紧固件行业委外加工产品质量检测数据

本数据是紧固件工业互联网平台的企业用户委托外部供应商加工的产品质量检测数据，通过依靠机器视觉检测机器对产品的尺寸和外观、机械性能、材料成分等项目进行检测。并将检查得分同步至系统。 用途：1、为紧固件行业工业互联网平台的外加工供应商等级评定提供依据，当其他紧固件企业提出外加工申请时，系统经过算法分析匹配最优质的供应商，促进行业整体质量提升。 2、有助于紧固件行业协会制定更严格和科学的行业标准和规范，并识别优秀的制造企业和落后企业，促进整个行业的健康发展。 3、政府部门可以利用数据，识别潜在的质量问题，进而制定相应的政策和法规，增强市场监管效率。 4、机器视觉系统可以收集和分析大量检测数据，供应商可以利用这些数据为客户提供更深入的质量控制和改进建议。1、数据来源：对外部加工的产品使用视觉检测机器对产品的外观、尺寸、机械性能、材料成分等检测，提供该批次产品各检测项平均得分。
2、数据处理及应用：平均分数（S）=检测项目1平均得分（a1)×权重1（w1)+检测项目2平均得分（a2)×权重2（w2)+检测项目3平均得分（a3)×权重3（w3)+检测项目4平均得分（a4)×权重4（w4)，对所得平均分数分段评估，S≥80时，该批次检测合格，60≤S＜80，该批次检测边缘合格，S＜60，该批次不合格。通过平均分数，为选择供应商提供参考依据，促进供应链上下游可持续性发展。

This dataset consists of product quality inspection data for products entrusted by enterprise users of the Fastener Industry Industrial Internet Platform to external suppliers for processing. Machine vision inspection equipment is used to detect items including product dimensions, appearance, mechanical properties, material composition and other relevant indicators, and the inspection scores are synchronized to the platform system.

Application scenarios:
1. Provide a basis for grading external processing suppliers on the Fastener Industry Industrial Internet Platform. When other fastener enterprises submit external processing applications, the system will match the most qualified suppliers through algorithmic analysis, so as to promote the overall quality improvement of the industry.
2. Help fastener industry associations formulate stricter and more scientific industry standards and specifications, identify excellent manufacturing enterprises and underperforming ones, and promote the healthy development of the entire industry.
3. Government departments can use the dataset to identify potential quality issues, formulate corresponding policies and regulations, and improve the efficiency of market supervision.
4. Machine vision systems can collect and analyze a large amount of inspection data, and suppliers can use this data to provide customers with in-depth quality control and improvement suggestions.

1. Data source: Visual inspection equipment is used to detect the appearance, dimensions, mechanical properties, material composition and other items of externally processed products, providing the average score of each inspection item for the corresponding product batch.
2. Data processing and application: The overall average score (S) is calculated as:
$S = a_1 imes w_1 + a_2 imes w_2 + a_3 imes w_3 + a_4 imes w_4$
Where $a_1$, $a_2$, $a_3$, $a_4$ refer to the average scores of the four inspection items respectively, and $w_1$, $w_2$, $w_3$, $w_4$ refer to the corresponding weights of each inspection item. Segmental evaluation is conducted on the obtained average score: when $S geq 80$, the product batch passes the inspection; when $60 leq S < 80$, the product batch is marginally qualified; when $S < 60$, the product batch fails the inspection. The overall average score serves as a reference for supplier selection, so as to promote the sustainable development of the upstream and downstream supply chain.

搜集汇总

数据集介绍

特点

该数据集为紧固件行业委外加工产品的质量检测数据，包含1403条记录，每日更新。数据通过机器视觉检测产品的外观、尺寸、机械性能、材料成分等，并计算综合得分，用于供应商评定、行业标准制定及质量控制改进。