How to Simplify Life Cycle Assessment for Industrial Applications-A Comprehensive Review

Life cycle assessment (LCA) has established itself as the dominant method for identifying the environmental impact of products or services. However, conducting an LCA is labor and time intensive (especially regarding data collection). This paper, therefore, aims to identify methods and tools that enhance the practicability of LCA, especially with regard to product complexity and variance. To this end, an initial literature review on the LCA of complex products was conducted to identify commonly cited barriers and potential solutions. The obtained information was used to derive search strategies for a subsequent comprehensive and systematic literature review of approaches that address the identified barriers and facilitate the LCA process. We identified five approaches to address the barriers of time and effort, complexity, and data intensity. These are the parametric approach, modular approach, automation, aggregation/grouping, and screening. For each, the concept as well as the associated advantages and disadvantages are described. Especially, the automated calculation of results as well as the automated generation of life cycle inventory (LCI) data exhibit great potential for simplification. We provide an overview of common LCA software and databases and evaluate the respective interfaces. As it was not considered in detail, further research should address options for automated data collection in production by utilizing sensors and intelligent interconnection of production infrastructure as well as the interpretation of the acquired data using artificial intelligence.

Automated summary

Life cycle assessment (LCA) is the dominant method for assessing the environmental impact of products or services, but it is labor and time intensive. This study aims to enhance the practicality of LCA for complex products by identifying methods and tools. Five approaches were identified, including the parametric approach, modular approach, automation, aggregation/grouping, and screening, each with their advantages and disadvantages. Automated calculation of results and generation of life cycle inventory (LCI) data show potential for simplification. Additionally, further research is needed to explore automated data collection using sensors and artificial intelligence interpretation.