Supporting Environmentally-Benign Design: Environmental Impact Estimation and Uncertainty Categories with Respect to Life Cycle Assessment in Conceptual Design

  • Shakuntala AcharyaEmail author
  • Amaresh Chakrabarti
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 66)


The goal of the conceptual design stage is to specify the solution principle, i.e., the concept; to design an environmentally-benign product, it is imperative that the most environmentally-benign concept is selected. However this selection can occur only upon evaluation of alternative solution-variants with respect to their potential environmental impacts. Life Cycle Assessment (LCA) is the most widely used approach to estimate environmental impacts of a product. However, at these early stages of design, information available on the lifecycle of the concepts is incomplete, subjecting LCA results to various sources of uncertainty. The environmental impact of a concept can thus be better gauged only upon considering the uncertainty in this estimation of impact. This paper proposes an uncertainty category called ‘solution-variant definition’, to be used in conceptual design, as a precursor to the more established uncertainty category called ‘structure definition’ for use at the embodiment design stage. It also elucidates that each sub-category of ‘solution-variant definition’ can be described using the ‘outcomes’ of the SAPPhIRE Model of Causality, and exhibits the same flow of causality. It is proposed that considering this uncertainty, along with other, more established uncertainties in Environmental Impact estimation, would support consideration of uncertainties in Conceptual design as opposed to only later in embodiment stages. This paper presents as to how decisions taken earlier could have a profound impact on the product with respect to its environmental-benignity.


Eco-design Design for sustainability Design creativity Synthesis Evaluation and optimisation Sapphire model of causality Environmental impact assessment Uncertainty 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Indian Institute of ScienceBangaloreIndia

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