（医药化工企业）高处作业效率管理数据

在浙江省化学原料药产业大脑数据服务中，高处作业是医药化工企业机械作业的高风险类型，包括设备高空架设、厂房外墙检修、储罐顶部焊接等场景，存在人员坠落、工具坠物伤人、火灾及触电等隐患。​ 作业前，企业需线上办许可证，系统自动调取登高设备维护记录、作业区风速等传感器数据及操作人员资格证，生成含流程、风险点和防护要求的电子作业票。​ 作业后，系统依据设备效率、作业周期、安全事故等指标算效率系数，输出报告，找出瓶颈与漏洞。​ 案例显示，某企业优化后，设备损坏率降 28%，单位工时产量升 22%，安全事故减 45%。该服务可推广，实现高处作业效率标准化管理，提升安全性。​ 1.数据采集：运用大数据平台，对医药化工行业各企业相关作业票数据进行采集并汇总，对部分数据和字段进行脱敏清洗。 2.数据运算：(1)承包商的作业票比重a=n/N×100%，其中N为总作业票数量，n为承包商的作业票数量；(2)作业总时长T=t1+t2+t3，其中t1为作业状态持续时长，t2为作业超期时长，t3为验收终止时长；(3)作业票效率系数x=a*T，结果保留两位小数。3.数据分析：若x＜3，则作业分析结果为“A级作业”；若3≤x＜6，则作业分析结果为“B级作业”；若6≤x＜9，则作业分析结果为“C级作业”；若x≥9，则作业分析结果为“D级作业”。In the data service of the Zhejiang Province Chemical Active Pharmaceutical Ingredient (API) Industrial Brain, working at height is a high-risk type of mechanical operation in pharmaceutical and chemical enterprises, covering scenarios such as high-altitude equipment erection, workshop exterior wall maintenance, and welding on top of storage tanks, with hidden hazards including personnel falling, injuries caused by falling tools, fires, and electric shocks. Before the operation, enterprises need to apply for permits online. The system automatically retrieves maintenance records of height-working equipment, sensor data such as wind speed in the operation area, and qualification certificates of operators, and generates electronic work tickets that include operation procedures, risk points, and protection requirements. After the operation, the system calculates the efficiency coefficient based on indicators such as equipment efficiency, operation cycle, and safety accidents, outputs a report, and identifies bottlenecks and loopholes. Case studies show that after optimization by a certain enterprise, the equipment damage rate decreased by 28%, the output per man-hour increased by 22%, and safety accidents were reduced by 45%. This service can be promoted and popularized to realize standardized management of working-at-height operation efficiency and improve safety. 1. Data Collection: Use a big data platform to collect and aggregate relevant work ticket data from enterprises in the pharmaceutical and chemical industry, and perform desensitization and cleaning on part of the data and fields. 2. Data Calculation: (1) Contractor's work ticket proportion a = n/N × 100%, where N is the total number of work tickets, and n is the number of contractor's work tickets; (2) Total operation duration T = t1 + t2 + t3, where t1 is the duration of the operation status, t2 is the overdue duration of the operation, and t3 is the acceptance termination duration; (3) Work ticket efficiency coefficient x = a*T, with the result rounded to two decimal places. 3. Data Analysis: If x < 3, the operation analysis result is "Level A Operation"; if 3 ≤ x < 6, the result is "Level B Operation"; if 6 ≤ x < 9, the result is "Level C Operation"; if x ≥ 9, the result is "Level D Operation".

搜集汇总

背景与挑战

背景概述

该数据集聚焦医药化工企业高处作业效率管理，包含401条每日更新的企业数据，涵盖作业票编号、作业内容、等级、作业时长和效率系数等关键字段。通过算法计算承包商作业票比重和作业总时长，得出效率系数并分级（A到D级），用于识别作业瓶颈、提升安全性和优化生产效率，应用案例显示能显著降低设备损坏率和安全事故。