What the Data for This Category Looks Like
Data related to pulp and paper equipment inspection and maintenance comes from wood pulp and waste paper batches, DCS/QCS systems, on-paper machine measurement equipment, laboratories, energy and water treatment systems. Daily documents include stock preparation sheets, beating records, paper machine operation records, online quality curves, laboratory reports, sheet break and grade change records. Fields cover stock ratio, beating degree, paper machine speed, grammage, moisture content, sheet break duration, and more. Update frequencies include three types: real-time, shift-based, and per roll.
Constraints on Forms and Interactions
Multi-source data with varying update frequencies requires forms to support fields linked to real-time, shift-based, and per-roll data, and display them grouped by update frequency to avoid information confusion. Multiple specialized documents require forms to configure input items in blocks according to business processes such as stock preparation, beating, and paper machine operation, to reduce entry complexity. The characteristics of high-speed continuous web production require forms to adapt to units and value ranges of specialized parameters such as web width and speed, while supporting quick entry of high-frequency inspection items to match real-time production rhythms.
Configuration Settings
These configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
formInput | Configure input items in four business blocks: stock preparation, beating, paper machine operation, and maintenance | Pulp and paper equipment inspection and maintenance involve multiple types of specialized documents; grouping reduces entry complexity |
userSelect | Preset high-frequency scenario options such as sheet break causes, beating degree adjustments, and stock preparation parameter adjustments | High-frequency scenarios reduce manual input time and match real-time production rhythms |
formInput | Add dedicated field validation rules for each block | Pulp and paper equipment parameters have clear industry value ranges; validation reduces entry errors |
| Block length | 800–1200 characters | A single block must cover input items for a complete business process, avoiding cross-block operations that interrupt workflows |
| Single search limit | Top 3 results | Production scenarios require quick access to accurate maintenance solutions; too many results increase decision-making costs |
| Maximum context | Interaction records within 600 seconds | Pulp production processes are continuous; context must cover shift-level operations and abnormal records |
Three Common Misconfigurations
- Phenomenon: The splitting logic extracted from question-answer pairs does not match the structure of business documents. Cause: Documents such as stock preparation sheets and sheet break records are not split first, and QA splitting guidance terms are applied directly.
- Phenomenon: An empty error occurs when global variables are passed between nodes. Cause: The variable scope and trigger timing are not configured correctly, resulting in the variable not being loaded properly.
- Phenomenon: No thought process is returned after selecting the qwen-plus model and enabling output thinking. Cause: The corresponding output switch is not correctly checked in the model configuration.
How to Verify Correct Configuration
- Enter test data for a stock preparation sheet, check if the
formInputblocks display corresponding fields grouped by business processes such as stock preparation and beating. - Trigger equipment inspection Q&A, check if the
userSelectpreset high-frequency scenario options include pulp and paper-specific scenarios such as sheet break and beating adjustment. - Submit a test request, confirm that the number of returned results does not exceed the set single search limit.
- View the global variable transfer log, confirm that there are no empty input errors when variables are passed between nodes.
The values provided are common starting points and should be measured against the reader's own samples.