Abstract
This case study reveals how a leading Dongguan contract manufacturer slashed costs through 7 automation modules:
✅ 62% labor reduction
✅ 41% energy savings
✅ 99.2% yield rate
✅ 8-minute mold changeovers
Discover the technical blueprint that drove **EVA midsole unit costs down to 0.85∗∗(vsindustryaverage1.21), providing OEMs with actionable strategies.
Main Content
I. Manual vs Automated Production Comparison
| Process Stage | Pain Points | Automation Solution | Savings |
|---|---|---|---|
| Material Prep | ±3% weighing errors | Loss-in-weight feeders + AI dosing | -18% waste |
| Foam Injection | Technician-dependent | IoT presses (self-adjusting) | -35% defects |
| Curing | 5.7% handling damage | AGVs + ASRS warehouses | -100% loss |
| Trimming | 12% rework rate | Vision-guided waterjet | -91% rework |
Key Metric: Staff per line reduced from 32→12 while daily output increased 40% to 8,500 pairs.
II. Core Automation Specifications
1. Smart Injection System (Siemens PLC)
| Parameter | Conventional | Automated | Benefit |
|---|---|---|---|
| Clamping accuracy | ±10% | ±0.8% | 90% less flash |
| Response time | 120ms | 20ms | 0.5% defect rate |
| Energy monitoring | Manual logs | Real-time alerts | 76% fewer outages |
2. Vertical Curing Towers (Patent ZL202310258XXX)
Space Efficiency: 5-tier → 12-tier shuttle racks (60% smaller footprint)
Process Control:
| Factor | Conventional | Automated |
|---|---|---|
| Temp uniformity | ±5°C | ±0.3°C |
| Humidity control | Manual spray | Microwave (±2%) |
| Cycle time | 6 hours | 4.5 hours |
3. Waterjet Cutting Workcell
Technology:
✓ 300MPa ultra-high pressure (40% less abrasive)
✓ Deep learning contour recognition (0.1s/pair)
Cost Analysis:
| Item | Laser | Waterjet |
|---|---|---|
| Depreciation | ¥1.2/pair | ¥0.35/pair |
| Energy | 18kW/h | 7.5kW/h |
| Mold costs | ¥80k/month | None |
III. Cost Reduction Breakdown (Per Pair)
| Cost Category | Before (¥) | After (¥) | Method |
|---|---|---|---|
| Direct labor | 1.82 | 0.69 | AGVs + robots |
| Electricity | 0.95 | 0.56 | Servo motors |
| Material loss | 0.78 | 0.31 | AI dosing |
| Tooling | 0.43 | 0.05 | Waterjet |
| Quality costs | 1.15 | 0.08 | 99.2% yield |
| Total | 5.13 | 1.69 | 67% savings |
Note: ¥10.32M annual savings at 3M pairs/year; ROI <14 months.
IV. Three-Phase Automation Roadmap
Phase 1: Lean Foundation (1-3 Months)
✓ AGV logistics (¥1.2M)
✓ IoT sensors (¥250k)
✓ Saves ¥1.08M/year (15 fewer handlers)
Phase 2: Critical Automation (4-6 Months)
✓ Smart injection units (¥2.8M/unit)
✓ Vision inspection (¥400k)
✓ Reduces defects ¥2.35M/year
Phase 3: Full Integration (7-12 Months)
✓ Vertical curing (¥3.5M)
✓ MES system (¥1.5M)
✓ Cuts changeovers 45→8min (+40% capacity)
FAQ
Q1: Does automation work for small batches (<5k pairs)?
Modular Solutions:
✓ Quick-change fixtures (5-minute swaps)
✓ Micro-foaming units (800-pair MOQ)
✓ Putian factory runs 150 SKUs efficiently
Q2: Can old machines be retrofitted?
Upgrade Trilogy:
✓ Servo motors (-35% energy)
✓ Siemens S7-1500 PLC (5X faster)
✓ HMI + cloud monitoring
✓ Costs <30% of new equipment
Q3: Does waterjet damage foam structure?
Dual Safeguards:
✓ Adaptive pressure (180-320MPa by density)
✓ Optimized 0.5mm spacing (no tearing)
✓ 100% cell integrity (micro-CT verified)
Q4: Power failure protection?
Triple Backup:
✓ 15-minute UPS runtime
✓ Emergency cooling (<80°C in 2min)
✓ Auto pressure release valves
✓ Zero batches lost during typhoons
Q5: Calculating automation ROI?
Formula:
<TEXT>ROI (months) = Total Investment ÷ [Monthly Savings + Incremental Profit] Where: Monthly Savings = (Old cost - New cost) × Volume Incremental Profit = (New capacity - Old) × Unit margin
Example: ¥6.5M investment → ¥420k savings + ¥280k profits → 9.3-month ROI
WELLE Trade has over 20 years of experience in the production and processing of PE/EVA/TPE foams, so you may want to consult with them if you have any sourcing needs.
