This plan is based on the operation and maintenance configuration guidelines for FastGPT v4.17.0. It applies to the production ledger summary and report generation workflow in photovoltaic module encapsulation scenarios.
What This Category’s Data Looks Like
Photovoltaic module encapsulation production data comes from wafer sorting equipment, glass adhesive film backplane batch systems, factory MES systems, string welding and lamination production equipment, EL defect detectors, and IV power testers. Each module generates one record upon completion. Batch information synchronizes for each raw material batch. Daily production documents include layout drawings, material batch records, lamination process parameter records, EL defect images, IV test reports, insulation withstand voltage test records, and finished product packing lists. Data fields include wafer current gear, lamination temperature and pressure parameters, EL crack coordinates, IV power value, packing batch number, and others. Units include degrees Celsius, pascals, watts, and additional standard units.
What Constraints Do These Characteristics Impose on Database and Operations Maintenance?
High-frequency, massive per-module data updates require databases to support high-concurrency writes and low-latency queries. Delayed ledger updates disrupt subsequent production workflows. Multi-source data access requires operation and maintenance configurations to support data formats from different devices and systems, and unify field mapping rules. Databases must support mixed storage of structured data and unstructured images and documents. Data errors can lead to quality issues such as non-compliant power output and lamination delamination. Databases need complete backup and verification mechanisms to ensure data accuracy. Photovoltaic module encapsulation ledgers link data across multiple workflows. Databases need indexes covering key business fields to improve summary and report generation efficiency.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Concurrency Limit | 80–120 concurrent requests | Adapt to scenarios where multiple string welding and lamination devices report data simultaneously, avoid exceeding concurrency limits of databases or external interfaces |
| Database Connection Pool Size | 150–250 connections | Match high-frequency write concurrency requirements, prevent write failures from exhausted connections |
| Redis Cache Expiration Time | 300 seconds | Cache frequently queried parameters such as wafer gears and lamination processes, reduce repeated query pressure on databases |
| Document Parsing Supported Formats | Add PPT format support | Adapt to import requirements for documents such as layout drawings, match types of daily production documents |
| Database Automatic Backup Cycle | Daily 00:00 full backup | Ensure data can be quickly restored in case of anomalies, avoid disrupting production ledger summary due to data loss |
Three Common Misconfigurations
- Interface returns status code 429 exception. Requests are directly rejected. The cause is no concurrency limit is configured, so concurrent requests exceed the preset upper limit.
- Ledger update delay exceeds 10 seconds. Production data takes too long to write to the database. The cause is database connection pool size is set too low, leading to queued write requests.
- Cannot import PPT format layout drawings. An unsupported file format prompt appears during upload. The cause is PPT format document parsing configuration is not enabled, so production documents in this format cannot be read.
How to Verify Successful Configuration
- Check database connection logs. Confirm current connection count stays within the configured connection pool size range, with no exhausted connection error messages.
- Simulate multiple devices reporting production data simultaneously. Check for 429 exceptions or high latency issues.
- Upload a PPT format layout drawing. Confirm normal parsing and writing of related fields to the database.
- Check automatic backup task execution logs. Confirm daily backup tasks complete automatically per the configured cycle.
The values provided are common starting points, and should be evaluated against the reader's own samples.