生产共享平台光伏组件A级率应用数据
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通过生产共享平台对各基地的组件、电池、拉晶、切片生产关键指标数据进行集中采集，有效的降低人工数据统计时间，提高数据质量和准确性。同时，企业管理者和生产部门可以在该平台快速获取各基地的生产对标分析数据，利于了解各基地的生产情况和存在的问题，从而制定更加科学合理有效措施，以提高生产效率和产品质量。生产对标共享平台的数据采集分析规则主要包括：1、制定核算标准：制定各基地良率指标核算标准，如：A级率=（最终入库量-PCA1级产量(块)）/最终入库量*100%；2、数据抽取和整理：通过使用Kattle工具，周期性对多种数据源进行采集，并将数据进行清洗、数据格式转化、填充缺失数据，最终整理成符合的数据格式要求；3、数据加工和分析：通过使用BI工具提取数据，并使用聚类分析和关联规则算法挖掘关键参数；4、数据可视化展示：通过使用BI工具将数据结果集以图表、表格等多样化形式展示关键指标的变化趋势和全国各基地同类产品的产能对比；5、共享和协作：将共享平台的数据分析结果应用到企业生产管理过程，让企业管理者和生产部门在平台利用数据辅助决策，做到了然于心、谋定而动。
Centralized collection of key indicator data for component, battery, crystal pulling and wafer slicing production across all manufacturing bases via the production sharing platform effectively reduces manual data statistics time and improves data quality and accuracy. Meanwhile, enterprise managers and production departments can quickly access production benchmarking analysis data of each base through this platform, which enables them to gain insights into the production status and existing issues of each base, so as to formulate more scientific, reasonable and effective measures to improve production efficiency and product quality. The data collection and analysis rules of the production benchmarking sharing platform mainly include: 1. Formulate accounting standards: Develop yield indicator accounting standards for each base, e.g., Grade A rate = (Final stock-in quantity - PCA1 grade output (pieces)) / Final stock-in quantity * 100%; 2. Data extraction and organization: Use the Kattle tool to periodically collect data from multiple data sources, clean the data, convert data formats, impute missing values, and finally organize the data into a format that meets the specified requirements; 3. Data processing and analysis: Extract data using BI tools, and use cluster analysis and association rule algorithms to mine key parameters; 4. Data visualization and display: Use BI tools to present the changing trends of key indicators and the production capacity comparison of similar products across all domestic bases in diversified forms such as charts and tables; 5. Sharing and collaboration: Apply the data analysis results of the sharing platform to the enterprise production management process, allowing enterprise managers and production departments to use data for auxiliary decision-making on the platform, so that they can have a clear grasp of the production situation and make well-considered decisions.
