What Data Looks Like for This Category
Data sources for pulp and paper manufacturing scenarios include wood pulp and waste paper batch archives, DCS/QCS control system data, on-machine measurement data, laboratory quality inspection reports, energy and water treatment system logs, plus documents such as stock preparation slips, beating records, paper machine operation logs, and sheet break and grade change records. Data update frequencies cover real-time online measurements, shift summary reports, and complete production archives after each paper roll is finished. Document fields include stock ratio, grammage, moisture content, thickness, equipment number, production batch number, and corresponding measurement timestamps.
Constraints Imposed on Source Citation and Traceability
Scattered data sources and varying update frequencies require precise association of records across different systems during the traceability link. For example, real-time grammage data from online measurements must be bound to the stock preparation slip for the corresponding batch. The nature of high-speed continuous web production requires traceability information to cover the full production cycle of each paper roll, and must not omit records of critical nodes such as sheet breaks and grade changes. Mixed queries across multiple document types require accurate field matching to avoid confusing stock data from different batches. Traceability information must also maintain timeliness to support rapid response for on-site incident handling.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
quoteMaxToken | 3000–5000 token | Matches the total character count of a single roll’s paper machine operation logs and laboratory quality inspection reports, avoids truncating critical traceability information such as batch numbers and equipment IDs |
| Single search limit | Top 8–12 entries | Covers shift-level stock preparation, beating, and quality records, meets the multi-document association needs of incident reports, avoids excessive redundant data |
responseData | Enable full field return | Retains traceability-critical metadata from original documents including batch numbers, measurement times, and equipment numbers |
detail | Enable full citation | Displays page numbers of original documents or timestamps of online records, enabling on-site personnel to quickly verify traceability information |
| Maximum context timeout | 600 seconds | Adapts to query latency for real-time online data, prevents loss of latest production records due to timeout |
This document is written based on the configuration logic of FastGPT v4.17.0.
Three Common Configuration Errors
- Setting
quoteMaxTokento 2000 results in truncated stock preparation slip batch numbers in responses. The full operation logs for a single paper roll often exceed 2000 tokens, and truncation prevents association of critical traceable batch data. - The knowledge base page does not display the source of cited documents. This occurs because full field return for
responseDatais not enabled, and original document number or timestamp fields are not captured. - The number of cited documents in responses exceeds expectations. This happens when the single search limit is set to 2000, which covers redundant records across multiple shifts, and no filtering is applied by production roll number or shift.
How to Verify Correct Configuration
- Submit a query containing keywords from paper machine operation logs, confirm the end of the response lists original document numbers, timestamps, or batch numbers.
- Adjust
quoteMaxTokento 1000 tokens, verify short queries do not display truncation prompts, and long queries are truncated per the configured threshold. - Review the
responseDatatoggle in the knowledge base configuration, confirm return of original document metadata fields is enabled. - Submit a query containing keywords for abnormal sheet breaks, count the number of returned cited documents, and confirm they fall within the expected shift or roll number range.
The values provided are common starting points and should be measured against the reader's own samples.