ASSESSMENT OF ADDITIVE AND CONVENTIONAL MANUFACTURING: CASE STUDIES FROM THE AEC INDUSTRY

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Nataša Mrazovic ◽  
Danijel Mocibob ◽  
Michael Lepech ◽  
Martin Fischer
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Case Studies ◽  
Environmental Impacts ◽  
Assessment Process ◽  
Manufacturing Cost ◽  
Foreseeable Future ◽  
Assessment Approach ◽  
Building Components ◽  
Future Work

Given the development of Additive Manufacturing (AM), popularly known as 3D Printing, the coexistence of AM and conventional manufacturing (CM) in AEC will be a reality for the foreseeable future. Case studies on two AM metallic building components demonstrated that AM for building components is technologically feasible but cost-prohibitive today, and, in some cases, has lower environmental impacts than CM. Firstly, a feasibility study was conducted to assess the applicability, time to manufacture, and manufacturing cost of AM vs. CM of specific metallic building components. Secondly, Life Cycle Assessment (LCA) was used to assess environmental impacts of AM and CM for those two cases. The case studies were the first well-documented comparative analyses of AM vs. CM for building components, and they contribute to the emerging "AM-in-AEC" knowledge base with their assessment approach, findings and documented baseline efforts for the analyses. The studies also revealed that AEC practitioners lack a systematic way to rapidly and consistently assess the applicability (A), schedule (S), environmental impacts (E), and cost (C) of AM compared with CM to produce building components. Future work includes formalization of such an ASEC multi-criteria framework and impact assessment of the formalized assessment process on the effort and the consistency of the assessment between different assessors.

scholarly journals Exergy-Based Life Cycle Assessment of Buildings: Case Studies

2021 ◽  
Vol 13 (21) ◽  
pp. 11682
Author(s):  
Martin Nwodo ◽  
Chimay Anumba
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Case Studies ◽  
Environmental Impacts ◽  
Resource Use ◽  
Assessment Method ◽  
Comparison Of Results ◽  
Sustainability Assessments

The relevance of exergy to the life cycle assessment (LCA) of buildings has been studied regarding its potential to solve certain challenges in LCA, such as the characterization and valuation, accuracy of resource use, and interpretation and comparison of results. However, this potential has not been properly investigated using case studies. This study develops an exergy-based LCA method and applies it to three case-study buildings to explore its benefits. The results provide evidence that the theoretical benefits of exergy-based LCA as against a conventional LCA can be achieved. These include characterization and valuation benefits, accuracy, and enabling the comparison of environmental impacts. With the results of the exergy-based LCA method in standard metrics, there is now a mechanism for the competitive benchmarking of building sustainability assessments. It is concluded that the exergy-based life cycle assessment method has the potential to solve the characterization and valuation problems in the conventional life-cycle assessment of buildings, with local and global significance.

Environmental impacts of manure management based on life cycle assessment approach

2020 ◽  
Vol 264 ◽  
pp. 121576
Author(s):  
Jouni Havukainen ◽  
Sanni Väisänen ◽  
Tero Rantala ◽  
Minna Saunila ◽  
Juhani Ukko
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Environmental Impacts ◽  
Manure Management ◽  
Assessment Approach

scholarly journals How to Conduct Prospective Life Cycle Assessment for Emerging Technologies? A Systematic Review and Methodological Guidance

2020 ◽  
Vol 12 (3) ◽  
pp. 1192 ◽  
Author(s):  
Nils Thonemann ◽  
Anna Schulte ◽  
Daniel Maga
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Case Studies ◽  
Environmental Impacts ◽  
Emerging Technologies ◽  
Early Stage ◽  
Scale Up ◽  
Data Availability ◽  
Novel Technologies ◽  
Stage Of Development

Emerging technologies are expected to contribute to environmental sustainable development. However, throughout the development of novel technologies, it is unknown whether emerging technologies can lead to reduced environmental impacts compared to a potentially displaced mature technology. Additionally, process steps suspected to be environmental hotspots can be improved by process engineers early in the development of the emerging technology. In order to determine the environmental impacts of emerging technologies at an early stage of development, prospective life cycle assessment (LCA) should be performed. However, consistency in prospective LCA methodology is lacking. Therefore, this article develops a framework for a prospective LCA in order to overcome the methodological inconsistencies regarding prospective LCAs. The methodological framework was developed using literature on prospective LCAs of emerging technologies, and therefore, a literature review on prospective LCAs was conducted. We found 44 case studies, four review papers, and 17 papers on methodological guidance. Three main challenges for conducting prospective LCAs are identified: Comparability, data, and uncertainty challenges. The issues in defining the aim, functionality, and system boundaries of the prospective LCAs, as well as problems with specifying LCIA methodologies, comprise the comparability challenge. Data availability, quality, and scaling are issues within the data challenge. Finally, uncertainty exists as an overarching challenge when applying a prospective LCA. These three challenges are especially crucial for the prospective assessment of emerging technologies. However, this review also shows that within the methodological papers and case studies, several approaches exist to tackle these challenges. These approaches were systematically summarized within a framework to give guidance on how to overcome the issues when conducting prospective LCAs of emerging technologies. Accordingly, this framework is useful for LCA practitioners who are analyzing early-stage technologies. Nevertheless, further research is needed to develop appropriate scale-up schemes and to include uncertainty analyses for a more in-depth interpretation of results.

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