无锡市电梯维保单位超期维保预警评价数据

采集和统计无锡市不同电梯维保单位超期维保相关数据，分析无锡市各维保单位工作质量。帮助各维保单位优化安全管理作业人员配置；当地监管部门根据各维保单位的超期维保相关数据的分析，对评价结果为“示警”的维保单位进行约谈、加强监管，提高日常维护频率和内容，减少电梯安全隐患。为相关环节负责人考虑合作方案提供数据支持。1、数据采集：通过电梯物联网设备和接警平台，采集无锡市不同电梯维保单位出现超期维保情形的相关数据. 2、数据处理：对采集到的原始数据进行清洗、分析、整理等方式，获取所需要的数据：维保单位，统计时间，地区，维保类型，超期维保数量，涉及小区数量.3.数据计算：单位超期维保电梯数量占比＝单位全年超期维保电梯总数/XX市全年超期维保电梯总数，单位超期维保涉及小区占比＝单位全年超期维保涉及小区数/XX市全年超期维保涉及小区数量.示例数据展示一个维保单位相关情形，数据包内包含多个维保单位数据，以（单位名称）的形式体现在数据字段中.4.预警评价：采取IF函数，对算法结果进行分级评价.就超期维保电梯数量占比而言，IF【0≤占比≤0.1】，评价A记为﹢，IF【占比＞0.1】，评价A记为-.就涉及小区数量占比而言，IF【0≤占比≤0.1】，评价B记为﹢，IF【占比＞0.1】，评价B记为-。当评价A和评价B同时为﹢时，单位整体评价为合格，其它情形皆评价为“示警”，对评价结果为“示警”的维保单位进行约谈、加强监管，提高日常维护频率和内容，减少电梯安全隐患。

This dataset collects and statistically analyzes data related to overdue maintenance of different elevator maintenance companies in Wuxi, to evaluate the work quality of each maintenance enterprise. It assists maintenance companies in optimizing safety management and staffing configuration; local regulatory authorities can leverage the analysis results of overdue maintenance data for each maintenance company to conduct disciplinary talks with enterprises rated as "Warning-level", strengthen supervision, increase the frequency and scope of daily maintenance, and reduce elevator safety hazards. It also provides data support for relevant personnel to formulate cooperation plans. 1. Data Collection: Relevant data on overdue maintenance cases of various elevator maintenance companies in Wuxi is collected via elevator Internet of Things (IoT) devices and alarm receiving platforms. 2. Data Processing: Clean, analyze and organize the collected raw data to obtain the required information: maintenance company, statistical time period, region, maintenance type, number of overdue maintenance elevators, and number of involved residential communities. 3. Data Calculation: Proportion of overdue maintenance elevators of the company = Total number of overdue maintenance elevators of the company in the whole year / Total number of overdue maintenance elevators in Wuxi in the whole year; Proportion of involved residential communities of the company = Number of overdue maintenance-related residential communities of the company in the whole year / Total number of overdue maintenance-related residential communities in Wuxi in the whole year. The example data shows the situation of one maintenance company, and the dataset contains data of multiple maintenance companies, with the company name presented in the data field in the format of (Company Name). 4. Early Warning Evaluation: Grade the algorithm results using IF functions. For the proportion of overdue maintenance elevators: IF [0 ≤ proportion ≤ 0.1], mark Evaluation A as "+"; IF [proportion > 0.1], mark Evaluation A as "-". For the proportion of involved residential communities: IF [0 ≤ proportion ≤ 0.1], mark Evaluation B as "+"; IF [proportion > 0.1], mark Evaluation B as "-". When both Evaluation A and Evaluation B are "+", the overall evaluation of the company is "Qualified"; all other scenarios are evaluated as "Warning-level". For maintenance companies with a "Warning-level" evaluation result, disciplinary talks will be conducted, supervision will be strengthened, the frequency and content of daily maintenance will be increased, and elevator safety hazards will be reduced.

搜集汇总

背景与挑战

背景概述

该数据集记录了无锡市电梯维保单位的超期维保情况，包含维保单位编码、超期维保数量、涉及小区数量等15个字段，共601条记录，每月更新，用于评估维保单位工作质量和辅助监管决策。