A conceptual tool for environmentally benign design: development and evaluation of a "proof of concept". Issue 1 (February 2020)

• Record Type: Journal Article
• Authors: Acharya, Shakuntala; Chakrabarti, Amaresh
• Is Part Of: AI EDAM. Volume 34:Issue 1(2020)
• Page Start: 30
• Page End: 44
• Publication Date: 2020-02
• Subjects: Conceptual stage of design, -- decision-making, -- design for sustainability, -- design tool, -- environmental impact assessment, -- SAPPhIRE model of causality; Engineering design -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; 620.00420285
• DOI: 10.1017/S0890060419000313
• Languages: English
• ISSNs: 0890-0604

Abstract

Abstract: Design is a decision-making process for which knowledge is a prerequisite. Most decisions are taken at the conceptual stage and have pronounced influence on the final design. The literature, therefore, recommends the incorporation of sustainability criteria, such as environment, at this stage. Difficulty in performing life cycle assessment (LCA) due to low availability of information at the conceptual stage for evaluation and highly abstract nature of solutions, inadequate incorporation of DfE (Design for Environment) guidelines and LCA reports into the design process, and a lack of effective communication of the same to the designers for prompt decision-making are major motivations for the development of a support. This paper discusses a " concep tual T ool for e nvironmentally benign design" – concepTe – that supports designers in decision-making during the conceptual design stage, by offering environmental impact (EI) estimates of abstract solutions with associated uncertainty, for evaluation and selection of the most environmentally benign solution as concept. The EI estimates are calculated by a module in the tool based on a proposed EI estimation method, which requires the support of a knowledge base to fetch appropriate LCA information corresponding to the design element being conceptualized. This knowledge base is grounded in the domain-agnostic SAPPhIRE model ontology, allows semantic operability of the knowledge, and offers the results to the designers in a familiar domain language to aid decision-making. A "proof of concept" of the tool is developed for application in design of building in the AEC (Architectural design, Engineering, and Construction) domain. Further, empirical studies are conducted to evaluate the effectiveness of the "proof of concept" to support decision-making and results are found favorable. The paper also discusses the future scope for further development of the tool into a holistic design decision-making platform.