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面向基于标准生成用于制造过程的可重复使用的生命周期清单数据模型

Towards Standards-Based Generation of Reusable Life Cycle Inventory Data Models for Manufacturing Processes.

作者信息

Brundage Michael P, Lechevalier David, Morris K C

机构信息

National Institute of Standards and Technology Systems Integration Division Gaithersburg, MD 20814.

Engisis LLC Bethesda, MD, 20817.

出版信息

J Manuf Sci Eng. 2019 Feb;141(2). doi: 10.1115/1.4041947.

Abstract

The production stage of a product's life cycle can significantly contribute to its overall environmental impact. Estimates of environmental impact for a product are typically produced using Life Cycle Assessment (LCA) methods. These methods rely on Life Cycle Inventory (LCI) data containing impact estimates of manufacturing processes and other operations that contribute to a product's creation. The accuracy of LCI data is critical for quality assessments; however, this data is often insufficient in the types and varieties of manufacturing processes covered and is often only a coarse estimate of actual impacts. At the same time, much manufacturing research focuses on how to model, measure, assess, and reduce the environmental impacts of manufacturing processes. Recent standards emerging from ASTM International define a structured format for presenting these studies in a reusable way. In this paper, we investigate the potential for using the ASTM E3012-16 format to generate LCI datasets suitable to perform LCA by mapping from the ASTM standard into the widely-adopted ecoSpold2 format. A process is presented for generating LCI datasets from ASTM models, and overlaps and gaps between the two standards are identified.

摘要

产品生命周期的生产阶段会对其整体环境影响产生重大作用。产品环境影响的评估通常采用生命周期评估(LCA)方法。这些方法依赖于生命周期清单(LCI)数据,该数据包含对制造过程及其他有助于产品形成的运营的影响评估。LCI数据的准确性对于质量评估至关重要;然而,该数据在所涵盖的制造过程的类型和种类方面往往不足,且通常只是对实际影响的粗略估计。与此同时,许多制造研究聚焦于如何对制造过程的环境影响进行建模、测量、评估和减少。美国材料与试验协会国际组织(ASTM International)最近出台的标准定义了一种结构化格式,以便以可重复使用的方式呈现这些研究。在本文中,我们通过将ASTM标准映射到广泛采用的ecoSpold2格式,研究使用ASTM E3012 - 16格式生成适用于执行LCA的LCI数据集的潜力。本文提出了一种从ASTM模型生成LCI数据集的过程,并确定了这两种标准之间的重叠和差距。

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