#!/usr/bin/env python3
"""Rate a PFMEA with AIAG-VDA Action Priority (AP), legacy RPN, and check the ratings for common errors.
CSV columns: step, function, failure_mode, effect, S, cause, prevention, O, detection, D,
special (CC/SC/blank), action, owner, due
Checks:
FM001 high AP = H without a recommended action (AIAG-VDA: action required or documented justification)
FM002 high severity 9-10 with no prevention or detection control
FM003 high rating missing or outside 1-10
FM004 medium D <= 3 claimed without an error-proofing / automatic detection control (rating inflation)
FM005 medium O <= 2 claimed without a prevention control
FM006 medium severity 9-10 not marked as a special characteristic (CC) - confirm with the customer's rules
FM007 low action without owner or due date
Usage:
python pfmea_ap.py pfmea.csv
python pfmea_ap.py pfmea.csv --sort rpn
python pfmea_ap.py pfmea.csv --csv > pfmea_rated.csv # adds AP and RPN columns
Exit codes: 0 no high findings, 1 high findings, 2 read error.
"""
import argparse
import csv
import re
import sys
# AIAG-VDA FMEA Handbook (2019) action priority, rows by S band and O band; columns D 7-10, 5-6, 2-4, 1
AP_TABLE = {
"9-10": {"8-10": "HHHH", "6-7": "HHHH", "4-5": "HHHM", "2-3": "HMLL", "1": "LLLL"},
"7-8": {"8-10": "HHHH", "6-7": "HHHM", "4-5": "HMMM", "2-3": "MMLL", "1": "LLLL"},
"4-6": {"8-10": "HHMM", "6-7": "MMML", "4-5": "MLLL", "2-3": "LLLL", "1": "LLLL"},
"2-3": {"8-10": "MMLL", "6-7": "LLLL", "4-5": "LLLL", "2-3": "LLLL", "1": "LLLL"},
"1": {"8-10": "LLLL", "6-7": "LLLL", "4-5": "LLLL", "2-3": "LLLL", "1": "LLLL"},
}
ERROR_PROOF = re.compile(r"poka|error[- ]?proof|mistake[- ]?proof|sensor|interlock|automatic|automated|vision|in-?line gauge|100%.*(auto|machine)|go/?no-?go fixture|presence detect", re.I)
def band(v, cuts):
for label, lo, hi in cuts:
if lo <= v <= hi:
return label
raise ValueError(v)
def action_priority(s, o, d):
sb = band(s, [("9-10", 9, 10), ("7-8", 7, 8), ("4-6", 4, 6), ("2-3", 2, 3), ("1", 1, 1)])
ob = band(o, [("8-10", 8, 10), ("6-7", 6, 7), ("4-5", 4, 5), ("2-3", 2, 3), ("1", 1, 1)])
col = 0 if d >= 7 else 1 if d >= 5 else 2 if d >= 2 else 3
return AP_TABLE[sb][ob][col]
def rating(v):
try:
n = int(str(v).strip())
return n if 1 <= n <= 10 else None
except ValueError:
return None
def main():
ap = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
ap.add_argument("csv", help="PFMEA CSV, or - for stdin")
ap.add_argument("--sort", choices=["ap", "rpn", "row"], default="ap")
ap.add_argument("--csv", dest="as_csv", action="store_true", help="print the PFMEA with AP and RPN columns")
a = ap.parse_args()
try:
fh = sys.stdin if a.csv == "-" else open(a.csv, newline="", encoding="utf-8-sig")
with fh:
rows = list(csv.DictReader(fh))
except (OSError, csv.Error) as e:
print(f"error: {e}", file=sys.stderr)
return 2
if not rows or not {"failure_mode", "S", "O", "D"} <= set(rows[0]):
print("error: PFMEA CSV needs failure_mode, S, O and D columns", file=sys.stderr)
return 2
findings, rated = [], []
for i, r in enumerate(rows, 1):
g = lambda k: (r.get(k) or "").strip()
s, o, d = rating(r["S"]), rating(r["O"]), rating(r["D"])
label = f"row {i} {g('step')} / {g('failure_mode')} / {g('cause')}".replace(" / /", " /")
if None in (s, o, d):
findings.append(("FM003", "high", label, f"S/O/D must be 1-10 (got {r['S']}/{r['O']}/{r['D']})"))
continue
prio = action_priority(s, o, d)
rpn = s * o * d
rated.append((i, r, s, o, d, prio, rpn))
if prio == "H" and not g("action"):
findings.append(("FM001", "high", label, f"AP H (S{s} O{o} D{d}) needs an action or a documented justification"))
if s >= 9 and not (g("prevention") or g("detection")):
findings.append(("FM002", "high", label, f"severity {s} with no prevention or detection control"))
if d <= 3 and not ERROR_PROOF.search(g("detection")):
findings.append(("FM004", "medium", label, f"D{d} claimed for '{g('detection') or 'no control'}': D 1-3 needs error-proofing or automatic detection"))
if o <= 2 and not g("prevention"):
findings.append(("FM005", "medium", label, f"O{o} claimed with no prevention control"))
if s >= 9 and g("special").upper() not in ("CC", "SC", "KC", "CRITICAL"):
findings.append(("FM006", "medium", label, f"severity {s}: mark as special characteristic (CC) if the customer's rules require"))
if g("action") and not (g("owner") and g("due")):
findings.append(("FM007", "low", label, "action without owner or due date"))
order = {"H": 0, "M": 1, "L": 2}
if a.sort == "ap":
rated.sort(key=lambda x: (order[x[5]], -x[2], -x[6]))
elif a.sort == "rpn":
rated.sort(key=lambda x: -x[6])
if a.as_csv:
w = csv.writer(sys.stdout, lineterminator="\n")
cols = list(rows[0].keys())
w.writerow(cols + ["AP", "RPN"])
for _, r, *_rest, prio, rpn in rated:
w.writerow([r.get(c, "") for c in cols] + [prio, rpn])
else:
print(f"{'AP':<3}{'S':>3}{'O':>3}{'D':>3}{'RPN':>5} {'Step':<14}{'Failure mode':<28}Cause")
for i, r, s, o, d, prio, rpn in rated:
print(f"{prio:<3}{s:>3}{o:>3}{d:>3}{rpn:>5} {(r.get('step') or '')[:13]:<14}{(r.get('failure_mode') or '')[:27]:<28}{(r.get('cause') or '')[:40]}")
counts = {k: sum(x[5] == k for x in rated) for k in "HML"}
print(f"\nAction priority: H {counts['H']}, M {counts['M']}, L {counts['L']} ({len(rated)} rated rows)\n")
sev = {"high": 0, "medium": 1, "low": 2}
for code, s_, label, msg in sorted(findings, key=lambda f: sev[f[1]]):
print(f"{code} [{s_}] {label}: {msg}", file=sys.stderr if a.as_csv else sys.stdout)
return 1 if any(f[1] == "high" for f in findings) else 0
if __name__ == "__main__":
sys.exit(main())
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