工业产品质量预测评测数据集

本数据集聚焦工业生产过程中的产品质量在线预测，覆盖半导体、钢铁、注塑、光伏、锂电池等行业。数据内容包括批次元数据、工艺参数（静态与时序特征，如温度、压力、速度、电流等）、质量指标标签（连续型如尺寸/强度/容量，分类型如合格/不合格）及训练/测试划分。适用于质量预测模型训练、工艺参数优化、异常批次根因分析、过程监控等场景。This dataset focuses on online product quality prediction in industrial production processes, covering industries including semiconductors, steel, injection molding, photovoltaic, and lithium batteries. The data includes batch metadata, process parameters (static and temporal features such as temperature, pressure, speed, current, etc.), quality indicator labels (continuous labels like size, strength, and capacity; categorical labels such as qualified/unqualified), as well as training/testing splits. It is applicable to scenarios such as quality prediction model training, process parameter optimization, root cause analysis of abnormal batches, and process monitoring.

搜集汇总

背景与挑战

背景概述

该数据集专注于工业产品质量的在线预测，覆盖半导体、钢铁、注塑、光伏和锂电池等多个行业。它包含批次元数据、工艺参数（如温度、压力等静态与时序特征）以及质量指标标签（包括连续型和分类型），适用于训练质量预测模型、优化工艺参数和分析异常批次根因等应用场景。