XBJ36BL-90纵剪机设备的运行效率数据

通过对XBJ36BL-90纵剪机的硅钢片剪切数据进行统计分析，了解日期、产线名称、工序名称、设备名称、设备型号、理论生产速率、计划工作时间、操作时间、维修时间、剪切总数、合格剪切总数等运行数据，分析XBJ36BL-90纵剪机的可用率、表现系数、质量指数、设备使用效率、同比增长率，为XBJ36BL-90纵剪机的健康运行提供数据支撑，在确保XBJ36BL-90纵剪机稳定运行的基础上，提高XBJ36BL-90纵剪机生产效率。XBJ36BL-90纵剪机的硅钢片剪切数据，不仅能应用于企业内部，针对硅钢片(数控)纵剪生产线的运行设备进行优化和采购指导，也能帮助变压器、电机、家电、汽车、建材、包装等行业的相关企业深入的了解XBJ36BL-90纵剪机的工作特性，对该企业的相关设备采购工作提供参考价值。算法规则包括以下几个方面：1.数据采集：通过对XBJ36BL-90纵剪机的运行数据进行采集，包括日期、产线名称、工序名称、设备名称、设备型号、理论生产速率、计划工作时间、操作时间、维修时间、剪切总数、合格剪切总数。2.数据处理：通过算法计算可知，可用率=操作时间/计划工作时间*100%；表现系数=（剪切总数/操作时间）/（理论生产速率*60）*100%；质量指数=合格剪切总数/剪切总数*100%；设备使用效率=可用率*表现系数*质量指数；同比增长率=（本期设备使用效率－同期设备使用效率）/同期设备使用效率*100%。3.数据应用：根据可用率、表现系数、质量指数、设备使用效率、同比增长率以及设备平均使用率的相关数据变化，为XBJ36BL-90纵剪机设备健康运行提供数据支撑，便于管理部门对硅钢片(数控)纵剪生产线进行全面评估，为企业智能化工厂的建设提供支持和数据保障。By conducting statistical analysis on the silicon steel sheet shearing data of the XBJ36BL-90 slitting machine, this work collects operational data including date, production line name, process name, equipment name, equipment model, theoretical production rate, scheduled working hours, operating time, maintenance time, total shearing quantity, and qualified shearing quantity, and analyzes the availability rate, performance coefficient, quality index, equipment utilization efficiency, and year-on-year growth rate of the XBJ36BL-90 slitting machine. The purpose is to provide data support for the healthy operation of the XBJ36BL-90 slitting machine, and improve its production efficiency on the basis of ensuring its stable operation. The silicon steel sheet shearing data of the XBJ36BL-90 slitting machine can not only be applied within the enterprise to provide optimization and procurement guidance for the operating equipment of the silicon steel sheet (CNC) slitting production line, but also help relevant enterprises in industries such as transformers, motors, home appliances, automobiles, building materials, and packaging to deeply understand the operating characteristics of the XBJ36BL-90 slitting machine, providing reference value for the equipment procurement work of these enterprises. The algorithmic framework includes the following aspects: 1. Data Collection: Collect the operational data of the XBJ36BL-90 slitting machine, including date, production line name, process name, equipment name, equipment model, theoretical production rate, scheduled working hours, operating time, maintenance time, total shearing quantity, and qualified shearing quantity. 2. Data Processing: Calculated via algorithms, the metrics are defined as follows: Availability Rate = (Operating Time / Scheduled Working Hours) * 100%; Performance Coefficient = [(Total Shearing Quantity / Operating Time) / (Theoretical Production Rate * 60)] * 100%; Quality Index = (Qualified Shearing Quantity / Total Shearing Quantity) * 100%; Equipment Utilization Efficiency = Availability Rate * Performance Coefficient * Quality Index; Year-on-Year Growth Rate = [(Current Period Equipment Utilization Efficiency - Same Period Equipment Utilization Efficiency) / Same Period Equipment Utilization Efficiency] * 100%. 3. Data Application: Based on the changes in relevant data such as availability rate, performance coefficient, quality index, equipment utilization efficiency, year-on-year growth rate, and average equipment utilization rate, provide data support for the healthy operation of the XBJ36BL-90 slitting machine, facilitate the management department to conduct a comprehensive assessment of the silicon steel sheet (CNC) slitting production line, and provide support and data guarantee for the construction of the enterprise's smart factory.

搜集汇总

数据集介绍

特点

该数据集记录了XBJ36BL-90纵剪机设备的运行效率数据，包含多个关键性能指标，如可用率、表现系数、质量指数等，用于设备健康运行的监控和优化。数据集规模为300条，每季度更新，适用于制造业的设备管理和采购决策。