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fazeZEROApplication Atlas

Demo listing. This page uses illustrative seed metadata to demonstrate the Atlas. Claims shown here are not verified product facts.

Formatry

Manufacturing

Demo

A closed-loop press control layer that lets the downstream quality gauge — not a simulation model — write the blank-holder force schedule for every stroke, so forming lines hold first-pass yield through coil, lubrication and tool-wear drift without a re-simulation project.

Design onlyfazeZERO VerifiedProprietary

Last verified 15 Sept 2026 · Updated 23 Sept 2026 · Metadata v1

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Configuration + implementation engagement

Problem

High-volume deep-drawn parts on hydraulic or servo presses with a programmable die cushion — battery cans, fuel-system cups, shock-absorber tubes, transmission housings — where one die runs 200k+ parts a year and an inline gauge or automated CMM already grades every part or every *n*th part.

Outcome

A design-complete foundation in the active pipeline — engineering scaffold planned to complete this month.

Who uses it

  • Operations Analyst
  • Solution Architect

Key capabilities

Capabilities are defined during customer configuration.

Typical workflow

Primary operating flow

Trigger: An operator starts the primary use case

  1. Task

    Stage 1: Capture inputs

    Operator

  2. AI-assisted

    Stage 2: Assist with draft

    System

  3. Human checkpoint

    Stage 3: Human approval

    Approver

Task Automated AI-assisted Human checkpoint Decision

About this foundation

Adaptive process control for forming, sold explicitly against setpoint engineering by simulation. Model predictive control and approximate dynamic programming both need an identified process model, and for nonlinear forming under stochastic friction that model is both the expensive artefact and the perishable one. Formatry deletes the model and replaces it with a scrap-budgeted learning loop closed on measured part quality — which is the one signal the plant already trusts enough to ship against.

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