AI cutting-parameter engine · Machinery's Handbook calibrated

Dial in perfect speeds & feeds in seconds, not test cuts.

Enter your material, tool, and operation. Our AI recommends optimal cutting parameters, predicts tool life and surface finish, flags chatter before it happens, and prices every part — backed by real machining science.

7
Material classes
31%
Avg. cycle-time cut
2.4×
Tool-life gain
<1s
To full recipe
Live demo · role-based

Sign in and test it from any seat

The optimizer lives inside a role-based shop workspace. Pick a demo role — Operator, Process Engineer, Quality Manager, or Admin — and see the dashboard and tools tailored to that seat. No setup, no signup.

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CNC Operator
Run the recommended recipe at the machine
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Process Engineer
Full tuning, lobe diagrams & comparisons
Quality Manager
Capability, finish & tolerance focus
Admin
Shop-wide fleet, cost & user overview
Open the demo workspace →
Cutting optimizer

Optimize this setup

Pick your job parameters on the left. The engine runs real machining math — Taylor tool-life, regenerative chatter stability, and cost modeling — and returns a complete cutting recipe.

Set your job parameters and optimize.

Job parameters

Define the cut

63 µin
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Your cutting recipe will appear here

Set your job parameters and hit Optimize parameters.

Recommended recipe
AI confidence
⚡ Cutting speed
🔄 Spindle
RPM
➞ Feed rate
↓ Depth of cut
axial
⏳ Tool life
✓ Surface finish
predicted Ra

📊 Chatter stability — lobe diagram

Limiting axial depth of cut vs. spindle speed for your tool & machine. The shaded zone is stable; your operating point is plotted against it.

⚖ Parameter comparison

Conservative keeps the tool alive longest; aggressive maximizes metal removal but courts chatter and wear. The optimizer's pick balances both.
ConservativeSafeOptimalAI pickAggressiveMax MRR

💰 Cost per part

Machine time plus amortized tooling at the optimal recipe.
per part
Machine time
Tooling (amortized)
Cycle time / part
Material removal rate

Cost model assumes a $95/hr machine rate and a representative 1.2 in³ of stock removed per part. Estimates are derived from Machinery's Handbook reference data and standard cutting-mechanics models — validate on a test part before production.

Capabilities

More than a speeds-and-feeds chart

A physics-aware optimizer that thinks like your best programmer — and never forgets a material.

Optimal speeds & feeds

SFM, RPM, and feed-per-tooth tuned to your exact material, tool geometry, and operation — in both imperial and metric.

Tool-life prediction

Taylor tool-life modeling estimates minutes and parts-per-edge so you can plan tool changes and quote accurately.

📊

Chatter stability lobes

Regenerative-chatter analysis maps stable depth of cut against spindle speed, steering you toward quiet, productive RPMs.

Surface-finish targeting

Tell it the Ra you need; the engine back-solves the feed to hit your finish on the first pass.

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Cost-per-part modeling

Machine time and amortized tooling combine into a live per-part cost so you can quote with confidence.

Strategy comparison

See conservative, optimal, and aggressive recipes side by side and pick the trade-off that fits the job.

Under the hood

From inputs to recipe

Real machining science, wrapped in a one-click workflow.

01 / INPUT

Describe the cut

Material, tool, operation, finish, tolerance, and machine rigidity — the same things you'd tell a setup sheet.

02 / MODEL

Run the physics

Cutting-speed tables, Taylor wear curves, and stability-lobe equations evaluate thousands of parameter combinations.

03 / OPTIMIZE

Balance the goals

The engine trades MRR against tool life, finish, and chatter margin to find the sweet spot for your shop.

04 / DELIVER

Get the recipe

A complete, machine-ready parameter set with predicted outcomes and cost — ready to post to the controller.

Stop guessing at the control panel.

Apprend Technologies brings AI-driven process optimization to machine shops of every size. Cut scrap, extend tool life, and quote faster.

CNC Process Optimizer