IJAT Vol.6 No.3 pp. 312-321
doi: 10.20965/ijat.2012.p0312


An Algorithmic Approach to Streamlining Product Carbon Footprint Quantification: A Case Study on Sheet Metal Parts

Ruisheng Ng, Zhiquan Yeo, Chee Wai Patrick Shi,
Fatida Rugrungruang, and Bin Song

Singapore Institute of Manufacturing Technology (SIMTech), 71 Nanyang Drive, Singapore 638075

January 8, 2012
April 11, 2012
May 5, 2012
carbon footprint (CFP), algorithmic approach, ssheet metal parts, sustainable manufacturing
Sustainable manufacturing is increasingly being recognized as the direction for technological innovation and implementation in industry. However, to measure and guide technology conceptualization, development, and deployment decisions, a quantifying indicator that is easy to understand is required. The carbon footprint (CFP) is found to be an effective indicator, as its value reflects essential elements of sustainability in manufacturing: materials, energy, and waste treatment. The existing standards provide a general framework to guide CFP quantification but lack explicit formulas for easy adoption. This paper presents an algorithmic approach that aims to granularize the emission source to streamline CFP quantification. This approach pinpoints the direct and indirect contributions and the respective task owners, decentralizes the responsibilities in data collection, and ascertains the degree of control to set realistic targets for CFP reductions. A case study is carried out in a manufacturer of sheet metal parts. Results show that indirect emissions from materials, energy, and transport collectively contribute 27% of product CFP.With the algorithmic approach, carbon reduction strategies can be formulated by setting priorities and realistic targets and then delegating to the task owners the reduction of the CFP of their respective areas. The current work establishes a base that can help companies to adopt CFP quantification and formulate carbon reduction strategies.
Cite this article as:
R. Ng, Z. Yeo, C. Shi, F. Rugrungruang, and B. Song, “An Algorithmic Approach to Streamlining Product Carbon Footprint Quantification: A Case Study on Sheet Metal Parts,” Int. J. Automation Technol., Vol.6 No.3, pp. 312-321, 2012.
Data files:
  1. [1] M. Hauschild , J. Jeswiet and L. Alting, “From life cycle assessment to sustainable production: status and perspectives,” CIRP Annals – Manufacturing Technology, Vol.54, pp. 1-21, 2005.
  2. [2] A. M. Deif, “A system model for green manufacturing,” Journal of Cleaner Production, Vol.19, pp. 1553-1559, 2011.
  3. [3] ISO 14040, “Environmental management – Life cycle assessment – Principles and framework,” International Standardization Organization, 2006.
  4. [4] ISO 14044, “Environmental management – Life cycle assessment – Requirements and guidelines,” International Standardization Organization, 2006.
  5. [5] H. Narita, H. Kawamura, T. Norishisa, L. Chen, H. Fujimoto, and T. Hasebe, “Development of prediction system for environmental burden for machine tool operation,” JSME International Journal, Vol.49, No.4, pp. 1188-1195, 2006.
  6. [6] IPCC, J. T. Houghton, Y. Ding, D. J. Griggs, M. Noguer, P. J. Van der Linden, K. Maskell, and C. A. Johnson, “Climate Change 2001: The scientific basis. Contribution of working Group I to third assessment report of the Intergovernmental Panel of Climate Change,” Cambridge University Press, 2001.
  7. [7] PAS 2050, “Specification for the assessment of the life cycle greenhouse gas emissions of goods and services,” British Standard International, 2011.
  8. [8] World Resource Institute, “Product Life Cycle Accounting and Reporting Standard,” 2011.
  9. [9] ISO/DIS 14067, “Carbon footprint of products - Requirements and guidelines for quantification and communication,” International Standardization Organization, 2011.
  10. [10] International Diary Federation, “A common carbon footprint approach for diary – The IDF guide to standard lifecycle assessment methodology for the diary sector,” Brussels, Belgium, 2012.
  11. [11] World Steel Association, “World Steel Association Life Cycle Inventory Study for Steel Products,” 2011.
  12. [12] G. P. Peters, “Efficient Algorithms for Life Cycle Assessment, Input-Output Analysis, and Monte-Carlo Analysis,” The International Journal of Life Cycle Assessment, 2007.
  13. [13] A. Bala, M. Raugei, G. Benveniste, C. Gazulla and P. Fullana-i-Palmer, “Simplified tools for global warming potential evaluation: when ‘good enough’ is best,” The International Journal of Life Cycle Assessment, 2009.
  14. [14] J.-G. Concepcion, K. Seungdo and R. O. Michael, “Methodology for Developing Gate-to-Gate Life Cycle Inventory Information,” The International Journal of Life Cycle Assessment, 2000.

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