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A conceptual tool for environmentally benign design: development and evaluation of a “proof of concept”

Published online by Cambridge University Press:  14 May 2020

Shakuntala Acharya Open the ORCID record for Shakuntala Acharya [Opens in a new window]  and
Amaresh Chakrabarti
Shakuntala Acharya*
Affiliation:
Centre for Product Design and Manufacturing, Indian Institute of Science (IISc), Bangalore560012, India
Amaresh Chakrabarti
Affiliation:
Centre for Product Design and Manufacturing, Indian Institute of Science (IISc), Bangalore560012, India
*
Author for correspondence: Shakuntala Acharya, E-mail: [email protected]; [email protected]
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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 “conceptual Tool for environmentally 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.

Keywords

Conceptual stage of designdecision-makingdesign for sustainabilitydesign toolenvironmental impact assessmentSAPPhIRE model of causality
Type
Research Article
Information
AI EDAM , Volume 34 , Issue 1: Thematic Collection on “Cognitive and Learning processes for transition to Design for Sustainability (DfS)” , February 2020 , pp. 30 - 44
Copyright
Copyright © Cambridge University Press 2020

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References

Acharya, S and Chakrabarti, A (2015) Supporting environmentally-benign design: elucidating environmental propagation in conceptual design by SAPPhIRE model of causality. Proceedings of International Conference on Engineering Design (ICED'15), Milan, Italy.Google Scholar
Acharya, S and Chakrabarti, A (2017) Supporting environmentally-benign design: environmental impact estimation and uncertainty categories with respect to life cycle assessment in conceptual design. International Conference on Research into Design. Singapore: Springer, pp. 3–18.CrossRefGoogle Scholar
Agudelo, LM, Nadeau, JP, Pailhes, J and Mejía-Gutiérrez, R (2017) A taxonomy for product shape analysis to integrate in early environmental impact estimations. International Journal on Interactive Design and Manufacturing (IJIDeM) 11, 397–413.CrossRefGoogle Scholar
Anand, CK and Amor, B (2017) Recent developments, future challenges and new research directions in LCA of buildings: a critical review. Renewable and Sustainable Energy Reviews 67, 408–416.CrossRefGoogle Scholar
Antón, LÁ and Diaz, J (2014) Integration of life cycle assessment in a BIM environment. Procedia Engineering 85, 26–32.CrossRefGoogle Scholar
Asimow, M (1962) Introduction to Design. Prentice-Hall. Inc., Englewood Cliffs, NJ.Google Scholar
Athena Institute. EcoCalculator. Ontario, Canada. Available at www.athenasmi.org.Google Scholar
Bhamra, TA, Evans, S, McAloone, TC, Simon, M, Poole, S and Sweatman, A (1999) Integrating environmental decisions into the product development process. I. The early stages. Proceedings EcoDesign'99: First International Symposium on Environmentally Conscious Design and Inverse Manufacturing. IEEE, pp. 329–333.Google Scholar
Blessing, LTM (1994) A Process-Based Approach to Computer-Supported Engineering Design. Enschede: University of Twente.Google Scholar
Borkowski, A, Fleischmann, N and Bletzinger, KU (1993) Supporting conceptual decisions in structural design. Computing Systems in Engineering 4, 223–234.CrossRefGoogle Scholar
Bras, B (1997) Incorporating environmental issues in product design and realization. Industry and Environment 20, 7–13.Google Scholar
BRE Group. BREEAM. Watford, UK. Available at www.bre.co.uk.Google Scholar
BRE Group. Envest 2. Watford, UK. Available at www.bre.co.uk.Google Scholar
