高密度聚乙烯
废品
焊接
流离失所(心理学)
支持向量机
过程(计算)
机械工程
材料科学
计算机科学
机器学习
工程类
复合材料
聚乙烯
心理学
操作系统
心理治疗师
作者
B. Novaković,Mohamed Kashkoush
摘要
Abstract This research studies the material displacement of high‐density polyethylene (HDPE) during the initial stage of the hot plate welding (HPW) process, called the Matching stage. Newly developed mathematical models simulate the relationship between the main process parameters (force, temperature, and time) and the size of the surface area. The collected data was used to develop four mathematical models for material displacement and time. Two models are machine learning based models (support vector machines). The other two models are regression models in the form of functions. In addition, this study provides a visual representation of HDPE melt displacement with the changes in temperature and pressure. The obtained results indicate that these models can be used for developing a parameter adjustment process or determining specifications for new production equipment. The potential applications of the developed models can be extended to industries that use HPW of HDPE, such as automotive or aerospace. This could result in significant savings in the amount of scrap and waste due to inaccurate and ad hoc settings that currently take place in the industry. Highlights Study of HDPE material displacement in the hot plate welding Matching stage. Visualization of HDPE melt displacement with temperature and pressure changes. Development of SVM and mathematical regression models. Applications in parameter adjustment and equipment specification. Savings in scrap and waste by reducing inaccurate settings.
科研通智能强力驱动
Strongly Powered by AbleSci AI