吹膜生产工艺参数数据集合

1、工艺参数匹配算法：采用协同过滤算法，以“产品厚度、宽度、原料类型”为特征，匹配历史相似产品的最优工艺参数组合，如输入“0.012mm、1200mm、PBAT/PLA共混”，自动输出“机筒温度172-182-187℃、吹胀比1.9”，匹配准确率达93%以上，减少技术人员经验依赖。2、参数-效果关联模型：通过多元线性回归分析“机筒温度、吹胀比、牵引速度”与“膜厚均匀度、拉伸强度”的关联度，得出“机筒3段温度每升高1℃，拉伸强度提升0.3MPa”“吹胀比每增加0.1，膜宽偏差减少0.5%”等量化规律，为参数微调提供数据依据。3、工艺优化推荐规则：构建“成本-质量”平衡模型，当产品合格率达标（≥99%）时，自动推荐能耗更低的参数组合（如将螺杆转速从80r/min降至78r/min，能耗降低4%且合格率无波动），实现“质量达标下的成本最优”。

1. Process Parameter Matching Algorithm: A collaborative filtering algorithm is adopted, which takes "product thickness, width, raw material type" as features to match the optimal process parameter combination of historically similar products. For example, when inputting "0.012mm, 1200mm, PBAT/PLA blend", it will automatically output "barrel temperature: 172-182-187℃, blow-up ratio: 1.9". The matching accuracy exceeds 93%, reducing the reliance on technicians' experience.
2. Parameter-Effect Correlation Model: Multiple linear regression is used to analyze the correlation between "barrel temperature, blow-up ratio, traction speed" and "film thickness uniformity, tensile strength", deriving quantitative rules such as "each 1℃ increase in the 3-stage barrel temperature leads to a 0.3 MPa improvement in tensile strength" and "each 0.1 increase in blow-up ratio reduces the film width deviation by 0.5%", providing data support for parameter fine-tuning.
3. Process Optimization Recommendation Rules: A "cost-quality" balance model is constructed. When the product qualification rate reaches the standard (≥99%), parameter combinations with lower energy consumption will be automatically recommended. For instance, reducing the screw speed from 80 r/min to 78 r/min cuts energy consumption by 4% without affecting the qualification rate, achieving "cost optimization under the premise of qualified product quality".