Loose Object Control & Incident Intelligence for Vehicle Assembly
🚀 Try it live: https://fod-guard.streamlit.app — no install needed.
Bringing aerospace-grade FOD (Foreign Object Debris/Damage) prevention practice to automotive and EV manufacturing: BM25 similarity search over past loose-object incidents, escape-point analytics, cost-of-escape modeling, and one-click professional incident reports.
Built by a manufacturing & process engineer who led a loose-object control program in high-volume EV assembly that achieved a ~95% reduction in retained loose objects — this tool encodes that program as software.
Loose objects — screws, nuts, washers, push clips, waste tape, wire trimmings, weld/cast slag — retained inside a finished vehicle cause:
- Customer dissatisfaction: rattling noise is directly perceived as poor build quality (the automotive BSR — Buzz, Squeak, Rattle — literature ties squeak/rattle to J.D. Power quality perception)
- Safety risk: a metallic object in the battery enclosure or HV junction area can create a short-circuit path; metallic contamination is a documented trigger for internal short circuits and thermal runaway in lithium-ion systems
- Cost asymmetry: an external object on the carpet takes ~20–30 minutes to find and remove; an internal object found at drive test can take 12+ hours of teardown, retrieval, retest, and reassembly — with paint-scratch risk during disassembly adding another 5–6 hours of repair and bake time
Aerospace formalized this problem decades ago (SAE AS9146, NAS 412, IAQG SCMH 3.4, NASA MSFC-STD-3598). Automotive has BSR testing but no equivalent incident-intelligence tooling. FODGuard fills that gap.
🔎 Similarity search (BM25): describe a new find or a noise symptom ("rattling from rocker panel during weave test") and retrieve the most similar past incidents with confirmed root causes and corrective actions. Okapi BM25 handles the short, jargon-dense incident narratives better than raw TF-IDF.
📊 Escape analytics: source Pareto (which process lines produce the objects), object Pareto, an introduced-vs-detected escape matrix (mass right of the diagonal = expensive late escapes), supplier-attribution tracking, and severity-class cost rollups.
💰 Cost-of-escape model: parameterized from production estimates — technician rate, teardown/reassembly hours, VDT retest cycles, plastic-object search penalty (magnetic pickup doesn't work on plastic), paint repair with bake/dry time. Tune the constants in fod_guard/core.py for your plant.
📝 Incident reports: aerospace-style severity classification (Class A Critical → Class D Contained) and a one-click professional .docx incident report — same document engine family as the companion package pfmea-doc-gen.
📚 Countermeasure playbook: the seven intervention families behind the 95% reduction, encoded as a reusable knowledge base (dedicated line inspectors, return-to-lead accountability, supplier incoming control, senior-tech assignment, 5S/shadow boards/magnetic plates, ergonomic rack redesign, push-clip system redesign).
git clone https://github.com/Fitsumtf/fod-guard.git
cd fod-guard
pip install -e .
streamlit run app.pyOr use the library directly:
from fod_guard.core import load_incidents, BM25Index
df = load_incidents("data/fod_incidents.csv")
index = BM25Index(df)
matches = index.query("clicking noise under driver seat after hard stop")
print(matches[["record_id", "root_cause", "corrective_action"]])data/fod_incidents.csv contains 120 synthetic incidents (no OEM data) generated to match observed production distributions: ~40% from subframe subassembly, ~30% from pre-marriage/marriage, ~20% post-marriage, ~10% other lines; object frequencies led by screws and push clips; ~5% supplier-attributed. Regenerate with python data/generate_dataset.py.
| Class | Definition | Typical cost |
|---|---|---|
| A — Critical | Safety-critical zone (battery enclosure, HV junction) | ~$750+ incl. containment review |
| B — Major | Internal cavity; teardown required | ~$300+ (12+ h worst case) |
| C — Minor | External/visible; quick removal | ~$15 |
| D — Contained | Caught in-station, no escape | ~$4 |
- SAE AS9146, Foreign Object Damage (FOD) Prevention Program — Requirements for Aviation, Space, and Defense Organizations (2017, reaffirmed 2022)
- NAS 412, Foreign Object Damage / Foreign Object Debris (FOD) Prevention, Aerospace Industries Association
- IAQG Supply Chain Management Handbook §3.4, Foreign Object Debris
- NASA MSFC-STD-3598, Foreign Object Damage Prevention
- Gosavi, S.S., Automotive Buzz, Squeak and Rattle (BSR) Detection and Prevention, SAE Technical Paper 2005-26-056
- Robertson & Zaragoza, The Probabilistic Relevance Framework: BM25 and Beyond, Foundations and Trends in IR (2009)
MIT — see LICENSE
Developed by Dr. Fitsum Taye Feyissa — manufacturing & process engineer (Tesla, Thermo Fisher Scientific, IIT Delhi), combining 20+ years of engineering experience with applied data science.