Bribián, IZ, Usón, AA and Scarpellini, S (2009) Life cycle assessment in buildings: state-of-the-art and simplified LCA methodology as a complement for building certification. Building and Environment 44, 2510–2520.CrossRefGoogle Scholar
Brown, MT and Bardi, E (2001) Handbook of emergy evaluation. A compendium of data for emergy computation issued in a series of folios Folio, 3..Google Scholar
Building and Fire Research Laboratory, BFRL. BEES 3.0. Available at www.bfrl.nist.gov/oae/software/bees.html.Google Scholar
Burnette, Charles and Associates (1979) “The Architect's Access to Information” NTIS # PB 294855 and “Making Information Useful to Architects — An Analysis and Compendium of Practical Forms for the Delivery of Information” NTIS # PB 292782. Washington, DC: U.S. Department of Commerce National Technical Information Service.Google Scholar
Cabeza, LF, Rincón, L, Vilariño, V, Pérez, G and Castell, A (2014) Life cycle assessment (LCA) and life cycle energy analysis (LCEA) of buildings and the building sector: a review. Renewable and Sustainable Energy Reviews 29, 394–416.CrossRefGoogle Scholar
Carrara, G, Fioravanti, A, Novembri, G and Dpt Architettura e Urbanistica (2001) Knowledge-based system to support architectural design. Architectural Information Management, Proceedings of eCAADe 01 Conference, pp. 29–31.Google Scholar
Castro-Lacouture, D, Quan, SJ and Yang, PPJ (2014) GIS-BIM framework for integrating urban systems, waste stream and algal cultivation in residential construction. In ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction Vol. 31, p. 1. IAARC Publications.CrossRefGoogle Scholar
Chakrabarti, A, Johnson, A and Kiriyama, T (1997) An approach to automated synthesis of solution principles for micro-sensor designs. Proceedings of the International Conference in Engineering Design, Tampere, Vol. 2, pp. 125–128.Google Scholar
Chakrabarti, A, Sarkar, P, Leelavathamma, B and Nataraju, BS (2005) A functional representation for aiding biomimetic and artificial inspiration of new ideas. Ai Edam 19, 113–132.Google Scholar
Council, U.S.G.B. (2008) LEED rating systems. Available at www.usgbc.org/articles/about-leed.Google Scholar
CPIC (2013) Uniclass2 (Development Release) Classification Tables. Retrieved November 2013, from CPIC: http://www.cpic.org.uk/uniclass2/.Google Scholar
Cross, N (2000) Engineering Design Methods — Strategies for Product Design. Chichester, UK: John Wiley and Sons Ltd.Google Scholar
CSI (2012) UniFormat. Retrieved November 2013, from CSI: http://www.csinet.org/uniformat.Google Scholar
CSI and CSC (2004) MasterFormat 2004 Edition Numbers and Titles. The Construction Specifications Institute (CSI) and Construction Specifications Canada (CSC).Google Scholar
CSI and CSC (2010) UniFormat a Uniform Classification of Construction Systems and Assemblies. CSI and CSC.Google Scholar
Devanathan, S, Ramanujan, D, Bernstein, WZ, Zhao, F and Ramani, K (2010) Integration of sustainability into early design through the function impact matrix. Journal of Mechanical Design 132, 081004.CrossRefGoogle Scholar
Dewulf, W and Duflou, J (2003) ECO-PAS — estimating the environmental performance of conceptual designs using parametric modelling. International Conference on Engineering Design, ICED, Vol. 3.Google Scholar
Dewulf, W and Duflou, J (2006) A web based application for the ECO-PAS tool. CIRP-13th International Conference on Life Cycle Engineering, Leuven, Belgium, Vol. 1, pp. 143–147.Google Scholar
Ding, GKC (2014) Life cycle assessment (LCA) of sustainable building materials: an overview. Eco-efficient construction and building materials. In Life Cycle Assessment (LCA) Eco-Labelling and Case Studies. Cambridge: Woodhead Publishing Limited, pp. 38–62.Google Scholar
