What data for this use case looks like
Data sources for petroleum refining scenarios include DCS/APC, LIMS, tank farm metering systems, crude oil evaluation systems, equipment management systems, and energy systems. Daily business documents cover operating procedures, production plans, material balance reports, distillate export quality reports, interlock ledgers, shift handover records, and change management documents. Data updates occur in real time, per shift, and daily. It includes multi-dimensional information from production operation, process, scheduling, equipment, and laboratory departments. Fields include crude oil density, unit load, fraction temperature, material flow rate, and other metrics. Some fields must use industry-standard units.
What constraints these characteristics impose on forms and interactions
Multi-source heterogeneous data sources require forms to pull data across systems, reducing manual entry errors. Fields with different update frequencies need real-time validation and scheduled synchronization logic, to ensure data in bid documents matches current production status. The coupled multi-unit business characteristic requires forms to support associated field linkage, such as synchronizing load configurations for multiple units when crude oil properties change. Strict potential error consequences require forms to have strong validation mechanisms, to block abnormal data from entering final documents.
How to Configure
| Configuration Item | Recommended Practice | Rationale |
|---|---|---|
formInput | Bind multi-source field mapping, support real-time pulling of DCS/APC and LIMS data | Petroleum refining data updates in real time, requiring the latest process parameters to be synchronized to bid documents |
userSelect | Pre-set 10-15 common crude oil type options, link to quality indicators from the associated crude oil evaluation system | Crude oil properties fluctuate widely, requiring rapid matching of corresponding quotations and process parameters |
| Form field validation rules | Set legal ranges for density, flow rate, temperature and other fields, based on actual on-site calibration | Prevent abnormal data from entering bid documents and reduce subsequent production risks |
| Form block configuration | Split into three modules: unit, material, quality, with 800–1200 characters per block | Bid documents have large content volume, and block division improves filling and review efficiency |
| Form timeout setting | 600 seconds | Multi-unit data pulling takes a long time, needing to match the pace of data updates |
| Cross-platform API configuration | Enable cross-domain permissions for formInput, synchronize field mapping to external interfaces | Support embedding forms into third-party bid collaboration platforms |
Three Common Misconfiguration Issues
- After calling form configurations via the FastGPT API, third-party platforms cannot load form fields. Cause: Cross-domain permissions for
formInputare not correctly configured, and multi-source data mapping fields are not synchronized to external API interfaces. - An error indicating some fields are empty appears after form submission. Cause: Real-time pulled DCS data null values are not validated, and missing shift handover record fields updated per shift are not handled.
- Corresponding quality indicators do not load automatically after selecting a crude oil type. Cause: The linkage logic of
userSelectonly configures static options, and no data source from the crude oil evaluation system is associated.
How to Verify Proper Configuration
- Call the form API interface of FastGPT v4.17.0, check if the returned field list includes all configured multi-source data fields.
- Simulate selecting different crude oil types, confirm if the quality indicators linked to
userSelectupdate automatically. - Input parameters outside the legal range, check if the form displays validation prompts.
- Wait 600 seconds before submitting the test form, confirm if data pulling and submission can be completed normally.
The values provided here are common starting points and should be measured against the reader's own samples.