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

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.