国内工业锅炉需求分析数据

对国内近三年各行业的工业锅炉需求数据进行分析，通过各行业每年对锅炉的数量及蒸发量的需求情况，分析行业未来的发展趋势，行业需求变化，为工业产品制造企业在未来工业品的设计研发方向提供有力数据支撑。1.数据来源：企业CRM系统中采集近3年工业锅炉行业的需求数量和用热蒸发量数据。
2.数据处理：（1）数据预处理：对采集得到的数据按照行业对锅炉数量及蒸发量分别汇总后分别计算平均值
（2）弹性需求计算：按照如下公式进行计算：相对平均偏差MAD=n∑i=1n∣Di−Fi∣，其中，DiD_iDi 表示实际值，FiF_iFi 表示预测值，n 表示期数。
（3）结果验证：计算预测值与实际值之间的平均绝对偏差，从而评估预测的准确性‌。

3.数据分析：根据|MAD|的数值可分析工业锅炉行业的需求量和用热蒸发量。（1）|MAD|=1（单位相对平均偏差），需求量预测值的平均偏差程度；（2）1<|MAD|（需求缺乏弹性），意味着工业锅炉在行业需求的过程中的变异性增加了，而较高的|MAD| 值表明数据点分布较为分散，需求量小；（3）|MAD|<1（需求富有弹性），在数据集中存在异常值的情况下更为稳健，数据点相对集中。
4.应用：
（1）对企业核心产品研发方向提供数据支撑；
（2）根据产品类型分布比例，结合实际订单获取情况，便于多个部门制定更为合理的、高效的工作流程，实现多部门协同联动降本增效目的。

This dataset conducts an analysis on the industrial boiler demand data of various domestic industries over the past three years. Leveraging the annual demand for boiler quantity and thermal evaporation capacity across different industries, it analyzes the future development trends and demand changes of these industries, providing robust data support for industrial product manufacturing enterprises to guide their future industrial product design and R&D directions.

1. Data Source: Data on the demand quantity and thermal evaporation capacity of the industrial boiler sector over the past three years are collected from the enterprise's CRM system.

2. Data Processing:
(1) Data Preprocessing: The collected data are aggregated by industry based on boiler quantity and thermal evaporation capacity respectively, and then the average values are calculated for each category.
(2) Elastic Demand Calculation: The calculation is performed using the standard formula for Mean Absolute Deviation (MAD): MAD = (1/n)∑_{i=1}^{n}|D_i - F_i|, where D_i represents the actual value, F_i represents the predicted value, and n denotes the number of periods.
(3) Result Validation: The accuracy of the demand forecast is evaluated by calculating the mean absolute deviation between the predicted values and the actual values.

3. Data Analysis: The demand and thermal evaporation capacity of the industrial boiler sector can be analyzed based on the magnitude of |MAD|:
(1) When |MAD| = 1 (unit relative mean absolute deviation), it reflects the average deviation level of the demand forecast values;
(2) When 1 < |MAD| (demand is inelastic), this indicates increased variability in industrial boiler demand across industries. A higher |MAD| value suggests that the data points are more dispersed, with smaller demand volumes;
(3) When |MAD| < 1 (demand is elastic), the model exhibits greater robustness when outliers exist in the dataset, and the data points are relatively concentrated.

4. Applications:
(1) Provide data support for determining the R&D directions of the enterprise's core products;
(2) Based on the distribution proportion of product types and combined with actual order acquisition status, it enables multiple departments to develop more reasonable and efficient work processes, achieving the goal of cross-departmental collaborative linkage to reduce costs and improve efficiency.

搜集汇总

数据集介绍

特点

该数据集包含8156条国内工业锅炉需求分析数据，涵盖行业、锅炉型号、蒸发量等字段，数据来源于企业CRM系统，更新频次为按需更新。主要用于分析行业需求变化，为企业产品研发提供数据支持。