加强循环经济实践:生命周期评估和机器学习驱动的剩余价值预测在支持物联网的微波炉中
Asif Iqbal1, Sonia Akhter1, Shahed Mahmud1
1Department of Industrial & Production Engineering, Rajshahi University of Engineering & Technology, Rajshahi-6204, Bangladesh.
Heliyon
|October 14, 2024
概括
将物联网 (IoT) 技术集成到微波炉中,可以通过准确预测剩余值来增强循环经济 (CE). 这提高了设备的利用率,并促进了可持续的资源管理.
科学领域:
- 环境科学 环境科学
- 计算机科学 计算机科学
- 材料科学 材料科学 材料科学
背景情况:
- 资源稀缺和环境问题需要创新的解决方案来管理家用电器.
- 目前对设备的使用后残留值的评估方法不足,导致使用量减少和过早处置.
- 包括微波炉在内的电子废物管理效率低下,对污染和资源枯竭作出了重大贡献.
研究的目的:
- 将物联网 (IoT) 技术集成到微波炉中,以实时监控性能.
- 开发一种预测性维护模型,用于估计设备生命周期,并在循环经济 (CE) 原则中对组件进行分类.
- 准确预测物联网启用微波炉的剩余值,使用机器学习来提高资源利用率.
主要方法:
- 使用集成的物联网传感器实时监控微波炉参数 (电压,电流,门关闭,电机/叶片旋转).
- 开发一个预测性维护模型,整合物联网数据分析和调查见解.
- 机器学习模型的应用 (随机森林,梯度增强,决策树) 用于剩余值预测.
主要成果:
- 物联网传感器数据促进了微波炉的性能分析和趋势跟踪.
- 预测性维护模型成功估计了部件生命周期和CE分类.
- 与梯度增强和决策树相比,随机森林模型在预测支持物联网的微波炉的剩余值方面取得了更高的准确性.
结论:
- 物联网在家用电器中的整合为推进循环经济实践提供了可行的途径.
- 预测性维护和准确的剩余值评估可以显著提高设备的使用率和寿命.
- 技术进步,特别是机器学习,是提高资源效率和可持续产品管理的关键.
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