Abstract: In industrial ceramics, balancing cost and performance is a core challenge. This article analyzes how to maximize the value of ceramic components through scientific decision-making across four dimensions: process selection, production volume, design complexity, and cost optimization strategies.
Introduction: Cost Drivers in Ceramic Manufacturing
Raw materials account for only 20% of the final cost of industrial ceramic components; the remaining 80% is determined by process route, production volume, and design features. For example, a simple alumina insulation ring produced via dry pressing and post-sintering machining may cost under ¥5 per piece, but if microporous and complex geometries require injection molding, costs can surge tenfold. Jinghui Ceramics’ case database shows that through DFM (Design for Manufacturing) optimization, clients can reduce total cost of ownership (TCO) by an average of 30%.
Process Selection and Cost Correlation
Economics of Major Processes
| Process | Cost per Piece | Min. Economic Batch | Accuracy Limit | Applications |
| Dry Pressing | ¥1–10 | 1,000+ | ±0.1mm | Simple geometries (washers, substrates) |
| Injection Molding | ¥50–300 | 10,000+ | ±0.05mm | Complex internal cavities, threaded structures |
| Isostatic Pressing | ¥20–100 | 500+ | ±0.03mm | Large homogeneous parts (crucibles, tubes) |
| Tape Casting | ¥0.5–5 (per layer) | 50,000+ | ±0.01mm (thickness) | Thin-film circuit substrates |
Hybrid Process Strategies
- Advanced Case: A aerospace sensor ceramic housing required Φ0.5mm±0.005mm inner diameter. if used Injection molding + laser correction: Injection molding for basic structure (¥80/pc), UV laser for micro-holes (additional ¥20/pc), reducing cost by 67% compared to pure CNC machining (¥300/pc).
Impact of Production Volume on Unit Price
Volume Effect Model
According to Jinghui order data, when volume increases from 100 to 10,000 pieces, the unit price decay follows an exponential curve:
- Mold Amortization: The cost of an injection molding die is ¥50,000. When producing 100 parts, the cost per part is ¥500; but when producing 10,000 parts, the cost per part drops to ¥5.
- Energy Optimization: The sintering furnace has a batch capacity of 500 pieces. Energy consumption accounts for 30% of the total cost for small batches, but this decreases to 5% for large batches.
Hybrid Volume Strategy
For R&D phases requiring rapid iteration, Jinghui recommends a two-stage model:
(photo-1 ceramic part )
- Rapid Prototyping: 50 pieces via 3D printing (stereolithography ceramics) at ¥150/pc, 3-day lead time
- Volume Production: Injection molding based on test results, unit cost drops to ¥25/pc
Design Complexity and Cost Control
High-Cost Design Features
- Sharp Angles: Require wire cutting, 200% higher cost than surface grinding
- Holes with Aspect Ratio >5:1: Require special drills with >20% scrap rate
- Asymmetric Wall Thickness: High sintering deformation risk, requiring correction steps
Low-Cost Design Optimization Case
A medical device company’s original ZrO₂ sleeve design included 0.2mm micro-holes (requiring micro-EDM, ¥80/pc). Jinghui proposed a modular assembly: splitting into “base + replaceable guide nozzle”, with dry-pressed base (¥5/pc) and standard micro-hole ceramic tube (¥3/pc), reducing total cost by 90%.
Technical Trade-Offs in Cost Optimization
Material Substitution Economics
| Scenario | Conventional | Optimized | Cost Change | Performance Impact |
| High-Temp Furnace Support | 99% Al₂O₃ (¥50) | 95% Al₂O₃ (¥30) | -40% | Load strength decreases 15%, still meets requirements |
| Semiconductor Wafer Boat | High-Purity AlN (¥800) | SiC-coated Al₂O₃ (¥400) | -50% | Thermal conductivity 180→100 W/m·K, still better than standard Al₂O₃ |
Cost Traps in Post-Processing
- Unnecessary Mirror Polishing: Improving Ra from 0.8μm to 0.1μm increases cost 300% with no practical sealing improvement
- Over-Engineering: Improving flatness from 0.01mm to 0.001mm increases grinding time 10x, only justified for ultra-precision applications like laser gyroscopes
Integrated Decision Framework: Jinghui’s ABCD Model
To help clients quantify decisions, Jinghui developed the ABCD Model:
- A (Application): Define application limits (e.g., temperature, corrosion resistance)
- B (Batch): Select volume strategy based on lifecycle needs
- C (Complexity): Simplify design through feature analysis
- D (Design): Iterate optimization based on DFM principles
Case Study: A new energy vehicle battery insulation project reduced cost from initial quote of ¥45/pc to ¥22/pc while ensuring 10-year service life.
Future Trends: Digitalization and Agile Manufacturing
- Parametric Design Library: Jinghui’s database of 1000+ ceramic components generates optimized solutions based on input parameters
- AI Process Recommendation: Machine learning predicts cost and lead time for different process combinations with >90% accuracy
