2022年10月11日，本批评选出的3家分别来自Arçelik、美光联合利华、西部数据。
1. Arçelik（罗马尼亚，乌尔米）
Arçelik乌尔米绿色工厂，实现了100%绿电供应，成功开展了数个可持续发展用例项目，包括用于能源管理的数字孪生项目以及集成了先进水处理工厂的水资源闭环管理系统。在用水紧张的背景下，该项目为每件产品生产节约25%用水量，降低17%能源消耗以及22%温室气体排放。
2. 美光（新加坡）
随着对内存和存储解决方案的需求不断增长，新加坡美光科技有限公司需要扩大和增加千兆字节产品的产量，同时减少对环境的影响。2018年到2021年，新加坡美光科技有限公司产量增加了270%，同时每生产千兆字节的资源消耗减少了45%。这得益于可持续的技术发展，通过跟踪环境足迹不断优化材料消耗。
3. 联合利华（达帕达，印度）
为了实现企业的可持续发展目标，即到2025年将温室气体范围1和2的排放量减少70%（相较于2015年基线），并在应对产量快速增长的同时减少水资源消耗，联合利华达帕达开展了14个使用案例，如通过集成能源管理系统实现以机器学习驱动的能源优化，运用数字孪生技术加速制定生态友好型配方生产策略。达帕达将范围1和2的排放量减少了54%，范围3的排放量减少了43%，用水量减少了36%，提前实现了其减排目标。
4. 西部数据（上海，中国）
在需求不断增长的情况下，西部数据在2017年至2021年期间将工厂拍字节（PB）产量翻了一番，同时减少了每PB产品的环境足迹，以实现企业的减排目标。这一结果由第四次工业革命的多项科技驱动，如运用机器学习动态优化水循环工厂性能以及根据实时操作数据检测异常能耗预测系统。这些措施使每PB产品水资源消耗减少了62%，能源消耗减少了51%。
翻译：
What will be sustainable lighthouses in 2022?
On October 11, 2022, the three companies selected by this criticism were from Arcelik, Micron Unilever, and Western Digital.
1. Arcelik (Urmi, Romania)
Arcelik’s Ulmi Green Plant, which has achieved 100% green electricity supply, has successfully implemented several sustainability use case projects, including a digital twin for energy management and a closed-loop water management system integrated with an advanced water treatment plant. In the context of water scarcity, the project has reduced water use by 25% per product production, energy consumption by 17% and greenhouse gas emissions by 22%.
2. Micron (Singapore)
With the growing demand for memory and storage solutions, Micron Technology Singapore Limited needed to expand and increase the production of gigabyte products while reducing its environmental impact. Between 2018 and 2021, Micron Technology Limited increased production by 270% while reducing resource consumption per gigabyte produced by 45%. This is thanks to sustainable technological developments that continuously optimize material consumption by tracking the environmental footprint.
3. Unilever (Dapada, India)
In order to achieve the company’s sustainability goal of reducing greenhouse gas emissions in Scope 1 and 2 by 70% by 2025 (compared to the 2015 baseline) and reducing water consumption while responding to rapid production growth, Unilever Dapada has developed 14 use cases, such as machine learning-driven energy optimization through integrated energy management systems. Accelerate the development of eco-friendly formula production strategies with digital twin technology. Dapada achieved its emission reduction targets ahead of schedule by reducing emissions in Scope 1 and 2 by 54 percent, Scope 3 by 43 percent, and water use by 36 percent.
4. Western Digital (Shanghai, China)
Amid growing demand, Western Digital doubled factory petabyte (petabyte) production between 2017 and 2021, while reducing the environmental footprint per petabyte of product to meet the company’s emission reduction targets. This result is driven by a number of fourth Industrial Revolution technologies, such as the use of machine learning to dynamically optimize water cycle plant performance and detection of abnormal energy consumption prediction systems based on real-time operational data. These measures resulted in a 62% reduction in water consumption and a 51% reduction in energy consumption per PB of product.
