What this category of data looks like
The quality traceability data for foundry (sand molding, precision casting, die casting) covers multiple types of business documents and system-collected content. Document types include foundry process cards, batching lists, heat records, mold history records, first article inspection records, material test reports, and nonconforming product review forms. System data sources include ERP material master data, melting furnace thermometers, spectrometers, MES heat records, mold management systems, customer drawings, and technical specifications. Data is updated per heat, per batch, or daily. Core fields include heat number, mold times, alloy composition, pouring temperature, and defect type. Corresponding units include ℃, ppm, batch numbers, and similar identifiers.
What constraints these characteristics impose on HTTP interfaces and external systems
This category has scattered data sources and high update frequency. HTTP interfaces must support different data formats from multiple systems, while handling high-frequency requests. The fixed units and business binding relationships of core fields require interface parameters to precisely match identification fields such as heat number and mold times. This prevents overly large or invalid query scopes. Each heat’s data requires associated verification. Interfaces must carry clear business identifiers as query conditions, and support retry mechanisms after failures to handle temporary system interaction exceptions. Defect analysis results are directly linked to scrap or claim risks. Interface returned data must undergo strict accuracy checks to avoid incorrect data entering subsequent analysis workflows.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Authorization Authentication | Configure the Authorization request header as a Bearer token | Complies with interface security specifications for external industrial systems |
| Request Timeout | 300 seconds | Adapts to the actual latency window for data return from equipment such as melting furnaces and spectrometers |
| Response Data Parsing | Parse responseData in JSON format | Matches the structured storage format of foundry business data |
| Variable Binding Rule | Bind variables parameters by heat number and mold times | Enables precise association between defect analysis and corresponding production batches |
| Return Data Volume Limit | No more than 50 items returned per request | Adapts to the volume of business data for a single heat, avoiding excessive interface load |
| Retry Strategy | 2 retries after failure, with a 10-second interval | Addresses temporary network fluctuations or brief stalls in external systems |
Three common misconfigurations
- Interface returns empty fields, unable to match process data for the target heat. Cause: No heat number is specified as a query condition in the request parameters, leading the external system to return full invalid data.
- Call timeout triggers 504 status code errors. Cause: The request timeout setting is too short, and does not match the actual latency window for melting furnace data collection.
- No unit conversion for alloy composition is performed. Cause: The ppm unit returned by the spectrometer is not adapted to the percentage unit required by the business, leading to incorrect component judgments in defect analysis. This creates a risk of full-heat scrap.
How to confirm successful configuration
- Initiate an interface request with a specified heat number, check if the returned data includes core business fields such as batching list and melting temperature for the corresponding heat.
- Simulate a network latency scenario, verify that the interface completes response and returns valid data within 300 seconds.
- Check the
Authorizationheader configuration, initiate an unauthorized request, confirm that a 401 status code is returned. - View the FastGPT v4.17.0 system log, confirm that the
variablesparameter has been correctly bound to business identification fields such as heat number and mold times.
The values provided are common starting points, and should be evaluated against the reader's own samples.