📊 Barashi Defect Dashboard

Toyota ASSB · Jan–Jul 2026 · 0 defects · Source: ATS Inspect Advanced Reports
BotBot analysis · 2026-07-09
TAGG/T-A (Production self-declared)
QG/IR-QG (Quality Gate)
HANE (Offline repair)

📊 Detection Family Distribution

📊 Detailed Concern (Top 12)

📊 Top Parts (Pareto)

📊 Top Locations

📊 Defects by Model

📊 Top Recorders

📊 Family vs Concern Stacked

📊 Model × Family (Cross-tab)

📊 Part × Family (Top 25)

📊 Top 20 Parts (Full Pareto)

📊 Top 20 Part × Location

📊 Model × Top 5 Parts

📊 Defects per Model

📊 HANE Rate by Model (Offline Repair %)

📊 Per-Model Top Parts

📊 Monthly Defect Trend

📊 Monthly Family Split

Prod DateShiftModelBody NoPart LocationConcernFamilyResp Area Rec StnRecorded By

📋 Recommended Action Plan

🔴 Priority 0 — Side Skirt Gap Issue

Root cause + countermeasure for Side Skirt (705 defects, 54% of total)

Surfaces in TAGG (438, production self-catches) + QG (267, gate catches) + HANE (31, leaks to offline repair). Single biggest issue across the value stream.
Steps:
  • Pull all 705 Side Skirt records → cluster by station, shift, supplier lot
  • 3-day side-by-side between production + QG inspectors on VIOS line
  • Check supplier dimensional reports for top 3 Side Skirt suppliers
  • Review jig calibration records per QP-QCD-008
Impact: ~705 defects / 6 months · Effort: 2-3 weeks
🟠 Priority 1 — VIOS Offline-Repair Investigation

Why is VIOS HANE rate 14.6% vs COROLLA 8.2% vs YARIS 4.2%?

VIOS contributes 113 of 148 HANE defects (76%). Likely Side Skirt issue compounding. Need to understand why VIOS-specific mounting process differs.
Steps:
  • Compare VIOS mounting process with COROLLA — what's different?
  • Check operator training records for VIOS-specific training
  • Audit body dimensional variation between VIOS/COROLLA mounting points
Impact: ~113 defects / 6 months · Effort: 2 weeks
🟠 Priority 1 — Fix Barashi Data Form

47% of records have Nil or _OTHER for Part/Location

450 records (34.4%) have Location="Nil" + 168 records (12.8%) have Part="_OTHER". Cannot trend or root-cause these. Data-quality blocker for future analysis.
Steps:
  • Update ATS Inspect form: make Part + Location mandatory dropdowns (Fr/Rr/Lh/Rh/Ctr)
  • Add validation to prevent "Nil" without a reason field
  • Re-train 3 active recorders (Fitry Abdillah, Mohd Tarmizi, Lokman Musa)
Impact: Better trend data, blocks future analysis · Effort: 1 week
🟡 Priority 2 — Cross-Shift Gap Consistency

3-shift variation on Side Skirt installation

Need to verify if gap defects are concentrated in one shift (N/D/E) and which shift has the highest TAGG rate vs QG rate.
Steps:
  • Group Side Skirt records by shift → identify shift-level patterns
  • Compare jig handover protocols between shifts
  • Consider rotating operators if pattern persists
Impact: All Side Skirt defects · Effort: 1 week
🟡 Priority 2 — Recalibrate Barashi Recording SOP

Standardize how defects are classified

3 active recorders logging 1,308 records but classification appears inconsistent (Nil/_OTHER issue, parts vs locations mixed).
Steps:
  • Update IR for barashi recording (likely IR/26 area)
  • Add examples + decision tree for each Part/Location/Concern combination
  • Quarterly cross-check between recorders
Impact: Cleaner future data · Effort: 3 days