Dorst, K and Cross, N (2001) Creativity in the design process: co-evolution of problem–solution. Design Studies 22, 425–437.CrossRefGoogle Scholar
Fenves, SJ, Flemming, U, Hendrickson, C, Maher, ML and Schmitt, G (1990) Integrated software environment for building design and construction. Computer-Aided Design 22, 27–36.CrossRefGoogle Scholar
Fitzgerald, DP, Herrmann, JW, Sandborn, PA, Schmidt, LC and Gogoll, TH (2005) Beyond tools: a design for environment process. International Journal of Performability Engineering 1, 105–120.Google Scholar
Fitzgerald, DP, Herrmann, JW and Schmidt, LC (2010) A conceptual design tool for resolving conflicts between product functionality and environmental impact. Journal of Mechanical Design 132, 091006.CrossRefGoogle Scholar
Florez, L and Castro-Lacouture, D (2013) Optimization model for sustainable materials selection using objective and subjective factors. Materials and Design 46, 310–321.CrossRefGoogle Scholar
Franzoni, E (2011) Materials selection for green buildings: which tools for engineers and architects? Procedia Engineering 21, 883–890.CrossRefGoogle Scholar
French, M (1999) Conceptual Design for Engineers, 3rd Edn.London, UK: Springer-Verlag.CrossRefGoogle Scholar
Gero, JS (1989) A Locus for Knowledge-Based Systems in CAAD Education.Google Scholar
Gero, JS (1990) Design prototypes: a knowledge representation schema for design. AI Magazine 11, 26.Google Scholar
Gero, JS and Maher, ML (1988) Future Roles of Knowledge-Based Systems in the Design Process.Google Scholar
Haapio, A and Viitaniemi, P (2008) A critical review of building environmental assessment tools. Environmental Impact Assessment Review 7, 469–482.CrossRefGoogle Scholar
Handfield, RB, Melnyk, SA, Calantone, RJ and Curkovic, S (2001) Integrating environmental concerns into the design process: the gap between theory and practice. IEEE Transactions on Engineering Management 48, 189–208.CrossRefGoogle Scholar
Harputlugil, T, Gültekin, AT and Prins, M (2011) Conceptual framework for potential implementations of multi criteria decision making (MCDM) methods for design quality assessment. Proceedings of the international Conference on Management and Innovation for a Sustainable Built Environment, Amsterdam, The Netherlands.Google Scholar
Hawken, P, Lovins, A and Lovins, LH (1999) Natural Capitalism: Creating the Next Industrial Revolution. Boston: Little Brown, pp. 369.Google Scholar
Hazelrigg, GA (1998) A framework for decision-based engineering design. ASME Journal of Mechanical Design 120, 653–658.CrossRefGoogle Scholar
Heeren, N, Mutel, CL, Steubing, B, Ostermeyer, Y, Wallbaum, H and Hellweg, S (2015) Environmental impact of buildings what matters? Environmental Science & Technology 49, 9832–9841.CrossRefGoogle ScholarPubMed
Hofstetter, P, Lippiatt, BC, Bare, JC and Rushing, AS (2002) User Preferences for Life-Cycle Decision Support Tools: Evaluation of a Survey of BEES Users. NIST. Available at http:// www.bfrl.nist.gov/oae/software/bees.html.10.6028/NIST.IR.6874CrossRefGoogle Scholar
Hubka, V and Eder, WE (1996) Introduction to the needs, scope and organization of engineering design knowledge. In: Design Science. London and Berlin/Heidelberg: Springer-Verlag http://deed.ryerson.ca/DesignScience.CrossRefGoogle Scholar
ISO 14040: 2006 Environmental Management – Life Cycle Assessment – Principles and Framework. Brussels: CEN (European Committee for Standardisation).Google Scholar
ISO 14044: 2006 Environmental Management – Life Cycle Assessment – Requirements and Guidelines. Brussels: CEN (European Committee for Standardisation).Google Scholar
