Improving Asset Naming in CLO3D

Improved a repetitive naming workflow through automation, testing and user feedback, demonstrated publicly with dummy information.

Improving Asset Naming in CLO3D

Professional workflow-improvement case

This project improved a repetitive naming process used when preparing textile CAD models in CLO3D. The goal was to reduce manual work while keeping pattern-piece names consistent with the required convention.

The challenge

For products containing many pattern pieces, manual renaming created repetitive work and could take several hours.

The process was repetitive, time-consuming and easy to perform inconsistently.

My contribution

I initiated the improvement after identifying the repetitive work and defined how the naming process should change.

My contribution included:

  • Identifying which information the automation needed
  • Defining the required workflow and expected naming result
  • Requesting additional API functionality when the available data was insufficient
  • Coordinating support for implementation and code review
  • Testing the final solution in CLO3D
  • Collecting user feedback and defining further improvements

The solution

Users prepare the required category information, such as fabric No., before running the automation. Pattern pieces that share the same category can be selected and updated together.

The automation then generates the pattern-piece names according to the defined structure, replacing repeated manual naming actions.

Outcome

The automation replaced repeated manual renaming and conservatively saved at least 5% of the total CLO3D model-creation time.

The solution was released for professional use and made available to at least ten users. Feedback after release also led to an additional completion notification so users could see when the process had finished.

Script Demo

The demonstration shown in this portfolio uses dummy information and a modified workflow.

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This project demonstrates

  • Workflow analysis and improvement
  • Translating user needs into technical requirements
  • Testing and validation
  • Collaboration with technical contributors
  • Incorporating feedback after release
  • Taking an improvement from an observed need to daily use

Limitations

The automation focuses on pattern-piece naming rather than the complete CLO3D workflow. Users must still provide the required category information manually.