遇见数据集

嘉钦精工行车记录仪壳体结构尺寸精度数据集

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深圳市数据知识产权登记系统2026-02-07 更新2026-02-07 收录
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资源简介:

本数据集主要应用于嘉钦精工行车记录仪壳体产品在注塑成型完成后的结构尺寸精度检测、装配适配性分析及产品一致性管理等数据化应用场景。行车记录仪壳体作为电子终端产品的重要结构件,其整体结构尺寸精度直接影响内部电路、光学模组及固定组件的装配稳定性和使用可靠性。通过对壳体关键结构尺寸进行系统化采集与量化分析,本数据集用于构建基于数据的结构尺寸精度评估体系。在实际应用中,该数据集可用于不同生产批次、不同模具条件及不同生产阶段下的结构尺寸精度对比分析,识别尺寸偏差变化趋势及潜在结构风险。同时,通过对综合尺寸偏差指数的长期统计分析,可为模具修正、工艺参数调整及装配方案优化提供数据支撑。该应用场景强调结构尺寸数据在产品装配决策和质量管理中的分析价值,而非仅作为单件检测记录保存。

This dataset is mainly applied to data-driven application scenarios including structural dimensional accuracy inspection, assembly adaptability analysis, and product consistency management for dash camera housing products of Jiaqin Precision after injection molding. As a key structural component of electronic terminal products, the dash camera housing's overall structural dimensional accuracy directly affects the assembly stability and operational reliability of its internal circuits, optical modules, and fixing components. Through systematic collection and quantitative analysis of the housing's key structural dimensions, this dataset is used to establish a data-based evaluation system for structural dimensional accuracy. In practical applications, this dataset can support comparative analysis of structural dimensional accuracy across different production batches, mold conditions, and production stages, enabling the identification of trends in dimensional deviations and potential structural risks. Meanwhile, long-term statistical analysis of the comprehensive dimensional deviation index can provide data support for mold correction, process parameter adjustment, and assembly scheme optimization. This application scenario highlights the analytical value of structural dimensional data in product assembly decision-making and quality management, rather than merely storing it as single-piece inspection records.

创建时间:
2026-02-07
搜集汇总
数据集介绍
嘉钦精工行车记录仪壳体结构尺寸精度数据集 数据集图片
背景与挑战
背景概述
该数据集专注于行车记录仪壳体结构尺寸精度的检测与分析,包含关键尺寸的设计值、实测值和偏差计算数据,并生成综合尺寸偏差指数用于量化精度水平。它应用于注塑成型后的尺寸检测、装配适配性分析和产品一致性管理,支持模具修正和工艺优化。数据集以XLSX格式存储,通过加权计算和区间判定规则实现从原始检测到结构化分析数据的转化,为质量控制提供可靠基础。
以上内容由遇见数据集搜集并总结生成
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