+    parser.add_argument("--data", default=BASE + "C-6111_data.pkl")
+    parser.add_argument("--prefix", default="C-6111")
    args = parser.parse_args()
    df = pd.read_pickle(args.data)
    df = df[df["mode"] == "PROD"].copy()
--- a/scripts/analysis/c6111_shadow.py
+++ b/scripts/analysis/c6111_shadow.py
@@ -40,8 +40,8 @@ class SteamPredictor:

 def main():
    parser = argparse.ArgumentParser()
-    parser.add_argument("--data", default=BASE + "c6111_data.pkl")
-    parser.add_argument("--prefix", default="c6111")
+    parser.add_argument("--data", default=BASE + "C-6111_data.pkl")
+    parser.add_argument("--prefix", default="C-6111")
    args = parser.parse_args()
    df = pd.read_pickle(args.data)
    df = df[df["mode"] == "PROD"].copy()
--- a/scripts/analysis/c6111_shutdown.py
+++ b/scripts/analysis/c6111_shutdown.py
@@ -89,8 +89,8 @@ def shutdown_milestones(df, co):

 def main():
    parser = argparse.ArgumentParser()
-    parser.add_argument("--data", default=BASE + "c6111_data.pkl")
-    parser.add_argument("--prefix", default="c6111")
+    parser.add_argument("--data", default=BASE + "C-6111_data.pkl")
+    parser.add_argument("--prefix", default="C-6111")
    args = parser.parse_args()
    df = pd.read_pickle(args.data).sort_values("dtat").reset_index(drop=True)
    cutoffs = detect_cutoffs(df)
--- a/scripts/analysis/c6111_startup.py
+++ b/scripts/analysis/c6111_startup.py
@@ -60,8 +60,8 @@ def milestones(df, ci):

 def main():
    parser = argparse.ArgumentParser()
-    parser.add_argument("--data", default=BASE + "c6111_data.pkl")
-    parser.add_argument("--prefix", default="c6111")
+    parser.add_argument("--data", default=BASE + "C-6111_data.pkl")
+    parser.add_argument("--prefix", default="C-6111")
    args = parser.parse_args()
    df = pd.read_pickle(args.data).sort_values("dtat").reset_index(drop=True)
    cutins = detect_cutins(df)
--- a/scripts/analysis/c6111_trim.py
+++ b/scripts/analysis/c6111_trim.py
@@ -22,7 +22,7 @@ MOVE = 0.1        # OP 변경 인식 임계(%)


 def main():
-    df = pd.read_pickle(BASE + "c6111_data.pkl")
+    df = pd.read_pickle(BASE + "C-6111_data.pkl")
    df = df[df["mode"] == "PROD"].copy().sort_values("dtat").reset_index(drop=True)
    df = df[(df["feed"] > 50) & (df["steam_op"] > 1)]

--- a/scripts/analysis/export_plotdata.py
+++ b/scripts/analysis/export_plotdata.py
@@ -359,8 +359,8 @@ def _nanmid(s):

 def main():
    parser = argparse.ArgumentParser(description="Export plot data as JSON for web dashboard")
-    parser.add_argument("--data", default=os.path.join(BASE, "c6111_data.pkl"))
-    parser.add_argument("--prefix", default="c6111")
+    parser.add_argument("--data", default=os.path.join(BASE, "C-6111_data.pkl"))
+    parser.add_argument("--prefix", default="C-6111")
    parser.add_argument("--output", default=None, help="Output path (default: data/{prefix}_plotdata.json)")
    args = parser.parse_args()

--- a/scripts/analysis/gen_temp_profiles.py
+++ b/scripts/analysis/gen_temp_profiles.py
@@ -35,8 +35,8 @@ def cluster_products(reb):


