Inspection and Process Record Audit for Garment Cutting and Sewing: Workflow Orchestration

- Client industry: Garment cutting and sewing

About This Page

  • Client industry: Garment cutting and sewing
  • Business direction: Inspection and process record audit
  • Capability area: Workflow orchestration

What the data for this category looks like

Core data for this category comes from orders and size charts, CAD patterns, fabric and accessory inspection records, workshop hanging systems, needle detector test data, and customer sealed samples. Daily produced documents include process sheets, layout plans, cutting lists, first-piece sealed sample records, process quality tables, and packaging size matching lists. Data updates follow per-order, per-style, per-batch cycles. Most fields relate to specific sizes, fabric dye lots, cut piece matching quantities, and process quality inspection results. No unified, standardized cross-batch field format exists.

Constraints imposed by these characteristics on workflow orchestration

This category has many styles, strong seasonality, and cut pieces are irreversible. Workflow orchestration must adapt to frequent document updates and temporary adjustments. Process sheets and layout plans for different orders have large field differences. Dynamic field extraction for different document structures must be supported. Real-time data from hanging systems and needle detectors must be integrated into the workflow. Configuration options must support synchronization across multiple data sources. Process quality inspection results must be associated with corresponding cut pieces and batches. The workflow must retain relational data for traceability to avoid cross-batch data confusion.

How to set configurations

Config ItemRecommended SettingRationale
Global variable configurationEnable the variables module, add a Number type counter with an initial value of 0Used to count the number of non-conforming processes per order, meeting business counting requirements
Node ID settingConfigure a unique nodeId for each quality inspection nodeFacilitates association of process records with corresponding cut piece batches to enable data traceability
Text extraction limitSet to the first 5 entriesAdapts to the number of fields extracted from process sheets and layout plans, avoiding redundant data
Context lengthSet to 800–1200 charactersAdapts to the single-page document length of process sheets and layout plans, avoiding truncation of key fields
Timeout thresholdSet to 600 secondsAdapts to time-consuming scenarios for multi-data source synchronization, avoiding process interruptions
Debug modeEnable full-process debuggingUsed to troubleshoot exceptions in workflow node operation, aligning with the debugging logic of FastGPT v4.17.0

Three common configuration mistakes

  • Code run node not visible during debugging: The debug panel in the workflow orchestration interface does not display the code run node option. After FastGPT v4.17.0, the "Advanced Node Visibility" option must be enabled in global settings. If this option is not enabled, the node is hidden.
  • Text extraction node model selection unavailable: The model dropdown menu for the text extraction node is empty or unselectable. This occurs because the tool call permission for the corresponding model is not enabled in global configuration, or the workflow is not bound to the model call plugin.
  • Global counter fails to update automatically: The Number type counter value does not increase after an AI response. This happens because the variable update plugin is not correctly bound to the counter variable in the variables module, or the trigger timing is set before the AI response, so the AI output result is not retrieved.

How to confirm a correct configuration

  • A test process sheet is uploaded, and the workflow is checked for automatic triggering of the text extraction node and return of corresponding fields.
  • After the workflow runs, the global variables counter value is checked for updates as non-conforming quality inspection results increase.
  • Each quality inspection node’s nodeId is verified to be unique, ensuring accurate traceability of process records.
  • Debug mode is enabled to run the full workflow, and the output logs of each node are checked for errors and complete data.

The values provided here are common starting points and should be evaluated against the applicable samples.