Test cost

Keywords: test cost,testing

Test cost is the expense of electrically testing each device — including equipment, labor, facilities, and materials, typically $0.10-$2.00 per device, representing 5-20% of total manufacturing cost and a major target for cost reduction efforts.

What Is Test Cost?

- Definition: Total cost to test one device.
- Typical: $0.10-$2.00 per device depending on complexity.
- Components: Equipment, labor, facilities, consumables.
- Impact: 5-20% of total manufacturing cost.

Why Test Cost Matters

- Profitability: Significant portion of manufacturing cost.
- Competitiveness: Lower test cost improves margins or enables lower prices.
- Volume: High-volume products amplify test cost impact.
- Optimization: Major opportunity for cost reduction.

Cost Components

- Equipment: Tester depreciation and maintenance (40-60%).
- Labor: Test operators and engineers (20-30%).
- Facilities: Cleanroom space, utilities (10-20%).
- Consumables: Probe cards, sockets, handlers (5-10%).
- Yield Loss: Cost of overkill and escapes (5-15%).

Calculation

``python
def calculate_test_cost(tester_cost_per_hour, test_time_seconds,
labor_rate, overhead_rate):
# Equipment cost
equipment_cost = (tester_cost_per_hour / 3600) * test_time_seconds

# Labor cost (per device)
labor_cost = (labor_rate / 3600) * test_time_seconds

# Overhead
overhead = (equipment_cost + labor_cost) * overhead_rate

total_cost = equipment_cost + labor_cost + overhead
return total_cost

# Example
cost = calculate_test_cost(
tester_cost_per_hour=500,
test_time_seconds=5,
labor_rate=50,
overhead_rate=0.3
)
print(f"Test cost: ${cost:.3f} per device")
``

Reduction Strategies

- Reduce Test Time: Optimize patterns and parallel testing.
- Increase Utilization: Maximize tester uptime.
- Adaptive Testing: Skip unnecessary tests.
- Automation: Reduce labor content.
- Yield Improvement: Reduce retest and rework.

Trade-offs: Lower test cost must be balanced against quality (coverage) and yield (overkill vs escapes).

Test cost is a major profit lever — optimizing it while maintaining quality is critical for competitive manufacturing economics.

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