Kemper, LE, Wei, C and Linda, SC (2006) Decision Making in Engineering Design. New York: ASME, Chap. 2–3; [2].Google Scholar
Kihlander, I (2009) Decision making in concept phases towards improving product development processes (Licentiate Doctoral thesis). KTH. ISBN 978-91-7415-375-0.Google Scholar
Kitamura, Y (2006) Roles of ontologies of engineering artifacts for design knowledge modeling. In: Design Methods for Practice.Google Scholar
Kitamura, Y, Sano, T, Namba, K and Mizoguchi, R (2002) A functional concept ontology and its application to automatic identification of functional structures. Advanced Engineering Informatics 16, 145–163.CrossRefGoogle Scholar
Kitamura, Y, Kashiwase, M, Fuse, M and Mizoguchi, R (2004) Deployment of an ontological framework of functional design knowledge. Advanced Engineering Informatics 18, 115–127.CrossRefGoogle Scholar
König, M, Dirnbek, J and Stankovski, V (2013) Architecture of an open knowledge base for sustainable buildings based on linked data technologies. Automation in Construction 35, 542–550.CrossRefGoogle Scholar
Kota, S and Chakrabarti, A (2010) A method for estimating the degree of uncertainty with respect to life cycle assessment during design. Journal of Mechanical Design (ASME) 132, 091007/1-9.Google Scholar
Kraus, R and Myer, J (1970) Design: a case history and specification for a computer system. In Moore, G (ed.), Emerging Methods in Environmental Design and Planning. Cambridge, MA: MIT Press.Google Scholar
Krishnan, V and Ulrich, KT (2001) Product development decisions: a review of the literature. Management Science 47, 1–21.CrossRefGoogle Scholar
Lindahl, M (2003) Designer's utilization of DfE methods. 1st International Workshop on Sustainable Consumption, Tokyo.Google Scholar
Lombera, JTSJ and Rojo, JC (2010) Industrial building design stage based on a system approach to their environmental sustainability. Construction and Building Materials 24, 438–447.CrossRefGoogle Scholar
Luttropp, C and Lagerstedt, J (2006) EcoDesign and The Ten Golden Rules: generic advice for merging environmental aspects into product development. Journal of Cleaner Production 14, 1396–1408.CrossRefGoogle Scholar
Manago, C and Gero, JS (1987) Some aspects of the communication between expert systems and a CAD model. Working Paper.Google Scholar
March, JG (1997) Understanding how decisions happen in organizations. Organizational Decision Making 10, 9–32.Google Scholar
Mizoguchi, R (2004) Tutorial on ontological engineering - Part 1, 2, 3. New Generation Computing 21, 365–384. 22(1), 2004, pp. 61–96, 22(2), pp. 193–220.CrossRefGoogle Scholar
Montelisciani, G, Gabelloni, D and Fantoni, G (2015) Developing integrated sustainable product-process-service systems at the early product design stages. International Journal of Sustainable Manufacturing 3, 310–332.CrossRefGoogle Scholar
Najjar, M, Figueiredo, K, Palumbo, M and Haddad, A (2017) Integration of BIM and LCA: evaluating the environmental impacts of building materials at an early stage of designing a typical office building. Journal of Building Engineering 14, 115–126.CrossRefGoogle Scholar
Neufert, E, Neufert, P and Kister, J (2012) Architects’ Data. John Wiley & Sons.Google Scholar
OmniClass, A (2006) Strategy for classifying the built environment.Google Scholar
O'Shea, MA (2002) Design for Environment in conceptual product design – a decision model to reflect environmental issues of all life-cycle phases. The Journal of Sustainable Product Design 2, 11–28.CrossRefGoogle Scholar
Pahl, G and Beitz, W (1996) Engineering Design: A Systematic Approach. UK: Springer-Verlag.CrossRefGoogle Scholar
