单轴精密绕线机运行效率数据

通过对单轴精密绕线机运行效率数据采集于电控精密调压阀，采集设备的关键运行参数，包括日期、名称、型号、运行时间、当日加工数和报废数量等。这些数据不仅用于计算设备的稼动率、加工合格率、性能效率和OEE（设备综合效率），还为设备的稳定运行提供了重要支撑。基于单轴精密绕线机运行效率数据，企业可以优化电控精密调压阀的生产计划，提高生产效率，同时将有价值的数据反馈给设备制造商，促进产品改进和性能提升。同行制造商可通过比较稼动率和OEE等指标，评估自身在行业中的位置，并决定是否需要改进生产流程或升级设备。潜在的设备购买者可利用这些数据作为参考，评估设备在实际生产环境中的表现，辅助采购决策。下游客户则可借此了解供应商的生产能力和稳定性，如高稼动率和OEE可能表明供应商有能力满足大量订单需求。1：数据采集：通过对 单轴精密绕线机F-100AN（XYRX-044） 数据进行统计分析，了解日期、设备名称、设备型号、运行时间、当日加工数、报废数量等运行数据
2.数据处理：通过算法计算可知，稼动率=运行时长/开机时间 *100；合格率=（当日加工数-报废数量）/当日加工数 *100；性能效率=（当日设备加工总数量-上一日设备加工总数量）/(开机时间 * 3600 /单价加工总数时长（件/S））*100;OEE=稼动率*合格率*性能效率；OEE波动率（%）=(当日OEE-前一天OEE)/前一天OEE *100。
3、数据应用：OEE波动率分为五个等级：当波动率大于或等于5%时被视为"优秀"，表明设备效率显著提升；0%到5%之间为"良好"，代表效率保持稳定或有小幅提升；-5%到0%之间被归类为"一般"，表示效率略有下降但仍在可接受范围内；-10%到-5%之间被标记为"需改进"，意味着效率下降明显，需要采取措施；而低于-10%则被视为"警告"级别，表明可能存在严重问题，需要立即介入。

This dataset is sourced from the operating efficiency data of single-axis precision winding machines used for electrically controlled precision pressure regulating valves. Key operating parameters of the equipment are collected, including date, equipment name, model, operating time, daily processed quantity, scrapped quantity, and other relevant metrics. These data are not only used to calculate equipment utilization rate, processing pass rate, performance efficiency, and OEE (Overall Equipment Effectiveness), but also provide critical support for the stable operation of the equipment. Based on the operating efficiency data of single-axis precision winding machines, enterprises can optimize the production planning of electrically controlled precision pressure regulating valves, improve production efficiency, and feed valuable data back to equipment manufacturers to facilitate product improvement and performance enhancement. Peer manufacturers can evaluate their industry position by comparing indicators such as utilization rate and OEE, and determine whether to optimize production processes or upgrade equipment. Potential equipment buyers can use these data as a reference to assess the actual performance of the equipment in production environments and support their purchasing decisions. Downstream customers can also leverage this data to understand the production capacity and stability of suppliers; for instance, high utilization rate and OEE may indicate that the supplier is capable of fulfilling large-scale order demands.

1. Data Collection: Conduct statistical analysis on the operating data of single-axis precision winding machine F-100AN (XYRX-044) to collect metrics including date, equipment name, equipment model, operating time, daily processed quantity, and scrapped quantity.

2. Data Processing: Calculate relevant indicators via algorithms as follows:
Equipment Utilization Rate = (Operating Duration / Boot-up Time) × 100;
Processing Pass Rate = [(Daily Processed Quantity - Scrapped Quantity) / Daily Processed Quantity] × 100;
Performance Efficiency = [(Total Daily Equipment Processed Quantity - Total Equipment Processed Quantity of the Previous Day) / (Boot-up Time × 3600 / Unit Processing Duration (pieces/second))] × 100;
OEE (Overall Equipment Effectiveness) = Equipment Utilization Rate × Processing Pass Rate × Performance Efficiency;
OEE Volatility (%) = [(Daily OEE - Previous Day's OEE) / Previous Day's OEE] × 100.

3. Data Application: OEE volatility is divided into five levels:
- "Excellent": When volatility is greater than or equal to 5%, indicating a significant improvement in equipment efficiency;
- "Good": When volatility ranges from 0% to 5%, representing stable efficiency or a slight improvement;
- "Fair": When volatility ranges from -5% to 0%, indicating a slight efficiency decline but still within an acceptable range;
- "Needs Improvement": When volatility ranges from -10% to -5%, meaning a notable efficiency decline requiring corrective actions;
- "Alert": When volatility is lower than -10%, indicating potential serious issues that demand immediate intervention.