Inspection and Process Record Audit for Plastic Injection Molding: Knowledge Base Retrieval and Recall

What this category of data looks like

This category of data covers the entire production flow of enterprises manufacturing injection molded parts, automotive interior components, home appliance parts, and medical plastic products. Daily documents include injection molding process cards, raw material drying records, mold histories, first-piece inspection forms, shift patrol inspection forms, and material change and machine cleaning records. Data sources include resin batch property sheets, injection molding machine operating parameters, mold temperature controller data, MES systems, and dimensional and appearance inspection results. Updates trigger with each production batch, mold change, material change, and each shift’s patrol inspection. Document fields include process parameters (units: MPa, seconds, degrees Celsius), material batch numbers, inspection values (units: millimeters), mold cycle records, and additional relevant fields.

What constraints this category imposes on knowledge base retrieval and recall

The high-frequency update nature of this category requires the knowledge base to support incremental updates triggered by production batches and mold change events. This avoids excessive full indexing time that would disrupt real-time query performance. The mixed structure of multiple document types, including process parameters, inspection records, and material histories with distinct fields, requires retrieval to match professional process semantics that include units. This reduces the number of irrelevant results. Differences in structural completeness across data sources require that retrieval scopes can be limited by dimensions such as mold and production shift. It also requires adaptation to semantic recall for professional terms like resin properties and injection molding machine parameters, to prevent semantic search mis-hits.

Configuration Settings

This configuration is based on the knowledge base retrieval function of FastGPT v4.17.0.

Three Common Configuration Mistakes

• Retrieval results include mold history documents unrelated to the current production batch. The cause is failure to limit the retrieval scope via collectionIds, leading to recall of redundant data across shifts and molds.
• Semantic search for "shrinkage defect analysis" hits defect documents from non-injection molding categories. The cause is failure to enable datasetSearchUsingExtensionQuery to filter irrelevant professional term associations, resulting in semantic mismatching.
• Retrieval time exceeds expected thresholds. The cause is failure to set a reasonable limit parameter, which recalls too many redundant documents and increases context processing time.

How to Verify Correct Configuration

• Manually input keyword terms for the current production batch’s process parameters, check that returned results include target documents such as injection molding process cards and patrol inspection forms.
• Trigger a document update for material change and machine cleaning, wait 10 minutes, then retrieve corresponding keyword terms. Confirm that updated documents have been recalled.
• View retrieval logs, check that the similarity threshold filters out low-relevance results below the set value, and that usingReRank has re-ranked the results.
• Check the collectionIds parameter, confirm that only the knowledge base collection bound to the current production shift is being retrieved, and no documents from other molds are included.

Note: The configuration values listed here are common starting points. Adjustments should be made based on local samples.