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In forging process, targeted optimization needs to be adjusted according to specific materials, product shapes, performance requirements, and production conditions. The following are optimization strategies for different forging scenarios:
1. Optimization for different materials
(1) Carbon steel&alloy steel forging
Optimization objective: Improve strength, reduce cracks, refine grain size
Key measures:
Preheating control: Adopting a stepped heating method (such as first low-temperature stress relief and then raising to forging temperature).
Final forging temperature control: Avoid temperatures below the recrystallization temperature (such as carbon steel final forging temperature ≥ 800 ° C) to prevent cold work hardening.
Post forging heat treatment: Adopting normalizing or quenching and tempering treatment (quenching+tempering) to improve the comprehensive mechanical properties.
(2) Aluminum alloy forging
Optimization objective: prevent overheating, improve fluidity, and reduce oxidation
Key measures:
Low temperature forging: The forging temperature of aluminum alloy is generally between 350-500 ° C to avoid high-temperature grain growth.
Rapid forging: using high-speed hammers or mechanical presses to reduce the residence time of the billet in the mold.
Inert gas protection: Nitrogen or argon gas is introduced into the heating furnace to reduce the formation of oxide scale.
(3) Titanium alloy forging
Optimization objective: To avoid embrittlement of alpha phase and improve uniformity
Key measures:
Isothermal forging: The mold and billet are at the same temperature (900-1000 ° C) to reduce deformation resistance.
Beta forging: Forging in the beta phase region (>1000 ° C) to improve plasticity, but strict control of cooling rate is required.
Superplastic forging: Forging at a specific temperature strain rate, suitable for complex thin-walled parts.
2. Optimization for different forging methods
(1) Open Die Forging
Optimization objective: Improve material utilization and reduce machining allowance
Key measures:
Multi directional forging: using alternating upsetting and elongation to improve the uniformity of the structure.
Near net forming: combined with CNC operation machine, reducing subsequent machining volume.
(2) Closed Die Forging
Optimization objective: Improve mold life and reduce burrs
Key measures:
Pre forging+final forging: phased forming, reducing single deformation and improving dimensional accuracy.
Mold lubrication: Use graphite based or glass lubricants to reduce friction and mold wear.
Mold cooling: internal water cooling or spray cooling is used to prevent the mold from overheating and deformation.
(3) Precision Forging
Optimization objective: Reduce subsequent processing and improve surface quality
Key measures:
Warm forging/cold forging: Forging at lower temperatures (such as 600-800 ° C) to improve dimensional accuracy.
Elastic mold design: adopting elastic compensation structure to reduce the impact of rebound.
3. Optimization for different defects
Analysis of common defect causes and optimization measures
Improper flow of metal during folding (Lap), with surface metal pressed into the interior to optimize the pre forged shape and increase rounded transitions
Crack temperature too low, deformation rate too fast, increase forging temperature, reduce deformation rate
Control the final forging temperature if the grain size is too large or the cooling is too slow, and quickly cool after forging (air cooling/water mist cooling)
High precision molds are used to optimize heating uniformity due to size deviation, mold wear, or uneven temperature
4. Digitization and intelligent optimization
(1) Numerical simulation (FEM simulation)
Simulate metal flow, temperature field, stress distribution, and optimize process parameters using software such as Deform and QForm.
Case: Simulating the gear forging process, predicting folding risks, and adjusting mold design.
(2) Intelligent monitoring
Intelligent temperature control: infrared temperature measurement+AI dynamic adjustment of heating parameters.
Pressure adaptive: Real time monitoring of forging pressure to prevent overload or underload.
5. Optimization of typical cases
Case 1: Forging of Automotive Connecting Rod
Problem: Traditional forging requires a large amount of machining, resulting in high costs.
Optimization plan:
Adopting quasi dense forging to reduce excess.
After forging, residual heat quenching eliminates the need for secondary heating.
Case 2: Forging of Aircraft Engine Blades
Problem: Titanium alloy has high deformation resistance and is prone to cracking.
Optimization plan:
Isothermal forging (heating the mold to 950 ° C).
Adopting superplasticity forming to improve dimensional accuracy.
Summary
The targeted optimization of forging technology requires a combination of material characteristics, forging methods, defect control, digital technology, and other factors. The core optimization directions include:
Material adaptation (temperature, deformation rate).
Process improvement (multi-directional forging, quasi dense forming).
Defect prevention (simulation, intelligent monitoring).
Cost control (near net forming, waste heat utilization).
Through system optimization, the quality of forgings can be significantly improved, the scrap rate can be reduced, and production efficiency can be enhanced.
