Machine Vision System Rebuild: Cycle-Time Reduction & Yield Recovery
- Six EV battery module assembly lines running at capacity
- Sub A/B: adhesive dispense + profilometer inspection via overhead vision gantry
- One AutoAssembly cycle = one module; any Sub A/B failure loses one unit
- 6 lines × failure rate = 240 cars/week exposure
Dual Bottleneck Identified
Cycle-Time
Sub A/B CT exceeded line bottleneck, starving downstream
Yield
Components failing inspection reduced available throughput
Gantry Path: Cycle Time Split
Adhesive Dispense + Profilometer = 75% of path time. Inspection travel reducible by 2/3.
Required Outcome
Rebuild the system ground-up: eliminate 100% of starved time, recover 1% yield, integrate all 6 line variants without halting production
Root Cause Analysis: 8 Identified
Ground-up rebuild eliminates these failure modes and enables structured categorization for reaction planning, recovering 1% process yield.
System Integration: 14 Interdependencies
Fixturing Design & Gantry Improvements
Inspection Programming
1. Define Failure Modes and Severities
Critical to Quality of Product
Critical to Yield of Station
2. Develop Inspection Techniques
1. Fundamental Program Architecture, PLC Inputs, Vision Tools, Variable Maintenance
2. Data Collection Logic
3. Data Storage Array Logic
4. Data Conditioning Logic
5. Communication and Storage Logic (PLC and Global)
6. Part Disposition Logic
7. Visualization and SPC Logic
15-Step Script Architecture
System Validation / Process Control / Management Tools
100%
Starved Time Eliminated
240
cars / week
6 lines
+1%
Process Yield
Vehicle Sale Value
$631.4M
12,480 carsets / yr
91%
CT contrib.
9%
Yield contrib.