Rectangular Pocket Generator

Purpose

Use this generator to standardize the first safe version of a pocketing routine. It helps engineering teams align entry style, roughing logic, and finishing passes before controller-specific optimization. The time saved comes from consistent structure and easier review, not from skipping feed, tool, or holder checks.

Recommended workflow

1. Confirm the actual part target, tool condition, and controller constraints first.
2. Use the tool to build a reviewable baseline, not an unverified production extreme.
3. Compare the output with machine limits, holder clearance, finish targets, and restart logic.
4. After prove-out, tune one variable at a time and store the accepted rule with revision context.

How to interpret the result

This tool is most valuable when it helps the team answer three questions: Is the target clear? Is the process controllable? Can the result be repeated across shifts and machines? Whether the output is a chart, an estimate, or a program skeleton, it should be read together with machine capability, inspection method, tooling condition, and recovery expectations. That is what turns a convenient calculation into a usable production baseline.

Common risks and checks

Pocket routines fail when entry, stock allowance, or corner treatment is disconnected from the actual cutter and setup. Validate cutter engagement, holder clearance, and chip evacuation. If wall quality matters, separate roughing and finishing intent instead of forcing one aggressive path to do both jobs.

When the result disagrees with the shop floor, check units, defaults, controller assumptions, tool condition, and recovery steps before questioning the core math. Teams get the best value when they feed the prove-out result back into setup notes, revision logs, and shift handoff documents.

Visual reference

Related tools

• gcode-viewer
• gcode-reference
• feed-speed-calculator

Final recommendation

Put the tool inside a fixed engineering loop: establish a baseline, validate the first piece, tune one variable at a time, and freeze the accepted rule with context. That approach delivers repeatability instead of one-off numbers.