PE Int′l. GaBi. Available at www.gabi-software.com/support/gabi/gabi-lcia-documentation/traci-21.Google Scholar
PRé Consultants. SimaPro. Amersfoort, The Netherlands. Available at ww.pre-sustainability.com/Simapro/.Google Scholar
Pugh, S (1991) Total Design: Integrated Methods for Successful Product Engineering. Addison-Wesley.Google Scholar
Ramesh, T, Prakash, R and Shukla, KK (2010) Life cycle energy analysis of buildings: an overview. Energy and Buildings 10, 1592–600.CrossRefGoogle Scholar
Ritzén, S (2000) Integration Environmental Aspects into Product Development: Proactive Measures (Doctoral dissertation). KTH.Google Scholar
Roozenburg, NF and Eekels, J (1995) Product Design: Fundamentals and Methods, Vol. 2. Chichester: Wiley.Google Scholar
Rosenman, MA and Gero, JS (1985) Design codes as expert systems. Computer-Aided Design 17, 399–409.CrossRefGoogle Scholar
Sartori, I and Hestnes, AG (2007) Energy use in the life cycle of conventional and low-energy buildings: a review article. Energy and Buildings 3, 249–257.CrossRefGoogle Scholar
Sigel, K, Klauer, B and Pahl-Wostl, C (2010) Conceptualising uncertainty in environmental decision-making: the example of the EU water framework directive. Ecological Economics 69, 502–510.CrossRefGoogle Scholar
Srinivasan, V and Chakrabarti, A (2010 a) An integrated model of designing. ASME Journal of Computing and Information Science in Engineering (JCISE), 10, 031013. in Special Issue on Knowledge Based Design, ed. by Ashok K. Goel and Andrés Gómez de Silva Garza.CrossRefGoogle Scholar
Srinivasan, V and Chakrabarti, A (2010 b) Investigating novelty-outcome relationships in engineering design. AI EDAM 24, 161–178.CrossRefGoogle Scholar
Stone, R and McAdams, ZSDA (2001) Mathematizing the Conceptual Design Phase: A Concept Generator Based on an Empirical Study. Rolla, MO: University of Missouri.Google Scholar
Stone, R and Wood, KL (2000) Development of a functional basis for design. Journal of Mechanical Design 122, 359–370CrossRefGoogle Scholar
Takano, A, Winter, S and Hughes, M (2014) Comparison of life cycle assessment databases for building assessment. OSB 615(210), 196Google Scholar
The Quartz Common Products Database. Available at www.quartzproject.org/p/CP042-a03.Google Scholar
Tinkleman, M (2015) ASME Sustainable Products and Processes Strategic Plan. NIST.Google Scholar
Trusty, W and Horst, S (2005) LCA tools around the world. Building Design and Construction, 12–16Google Scholar
Ullman, DG (1997) The Mechanical Design Process. New York: McGraw-Hill.Google Scholar
Ullman, DG (2003) The Mechanical Design Process. New York: McGraw-Hill.Google Scholar
Uschold, M and Jasper, R (1999) A framework for understanding and classifying ontology applications. In Proc. of the IJCAI99 Workshop onOntologies and Problem-Solving Methods.Google Scholar
Wall, S and Wimmers, G (2018) A comparative life cycle assessment: the design of a high performance building envelope and the impact on operational and embodied energy. World Academy of Science, Engineering and Technology, International Journal of Architectural and Environmental Engineering 5.Google Scholar
Watson, D (2004) Time-Saver Standards for Architectural Design.Google Scholar
Wiggins, GE (1989) Methodology in Architectural Design (Doctoral dissertation). Massachusetts Institute of Technology.Google Scholar
Wood, KL and Greer, JL (2001) Function-based synthesis methods in engineering design. Formal Engineering Design Synthesis, 170–227.CrossRefGoogle Scholar
Yoshioka, M, Umeda, Y, Takeda, H, Shimomura, Y, Nomaguchi, Y and Tomiyama, T (2004) Physical concept ontology for the knowledge intensive engineering framework. Advanced Engineering Informatics 18, 95–113.CrossRefGoogle Scholar