系统断桥铝合金门窗需求量预测数据

本数据聚焦于预测系统断桥铝合金门窗的需求量。对公司而言，通过预测各区域对该产品的需求量，可以精准配置生产技术人员和设备资源，合理规划生产能力，避免人力资源闲置或产品供不应求的情况发生。对于建筑设计单位、家装公司、门窗经销商及相关服务商而言，这些预测数据可作为其生产计划和库存管理的重要参考。基于对未来市场需求趋势的理解，供应商可以相应调整供应和服务策略，避免原材料及成品的积压或短缺。1.数据采集：采集系统断桥铝合金门窗的销售数据，包括统计时间、分析时间、订单编号、销售区域、产品名称、订单数量/㎡、订单金额/元。
2.数据预处理：对采集的数据进行清洗，去除重复记录，处理缺失值。
3.数据加工与分析：（1）计算历史需求量：对于每个具体型号的产品名称，使用SUMIFS函数对订单数量进行累加，分别计算出其过去365天、90天和30天的总需求量。（2）建立需求量预测模型：每种产品名称的未来30天需求量预测值=[(过去365天总需求量÷365*a)+(过去90天的总需求量÷90*b)+(过去30天的总需求量÷30×c)]*30*k；其中，系数a=0.5，b=0.3，c=0.2，调整因子k=1.1。系数a、b、c反映数值对未来30天需求量预测的影响程度，由于算法更注重长期需求趋势的影响，因此a被赋予了最高的权重。调整因子k 基于市场增长预期进行修正。

This dataset focuses on forecasting the demand for system thermal break aluminum alloy doors and windows. For manufacturing enterprises, forecasting the regional demand of this product allows for precise allocation of production technicians and equipment resources, as well as rational planning of production capacity, thus avoiding issues such as idle human resources or product supply shortages. For architectural design institutions, home decoration companies, door and window dealers and relevant service providers, these forecast data can serve as an important reference for their production planning and inventory management. Based on an understanding of future market demand trends, suppliers can adjust their supply and service strategies accordingly to prevent overstocking or shortage of raw materials and finished products.

1. Data Collection
Collect sales data of system thermal break aluminum alloy doors and windows, including statistical time, analysis time, order number, sales region, product name, order quantity (in ㎡), and order amount (in RMB).

2. Data Preprocessing
Clean the collected data, remove duplicate records, and handle missing values.

3. Data Processing and Analysis
(1) Calculate historical demand: For product names of specific models, use the SUMIFS function to accumulate order quantities, and calculate the total demand over the past 365 days, 90 days, and 30 days respectively.
(2) Establish demand forecasting model: The 30-day future demand forecast value for each product name is calculated as: [(Total demand over the past 365 days ÷ 365 × a) + (Total demand over the past 90 days ÷ 90 × b) + (Total demand over the past 30 days ÷ 30 × c)] × 30 × k; where the coefficients are a=0.5, b=0.3, c=0.2, and the adjustment factor k=1.1. The coefficients a, b and c reflect the degree of influence of their respective values on the 30-day future demand forecast. Since the algorithm prioritizes the impact of long-term demand trends, a is assigned the highest weight. The adjustment factor k is revised based on market growth expectations.

搜集汇总

背景与挑战

背景概述

该数据集是杭州墅景门窗科技有限公司的系统断桥铝合金门窗需求量预测数据，包含547条CSV格式记录，每日更新。数据集通过采集销售数据并应用加权平均算法预测未来30天需求量，权重侧重于长期趋势，用于辅助企业优化生产资源配置和库存管理，避免资源闲置或短缺问题。