This document applies to FastGPT v4.17.0.
What this category of data looks like
Data sources for this category include raw material quality certificates, heating furnace systems, press collection data, MES systems, non-destructive testing equipment, and customer forging part drawings. Data updates follow the rhythm of each individual forged part, each batch of workpieces, or each furnace production run. Daily documents include forging process specifications, cutting lists, heating furnace records, forging process cards, mold life records, heat treatment commissioning slips, and ultrasonic testing reports. Core fields include forging batch number, furnace batch number, heating temperature, holding duration, forming pressure, mold usage count, and non-destructive testing result. Corresponding units are batch number, furnace number, degrees Celsius, minutes, megapascals, times, and pass/fail.
What constraints these characteristics impose on HTTP Interfaces and External Systems
Data updates are based on single batches or single furnace runs. High-frequency production data synchronization requires HTTP interfaces to support short-interval calls. This prevents data backlog. Multi-source data docking requires interfaces to support compatible return formats for different external systems. It must adapt to differentiated field structures, such as the furnace batch number field in raw material quality certificates, temperature parameters from heating furnace systems, and testing results from non-destructive testing equipment. Forging production errors have serious consequences. Interfaces must include built-in field validity checks. This stops non-standard units or missing fields from entering the ledger summary process. Batch data synchronization scenarios require support for paginated data pulling. This adapts to batch data transmission for single batches or multiple furnace runs.
How to configure the settings
| Configuration Item | Recommended Practice | Rationale |
|---|---|---|
| Request header configuration | Optionally disable automatic Authorization supplementation, or manually specify a Bearer token | Adapt to scenarios where some industrial systems do not require automatic authentication headers, and address custom authentication requirements |
| Dynamic variable passing | Pass the variables parameter, which includes dynamic tokens, forging batch ranges, etc. | Support calling corresponding data sources by different production batches, adapting to batch ledger summary requirements |
| Response data processing | Extract core fields from responseData, filter out unnecessary metadata | Only retain fields required for the ledger, such as forging batch number and heating temperature, simplifying the summary process |
| Interface timeout setting | 30–60 seconds | Adapt to data return delays from industrial systems such as heating furnaces and presses, avoiding synchronization interruptions |
| Paginated pulling configuration | Configure a single pull limit based on the data volume of a single furnace run | Adapt to scenarios where data volume fluctuates per furnace run, avoiding interface overload |
| Field validation configuration | Enable required field validation, limit unit ranges | Ensure data entering the ledger meets standard field and unit requirements for forging production |
Three common configuration mistakes
- Phenomenon: The interface returns empty data or a 401 Unauthorized status code. Cause: Automatic
Authorizationsupplementation was not disabled, leading to an incorrect authentication header being carried, which was intercepted by the external industrial system. - Phenomenon: Dynamic parameters passed in the workflow do not take effect, and the called data source returns incorrect batch data. Cause: Dynamic parameters were not correctly configured in
variables, leading to parameters not being passed to the external interface. - Phenomenon: Duplicate or missing data appears in the ledger summary. Cause: Reasonable pagination parameters were not configured, leading to too much or too little data being pulled per batch, resulting in duplicates or omissions.
How to verify correct configuration
- Manually trigger an interface call. Check if the returned
responseDataincludes core ledger fields such as forging batch number and heating temperature. - Review workflow logs. Confirm that the
variablesparameter updates dynamically for different production batches, and that external interface parameters are correct. - Simulate a request without a valid authentication header. Verify that the interface returns a 401 status code, confirming that the automatic
Authorizationsupplementation configuration is active. - Review the generated production ledger. Check that extracted field units conform to forging production standards, for example, whether temperature is in degrees Celsius and pressure is in megapascals.
The values provided are common starting points and should be measured against relevant operational samples.