Evaluating the effectiveness of InDeaTe tool in supporting design for sustainability

Author:

Acharya ShakuntalaORCID,Ghadge Kiran,Ranjan B. S. C.,Devadula Suman,Chakrabarti Amaresh

Abstract

AbstractIn today's aggressive global market, innovation is key for success and design solutions require not only to achieve competitive edge, but also to address the growing environmental, social, and economic needs of the community at large. Consideration of these three pillars of sustainability makes a design inclusive, and life cycle thinking is found to be a promising approach across the literature. However, most supports for design address certain facets or aid singular tasks, and the use of design methods and tools, which have the potential to significantly improve the design process, is low due to inappropriate use and selection of these methods. InDeaTe (Innovation Design database and Template) is a holistic, knowledge-driven, computer-based tool for design of sustainable systems, such as products, manufacturing systems andservice systems and has been developed to address and integrate the aspects of sustainability on a singular design platform. It comprises of the generic design process Template that imbibes life cycle thinking into the process by incorporating consideration of every life cycle phase in each design stage, where design activities are performed iteratively. It further supports the design process by aiding the use and selection of appropriate design methods and tools in concurrence with the primary motivation of improving sustainability of the system with the aid of the InDeaTe Design Database. This paper discusses the ontological underpinnings behind the conceptualization of the InDeaTe methodology and the development of the supporting tool. The paper further reports empirical findings from six different case studies conducted for evaluating the effectiveness of InDeaTe tool in supporting design for sustainability (DfS). The results show that InDeaTe tool has potential in supporting DfS.

Publisher

Cambridge University Press (CUP)

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering

Reference57 articles.

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