As published on the 3DS blog, this article was written by DELMIA Machining expert Dominique Galmel.
DELMIA Machining implements all four pillars of AI‑assisted CAM programming—virtual twins, knowledge platforms, virtual companions, and AI learning—delivering 40–75% programming time reduction through feature recognition, automatic programming from know‑how, and feed & speed optimization.
From AI philosophy to DELMIA implementation
AI in machining means algorithms that learn from machining data to optimize toolpaths, parameters, and help make decisions—choosing better tools, feeds, speeds, and strategies based on experience encoded in data, not just rules.
This aligns directly with the company strategy around 3DUNIV+RSES which is a decision infrastructure.
Virtual twins: Model how machining should behave
Knowledge platforms: Turn tribal knowledge into digital capital
Virtual companions: Structure reasoning with AI; humans arbitrate trade‑offs
Generative experience: embedding AI in the process
DELMIA Machining delivers this infrastructure today across transportation, industrial equipment and aerospace & defense manufacturing. Here’s how:
1. Virtual Twin: Complete NC cell simulation
A machining virtual twin goes beyond static 3D geometry. DELMIA Machining models:
Machine kinematics + constraints (axis limits, spindle dynamics, spindle speeds, accelerations)
Cutting tools + cutting conditions (tool geometry, insert grades feed rates, depths of cut, cutting forces)
Material behavior (workpiece properties, heat generation, surface quality)
Real machining data (vibration, power consumption, cycle deviations)
Key capability: Program and simulate all NC cells end‑to‑end.
Improve machine tending through full work cell simulation
Connect to virtual controllers (NC controller software in the loop for realistic behavior)
Validate before cutting: Collision detection, reachability, cycle time estimation
This creates the “should” behavior foundation that AI builds upon.
2. Knowledge & Know‑How Platform: NC Knowledge Manager
DELMIA’s NC Knowledge Manager captures and operationalizes machining expertise:
What it captures:
Company standards and rules
Tooling and parameter libraries
Cutting strategies and best practices
What it delivers:
Assure standards across teams and plants
Avoid programming mistakes
Reduce training time for new programmers
Minimize knowledge loss when experts retire
This becomes the digital capital that powers AI‑assisted decisions.
3. Generative Tool Path: AI‑Driven Automation
DELMIA Machining’s Generative Tool Path implements core AI‑assisted capabilities available today:
Feature Recognition
Retrieve proven programming from similar parts via:
Automatic feature detection (pockets, contours, holes, bosses)
Part family matching
Constraint‑preserving transfer across machining cells
Result: Programming time slashed for repeat/variant parts without starting from scratch.
Read the full article and "See it in Action":
