DeltaLCA:电子设计生命周期比较评估

Zhihang Zhang, Felix Hähnlein, Yuxuan Mei, Zachary Englhardt, Shwetak Patel, Adriana Schulz, Vikram Iyer
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摘要

减少电子和计算设备的环境足迹需要新的工具,使设计人员能够在设计过程中就可持续发展做出明智的决定。目前的生命周期评估(LCA)工具无法做到这一点,因为这些工具需要大量的专业领域知识和时间来评估构成设备的众多芯片和其他组件。我们首先发现,明智的决策并不需要绝对的指标,而是可以通过比较设计来实现。其次,我们可以使用特定领域的启发式方法来进行这些比较。我们将这些见解结合起来,开发出了开源交互式设计工具 DeltaLCA,通过对电子设计进行比较分析,解决了自动生成生命周期清单和数据可用性的双重挑战。用户可以从电子设计自动化 (EDA) 软件上传标准设计文件,该工具将引导用户确定哪种设计的碳足迹更大。DeltaLCA 利用电子产品特有的生命周期评估数据集和启发式方法,自动对两种设计进行排序,仅在必要时提示用户提供额外信息。我们通过案例研究表明,DeltaLCA 可实现与评估完整生命周期评估相同的结果,而且它可加快生命周期评估比较的速度,对于约 30 个组件的设备,只需点击一下鼠标即可完成,而对于约 100 个组件的更复杂设备,只需点击一下鼠标即可完成。
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DeltaLCA: Comparative Life-Cycle Assessment for Electronics Design
Reducing the environmental footprint of electronics and computing devices requires new tools that empower designers to make informed decisions about sustainability during the design process itself. This is not possible with current tools for life cycle assessment (LCA) which require substantial domain expertise and time to evaluate the numerous chips and other components that make up a device. We observe first that informed decision-making does not require absolute metrics and can instead be done by comparing designs. Second, we can use domain-specific heuristics to perform these comparisons. We combine these insights to develop DeltaLCA, an open-source interactive design tool that addresses the dual challenges of automating life cycle inventory generation and data availability by performing comparative analyses of electronics designs. Users can upload standard design files from Electronic Design Automation (EDA) software and the tool will guide them through determining which one has greater carbon footprints. DeltaLCA leverages electronics-specific LCA datasets and heuristics and tries to automatically rank the two designs, prompting users to provide additional information only when necessary. We show through case studies DeltaLCA achieves the same result as evaluating full LCAs, and that it accelerates LCA comparisons from eight expert-hours to a single click for devices with ~30 components, and 15 minutes for more complex devices with ~100 components.
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