What the data for this category looks like
Data for this category comes primarily from material grade ledgers, customer technical requirement documents, real-time data collected by temperature control instruments, furnace temperature uniformity test reports, test results from hardness testers and metallographic equipment, and workshop MES systems. Data is updated per furnace load and per batch. Daily documents include heat treatment process cards, furnace loading layout diagrams, time-temperature furnace curve charts, hardness and metallographic analysis reports, equipment inspection records, and exception handling forms. Core fields include furnace number, heating temperature, holding duration, cooling rate, Rockwell hardness value, and metallographic structure type. Units include degrees Celsius, hours, Rockwell hardness grades, and other relevant units.
What constraints these characteristics impose on the database and operations maintenance link
The high-frequency update rhythm for each furnace load and batch requires the database to support high-concurrency writes and low-latency queries. The mixed storage requirement for multiple document types requires the database to adapt to both structured ledger data and unstructured large-field data such as furnace temperature curves and metallographic images. The precise temperature, duration, and hardness parameters require the database’s numerical precision configuration to match the output precision of testing equipment. Multi-source cross-system data access requires the database to support synchronization verification and format unification for multi-source data. The full-link traceability requirement for defect analysis requires the data to retain a complete generation and modification chain, and must not be overwritten or deleted arbitrarily.
How to set the configuration
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | mongodb://admin:heatpass@db-host:27017/ht_quality?replicaSet=rs-heat | Adapts to storage of unstructured large-field data such as furnace temperature curves and metallographic images, and supports high-concurrency writes |
PG_URL | postgresql://admin:heatpass@db-host:5432/ht_台账?sslmode=require | Stores structured ledger data such as process cards, exception handling forms, and customer technical requirements |
DB_MAX_LINK | 100–150 | Matches the concurrent demand of high-frequency writes per furnace load, and prevents database connection exhaustion |
REDIS_URL | redis://:redispass@cache-host:6379/0 | Caches frequently queried furnace temperature curves and hardness test results to reduce load on the primary database |
| Database connection timeout threshold | 30 seconds | Adapts to workshop network fluctuation scenarios, and prevents long-term blocking of requests |
Three Common Mistakes
- Concurrent requests exceeding the threshold result in a 429 status code and significantly increased request latency. Cause: No database connection upper limit or concurrency limiting rules are configured, leading to database connection exhaustion and failure for new requests to establish connections.
- Database connection workflows return empty result sets after execution. Cause: Field naming rules for heat treatment scenarios are not followed. For example, miswriting "furnace number" as "furnace_id" causes SQL queries to fail to match the corresponding fields.
- Attempting to import a PPT-format process document results in the system failing to recognize it. Cause: PPT format parsing support is not added to the unstructured data import configuration. The default configuration only supports text-based file formats.
How to Verify the Configuration is Correct
- Submit a simulated single-furnace load data write request, and check that the database connection count monitoring indicator does not exceed the configured upper limit.
- Execute a query request that includes heating temperature and holding duration, and confirm that the returned results match the numerical precision output by the testing equipment.
- Import a PPT-format heat treatment process card document, and confirm that the system can normally parse and extract text content.
- Submit multiple concurrent query and write requests, and confirm that no 429 status code is returned, and request latency meets the expected threshold.
The values provided are common starting points and should be measured against the reader's own samples.