This document applies to FastGPT v4.17.0.
What the Data for This Category Looks Like
Production ledger data for spraying and coating scenarios covers documents including coating process cards, paint batch lists, paint mixing records, film thickness and color difference reports, oven curves, defect repair orders, VOCs ledgers, and more. Data sources include paint supplier TDS/SDS documents, real-time collected data from spray booths and ovens, colorimeters, film thickness gauges, environmental monitoring equipment, and factory MES systems.
Data update rhythms fall into three categories: update paint-related ledgers when each paint batch is completed, summarize shift production data at the end of each shift, and continuously collect real-time operating parameters for equipment such as spray booths and ovens.
Ledger fields include batch number, viscosity (unit: seconds), film thickness (unit: micrometers), oven temperature (unit: degrees Celsius), VOC concentration (unit: mg/m³), and more. All fields must match standard unit formats for industrial production.
What Constraints Do These Characteristics Impose on HTTP Interfaces and External Systems
The multi-source, multi-rhythm data characteristics of spraying and coating impose multiple constraints on HTTP interfaces. Multi-source data requires interfaces to support pulling device-collected data, MES system data, and supplier document data simultaneously, and be compatible with parsing different data formats. Mixed update rhythms require interfaces to support two invocation modes: scheduled triggering and real-time triggering after a single batch is completed, to adapt to shift summary and per-batch update requirements. The requirement that fields carry specific units requires interfaces to strictly match field names and unit formats, to avoid ledger data errors caused by inconsistent units. Complex data associations require interfaces to support cross-document field matching, such as associating paint batch lists and paint mixing records with corresponding coating process cards.
How to Configure the Settings
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
Authorization | Bearer ${token} | Complies with general security specifications for industrial system APIs |
variables | Map according to standard fields such as coating process cards and paint mixing records | Matches the core data structure of spraying ledgers |
responseData | Return only valid business fields | Reduces redundant data transmission and improves interface efficiency |
| Trigger Frequency | Every 30 minutes or after a single coating batch is completed | Adapts to shift and per-batch update rhythms |
| Retry Count | 3 times | Addresses temporary network fluctuations and device response delays |
| Timeout Duration | 15 seconds | Adapts to the typical response duration of industrial equipment data collection |
Three Common Configuration Errors
- An interface call returns a 404 status code. Cause: The
Authorizationparameter is not configured correctly, resulting in the server rejecting the request. - A red error number appears when referencing the interface within FastGPT. Cause: The
variablesmapping is not configured per standard fields, preventing parsing of the returned ledger data. - An interface call times out. Cause: The configured timeout duration is too short, failing to adapt to the response duration of industrial equipment data collection.
How to Confirm Configuration Is Valid
- Call the test interface and verify that the returned
responseDataincludes core business fields such as coating process cards and paint batch lists. - Verify that the
Authorizationparameter format is correct and passes server authentication checks. - Trigger data pulling after a single coating batch is completed, and confirm that the interface pulls corresponding production data on schedule.
- Simulate temporary network interruption and check whether the interface retry mechanism triggers normally.
The values provided are common starting points and should be evaluated against samples from the target deployment.