从经济,环境,社会和可持续发展的角度进行数据驱动的可持续性评估和制造系统改进
Xiaoxiao Si1, Cuixia Zhang2, Cui Wang3
1School of Electrical and Architectural Engineering, Huaibei Institute of Technology, Huaibei, 235000, China.
Environmental science and pollution research international
|April 29, 2024
概括
本研究引入了一种数据驱动的方法,用于评估和改进使用新兴方法的制造业可持续性. 将这一点应用于一个边框车间,显著提高了可持续性指标,为环保生产提供了一个参考.
科学领域:
- 工业工程 工业工程 工业工程
- 环境科学 环境科学
- 可持续性科学 可持续性科学
背景情况:
- 可持续制造对于碳中和至关重要,但目前的系统面临着诸如高资源消耗和环境退化等挑战.
- 在评估和提高制造系统的可持续性方面,研究有限.
- 开发有效的指标系统对于指导制造业可持续发展至关重要.
研究的目的:
- 开发一个数据驱动的方法来评估和改善制造系统的可持续性.
- 构建一个包含经济,环境,社会和可持续性视角的可持续发展评估模型.
- 在制造业背景下分析资源消耗,污染和可持续性之间的相互关系.
主要方法:
- 使用制造业生产过程数据开发了一种数据驱动的方法.
- 使用新兴方法来统一评估模型的数据维度.
- 从四个关键角度构建了一个可持续发展评估模型:经济,环境,社会和可持续性.
主要成果:
- 该方法应用于一家法兰生产车间,确定了优化方案.
- 实施导致新兴收益率 (EYR) 增加了23.40%,新兴可持续性指数 (ESI) 增加了52.76%.
- 环境负载率 (ELR) 降低了19.03%,人均新兴能源 (EPP) 增加了6.88%.
结论:
- 开发的方法论为分析和可视化制造业可持续发展提供了有效的工具.
- 该研究强调了技术和管理在实现可持续制造方面的关系.
- 结果为寻求可持续和精益制造实践的企业提供了有价值的参考.
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