南昌市电梯维保单位超期维保预警评价数据

采集和统计南昌市不同电梯维保单位超期维保相关数据，分析南昌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，采集南昌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 overdue elevator maintenance data of various elevator maintenance units in Nanchang City, aiming to evaluate the work quality of each maintenance unit, assist maintenance units in optimizing the allocation of safety management personnel, and provide local regulatory authorities with data support to hold interviews with maintenance units rated as "Warning", strengthen supervision, increase the frequency and content of daily maintenance, and reduce elevator safety hazards. It also provides data support for relevant personnel in charge of relevant links to formulate cooperation plans.

1. Data Collection: Collect data related to overdue elevator maintenance incidents of different elevator maintenance units in Nanchang City via elevator IoT devices and alarm receiving platforms.

2. Data Processing: Clean, analyze and organize the collected raw data to obtain the required datasets including: maintenance unit name, statistical time, region, maintenance type, number of overdue maintenance elevators, and number of involved residential communities.

3. Data Calculation: Define two proportion indicators:
- Proportion of overdue maintenance elevators of a unit = Total number of overdue maintenance elevators of the unit throughout the year / Total number of overdue maintenance elevators in Nanchang City throughout the year
- Proportion of involved residential communities of a unit = Total number of residential communities involved in overdue maintenance of the unit throughout the year / Total number of residential communities involved in overdue maintenance in Nanchang City throughout the year
The example data demonstrates the scenario of one maintenance unit. The dataset contains data from multiple maintenance units, with the unit name represented in the data field in the format of (unit name).

4. Early Warning Evaluation: Use IF functions to grade the algorithm results. For the proportion of overdue maintenance elevators:
- If 0 ≤ proportion ≤ 0.1, rating A is marked as "+"
- If proportion > 0.1, rating A is marked as "-"
For the proportion of involved residential communities:
- If 0 ≤ proportion ≤ 0.1, rating B is marked as "+"
- If proportion > 0.1, rating B is marked as "-"
When both rating A and rating B are "+", the overall rating of the unit is "Qualified"; all other scenarios result in a "Warning" rating. For maintenance units rated as "Warning", conduct interviews, strengthen supervision, increase the frequency and content of daily maintenance, and reduce elevator safety hazards.

搜集汇总

背景与挑战

背景概述

该数据集包含南昌市电梯维保单位的超期维保数据，每月更新601条记录，通过计算超期维保占比并进行分级评价（合格或示警），旨在帮助维保单位优化管理和监管部门加强安全监控，减少电梯安全隐患。