Understanding sustainability data through unit manufacturing process representations: a case study on stone production

Published

May 24, 2016

Author(s)

Bjoern J. Johansson, Mahesh Mani, William Z. Bernstein, Kevin W. Lyons, KC Morris, Laurie Rebouillat, Ilaria Barletta

Abstract

Efficiency of natural stone production processes in quarries directly affects the economic output and environmental performances, such as production lead times and energy consumptions. Knowledge on stone production processes is crucial in making responsible decisions in this business. Having a structured representation of information characterizing the stone production processes will support stakeholders in better assessing production resources in terms of sustainability and productivity. Value stream mapping can provide an overview and guidance for sustainability performance evaluation, but its application is limited. The challenges arise when trying to specifically map and relate sustainability data between processes e.g., variability in lead time and CO2 emissions. Manufacturing process characterization standards currently being developed by ASTM International manifest the potential to not only fill this gap but also to provide opportunities to characterize and compose manufacturing processes with relevant environmental information and description. This paper shows the application and lessons learned from deploying one such effort towards standardization.

Proceedings Title

Procedia CIRP

Volume

57

Conference Dates

May 25-27, 2016

Conference Location

Stuttgart, DE

Conference Title

49th CIRP Conference on Manufacturing Systems

Pub Type

Conferences

Download Paper

https://doi.org/10.1016/j.procir.2016.11.119

Local Download

Keywords

Sustainable Production, Natural Stone Production, Unit Manufacturing Process, Composability, Quarrying, Standardization

Citation

Johansson, B. , Mani, M. , Bernstein, W. , Lyons, K. , Morris, K. , Rebouillat, L. and Barletta, I. (2016), Understanding sustainability data through unit manufacturing process representations: a case study on stone production, Procedia CIRP, Stuttgart, DE, [online], https://doi.org/10.1016/j.procir.2016.11.119, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=920324 (Accessed March 13, 2025)