What data looks like for this category
Data for this category comes from ERP material master data, melting furnaces, spectrometers, MES heat records, mold management systems, and customer drawing technical requirements. Daily documents include foundry process cards, batching lists, heat records, mold histories, first article inspection records, material test reports, and nonconforming product review forms. Data update frequency is per heat, per batch, or daily. Fields cover alloy composition ratios, melting temperatures, heat numbers, mold cycle numbers, return charge ratios, pouring parameters, and more. Corresponding units include degrees Celsius, percentage, kilograms, and other standard units.
Constraints imposed by these characteristics in the forms and interactions workflow
Data sources are scattered and tied to unique identifiers such as heat numbers and mold cycle numbers. Forms must bind corresponding unique number fields to enable traceability of process data. Update frequency is high and involves real-time process parameters, so forms must support quick data entry or automatic pulling of data from external systems. Fields include professional parameters such as alloy ratios and pouring temperatures. Preset standardized input formats are required to avoid invalid entries. Multiple types of documents must be integrated into bid quotations, so forms must support batch association and reference of multiple fields, while restricting unauthorized modification of historical data.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
formInput | Supports automatic pulling of real-time data from ERP and spectrometers | Adapts to high-frequency data updates per heat, reduces manual entry errors |
userSelect | Presets the 10 most recent historical records for heat numbers and mold cycle numbers | Associates with historical records from mold management systems and MES, enabling quick recall of existing process parameters |
| Input format validation | Restricts temperature fields to the 1200–1700 degrees Celsius range, restricts ratio fields to the 0–100 percentage range | Matches actual parameter ranges for foundry processes, prevents invalid input |
| Form submission validation | Sets validation interval to 300 seconds | Matches the average processing cycle for foundry heats, avoids frequent validation that disrupts operations |
| Field association rules | Binds associated fields for customer drawings and process cards | Integrates all technical documents required for bids, ensures alignment between quotations and technical requirements |
Three Common Mistakes
- Symptom: When a knowledge base is selected and variables are referenced, the interface displays no selectable values. Cause: No knowledge base source corresponding to foundry process data is bound, or no association rules between fields and knowledge bases are configured.
- Symptom: Forms cannot trigger automatic data pulling, and core parameters such as melting temperature are missing after submission. Cause: The data source address for
formInputis not configured correctly, or the trigger condition for automatic pulling is not enabled. - Symptom: After form submission, an invalid parameter prompt appears, and heat records cannot be associated. Cause: No unique validation rule for heat numbers is set, or input parameters exceed the preset reasonable range.
How to Confirm Proper Configuration
- The form editing interface of FastGPT v4.17.0 is accessed, and core input fields related to foundry processes such as alloy composition and melting temperature are verified to be preset.
- Input format validation is triggered, a value outside the foundry process parameter range is entered, and the appearance of a corresponding prompt is confirmed.
- The heat number option from
userSelectis selected, and the retrieval of preset historical process data is confirmed. - Automatic pulling of ERP data via
formInputis tested, and the automatic population of corresponding fields is confirmed.
The values given are common starting points and should be measured against the reader's own samples.