 def build(prefix, stable_from=None, stable_to=None):
-    pkl = os.path.join(BASE, f"c{prefix}_data.pkl")
-    if prefix == "61" and not os.path.exists(pkl):
+    pkl = os.path.join(BASE, f"{prefix}_data.pkl")
+    if prefix == "C-6111" and not os.path.exists(pkl):
        pkl = os.path.join(BASE, "c6111_data.pkl")
    if not os.path.exists(pkl):
        print(f"  [skip] {prefix}: {pkl} 없음")
@@ -68,14 +68,14 @@ def build(prefix, stable_from=None, stable_to=None):
                       "std": round(float(g["vacuum"].std()), 2)},
            "stages": stages,
        })
-    ref = {"column": f"c{prefix}", "stages_order": STAGES,
+    ref = {"column": prefix, "stages_order": STAGES,
           "n_products": len(products),
           "period": f"{df['dtat'].min():%Y-%m-%d}~{df['dtat'].max():%Y-%m-%d}",
           "products": products}
-    out = os.path.join(BASE, f"c{prefix}_tempref.json")
+    out = os.path.join(BASE, f"{prefix}_tempref.json")
    with open(out, "w") as f:
        json.dump(ref, f, indent=2, ensure_ascii=False)
-    print(f"  c{prefix}: 제품 {len(products)}개  ", end="")
+    print(f"  {prefix}: 제품 {len(products)}개  ", end="")
    for p in products:
        s = p["stages"]
        print(f"[{p['label']} reb{s['reb_temp']['median']:.1f}/Tc{s['T_C']['median']:.1f}/"
@@ -90,7 +90,7 @@ def main():
    ap.add_argument("--from", dest="stable_from", help="안정구간 시작 YYYY-MM-DD")
    ap.add_argument("--to", dest="stable_to", help="안정구간 끝")
    args = ap.parse_args()
-    prefixes = [args.prefix] if args.prefix else ["61", "62", "81", "91", "92", "101", "102"]
+    prefixes = [args.prefix] if args.prefix else ["C-6111", "C-6211", "C-8111", "C-9111", "C-9211", "C-10111", "C-10211"]
    for p in prefixes:
        build(p, args.stable_from, args.stable_to)

--- a/scripts/analysis/run_column.py
+++ b/scripts/analysis/run_column.py
@@ -36,7 +36,7 @@ PY = sys.executable


 def extract(prefix, asset):
-    """추출 + 운전모드 분류. c{prefix}_data.pkl 저장."""
+    """추출 + 운전모드 분류. C-{prefix}11_data.pkl 저장."""
    from c6111_extract import roles_for, tag_frame, classify_phases, clip_to_ranges

    with psycopg.connect(DSN) as conn:
@@ -48,7 +48,8 @@ def extract(prefix, asset):

    df = clip_to_ranges(df, roles)        # 계기 EU range 밖 스파이크 → NaN
    df["mode"] = classify_phases(df)
-    out = os.path.join(BASE, f"c{prefix}_data.pkl")
+    col_key = f"C-{prefix}11"
+    out = os.path.join(BASE, f"{col_key}_data.pkl")
    df.to_pickle(out)

    print(f"\n=== {prefix} ({asset}) ===")
@@ -62,8 +63,9 @@ def extract(prefix, asset):

 def run_analysis(script, prefix):
    """분석 스크립트 1개 실행 (subprocess)."""
-    data = os.path.join(BASE, f"c{prefix}_data.pkl")
-    cmd = [PY, os.path.join(BASE, script), "--data", data, "--prefix", f"c{prefix}"]
+    col_key = f"C-{prefix}11"
+    data = os.path.join(BASE, f"{col_key}_data.pkl")
+    cmd = [PY, os.path.join(BASE, script), "--data", data, "--prefix", col_key]
    print(f"\n>>> {' '.join(cmd)}")
    r = subprocess.run(cmd)
    return r.returncode
@@ -87,11 +89,12 @@ def compare():

    rows = []
    for prefix, asset, label in COLUMNS:
-        pkl = os.path.join(BASE, f"c{prefix}_data.pkl")
-        # 6-1 legacy: c6111_data.pkl (not c61_data.pkl)
-        if prefix == "61" and not os.path.exists(pkl):
+        col_key = f"C-{prefix}11"
+        pkl = os.path.join(BASE, f"{col_key}_data.pkl")
+        # 6-1 legacy: c6111_data.pkl
+        if not os.path.exists(pkl):
            alt = os.path.join(BASE, "c6111_data.pkl")
-            if os.path.exists(alt):
+            if prefix == "61" and os.path.exists(alt):
                pkl = alt
        if not os.path.exists(pkl):
            print(f"  [skip] {label}: {pkl} 없음")