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Specialty materials management

Flows provides advanced workflow management for specialty alloys and metal powders.

database system
Comprehensive Material Genealogy Visualization & Reporting.

End to End Workflow for all Orders

  • Simple visualization of all actions/events and materials history

  • Automatically track utilization history by material batches

    • Number of uses, amount used, data of first use, user actions

  • Auto-create feature to automatically create runs when line item is set to confirmed

> Get in touch if you would like to find out more!

Intelligent Materials

  • ​Define workflows, work instructions and suppliers

  • Create customized material handling & process steps with Work Instructions

    • New powder shipments

    • Post-processing steps

  • Easily check output for location or workstation to get insights on atomized/sieved/classified materials in each batch.

  • Track real-time material status, utilization, and quantity remaining 

    • Virgin and reused powder cycles

    • List all orders completed with material

Intelligent Powder Management
Simplifying Material Handling on the Production Floor

Using Flows on the Shop Floor

  • Every shop floor user has an account and a device with Kiosk Mode to log in

  • Traveler QR codes are used to walk through work instructions and input reports can be generated

  • Ability to load and unload material from machine using Web & QR app

  • Track history of material actions (split, blend, sieve, test) 

Quality Assurance & Traceability Reports

  • Automatically track material availability across inventories and in-machine

  • Track real-time material status, utilization, and quantity remaining 

    • Virgin and reused powder cycles

    • List all builds/orders completed with material

  • Automatic material Traceability Report generation

  • Show material history & QA data

  • Ability to attach reports

Comprehensive Material Genealogy Visualization & Reporting

Our Goals with the REPMaM Project

Develop a continuous atomization method for critical alloys and ensure stability of powder properties.

Apply machine learning to identify key performance indicators and establish smart atomization rules.

Validate the smart atomization process through trials for both powder production and additive manufacturing.

3d printed shoe

This project has received funding from the Innovate UK research and innovation programme under agreement No 10079014.

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