Abstract
Environmental concern requires manufacturers to extend the domain of their control and responsibility across the product’s life cycle. Much of the research has concentrated on assessment of environmental performance through the application of the Life Cycle Assessment (LCA) framework that provides a technical methodology to help identification of environmental impacts of product systems. However, the current LCA framework does not incorporate dynamic and diverse characteristics of manufacturing processes. As a result, the LCA’s referential data will largely deviate from the real ones to an extent that the purpose of LCA is not meaningful. In other words, the current and fixed referential data-based method is not suitable to specify the impact categories related to manufacturing processes. From the perspective of decision making related with environmental impact during manufacturing, the current LCA method carried out in the off-line is hard to apply. As a result, performance index, such as greenability, a major performance index for environment conscious manufacturing cannot be implemented in the real practice. This paper presents the development of a framework (called process-oriented LCA) to realize environmental conscious manufacturing incorporating both greenability and productivity. To show the applicability and validity of this framework, experiments and analysis have been conducted and a prototype system has been implemented for a turning machining process.
We’re sorry, something doesn't seem to be working properly.
Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.
References
APO. (2006). Handbook on green productivity. Cober Printing Limited. http://www.apo-tokyo.org/publications/wp-content/uploads/sites/5/gp-hb_gp.pdf. Accessed June 23, 2009.
Bonvoisin, J., Thiede, S., Brissaud, D., & Herrmann, C. (2013). An implemented framework to estimate manufacturing-related energy consumption in product design. International Journal of Computer Integrated Manufacturing, 26(9), 866–880.
Box, G., & Behnken, D. (1960). Some new three level designs for the study of quantitative variables. Technometrics, 2, 455–475.
Choudhury, S. K., & Kishore, K. K. (2000). Tool wear measurement in turning using force ratio. International Journal of Machine Tools and Manufacture, 40, 899–909.
Duflou, J., Kellens, K., & Dewulf, W. (2011). Unit process impact assessment for discrete part manufacturing: A state of the art. CIRP Journal of Manufacturing Science and Technology, 4, 129–135.
Famili, F. (1994). Use of decision-tree induction for process optimization and knowledge refinement of an industrial process. Journal of Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 8(1), 63–75.
Frischknecht, R., Jungbluth, N., Althaus, H., Doka, G., Dones, R., Hischier, R., et al. (2007). Eco-invent: Overview and methodology. Swiss Centre for Life Cycle Inventories. http://www.ecoinvent.org/fileadmin/documents/en/01_OverviewAndMethodology.pdf. Accessed June 21, 2009.
Goedkoop, M., & Spriensma, R. (2001). The eco-indicator 99—A damage oriented method for life cycle impact assessment. Pre Consultants. http://www.pre-sustainability.com/download/misc/EI99_annexe_v3.pdf. Accessed June 16, 2009.
Goedkoop, M., Heijungs, R., Huijbregts, M., Schryver, A., Struijs, J., & Zelm, R. (2013). ReCiPe 2008: A life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level. Pre Consultants. http://www.leidenuniv.nl/cml/ssp/publications/recipe_characterisation_addenum.pdf. Accessed August 8, 2009.
Guinee, J., Gorree, M., Heijungs, R., Huppes, G., Kleijin, R., Koniq, A., et al. (2001). Life Cycle Assessment—An operational guide to the ISO standards. Leiden University. http://media.leidenuniv.nl/legacy/new-dutch-lca-guide-part-1.pdf. Accessed August 8, 2009.
Gungor, A., & Gupta, S. M. (1999). Issues in environmentally conscious manufacturing and product recovery: A survey. Computers & Industrial Engineering, 36(4), 811–853.
Hur, T., Kim, I., & Yamamoto, R. (2004). Measurement of green productivity and its improvement. Journal of Cleaner Production, 12, 673–683.
Iqbal, A., Zhang, H. C., Kong, L. L., & Hussain, G. (2013). A rule-based system for trade-off among energy consumption, tool life, and productivity in machining process. Journal of Intelligent manufacturing. doi:10.1007/s10845-013-0851-x.
ISO. (2000). ISO14043: Environmental management—Life Cycle Assessment—Life cycle interpretation. Geneva: International Standards Organization.
ISO. (2006). ISO14040: Environmental Management—Life Cycle Assessment—Principles and framework. Geneva: International Standards Organization.
Jia, S., Tang, R., & Lv, J. (2014a). Therblig-based energy demand modeling methodology of machining process to support intelligent manufacturing. Journal of Intelligent Manufacturing, 25(5), 913–931.
Jia, S., Tang, R., & Lv, J. (2014b). Machining activity extraction and energy attributes inheritance method to support intelligent energy estimation of machining process. Journal of Intelligent Manufacturing. doi:10.1007/s10845-014-0894-7.
Jiang, P., Jia, F., Wang, Y., & Zheng, M. (2014). Real-time quality monitoring and predicting model based on error propagation networks for multistage machining processes. Journal of Intelligent Manufacturing, 25(3), 521–538.
Jiang, Z., Zhang, H., & Sutherland, J. (2012). Development of an environmental performance assessment method for manufacturing process plans. International Journal of Advanced Manufacturing Technology, 58, 783–790.
Kellens, K., Dewulf, W., Overcash, M., Hauschild, M. Z., & Duflou, J. R. (2012). Methodology for systematic analysis and improvement of manufacturing unit process Life-Cycle Inventory (UPLCI)—CO2PE! Initiative (cooperative effort on process emissions in manufacturing). Part 1: Methodology description. International Journal of Life Cycle Assessment, 17, 69–78.
KNIME. (2015). Konstanz information miner. http://www.knime.org/. Accessed February 2, 2015.
Krause, M., Thiede, S., Herrmann, C., & Butz, F. F. (2012). A material and energy flow oriented method for enhancing energy and resource efficiency in aluminum foundries. In Proceedings of the 19th CIRP conference on Life Cycle Engineering (pp. 281–286).
Kuei, C., & Madu, C. (2003). Customer-centric six sigma quality and reliability management. International Journal of Quality & Reliability Management, 20(8), 954–964.
Le, T. P. N., & Lee, T. R. (2013). Model selection with considering the CO2 emission alone the global supply chain. Journal of Intelligent Manufacturing, 24(4), 653–672.
Lehtinen, H., Saarentaus, A., Rouhiainen, J., Pitts, M., & Azapagic, A. (2011). A review of LCA methods and tools and their suitability for SMEs. Europe Innova Eco-Innovation Bio Chem. http://www.biochem-project.eu/download/toolbox/sustainability/01/120321%20BIOCHEM%20LCA_review.pdf. Accessed January 17, 2014.
Li, C., Tang, Y., Cui, L., & Li, P. (2013). A quantitative approach to analyze carbon emissions of CNC-based machining systems. Journal of Intelligent Manufacturing. doi:10.1007/s10845-013-0812-4.
Mélanie, D., Oates, M. R., & Ball, P. D. (2013). Sustainable manufacturing tactics and cross-functional factory. Journal of Cleaner Production, 42, 31–41.
Mukherjee, I., & Ray, P. K. (2006). A review of optimization techniques in metal cutting processes. Computers & Industrial Engineering, 50, 15–34.
NIST. (2014). Engineering statistics handbook. http://www.itl.nist.gov/div898/handbook/. Accessed July 12, 2014.
Peng, T., & Xu, X. (2014). A holistic approach to achieving energy efficiency for interoperable machining systems. International Journal of Sustainable Engineering, 7(2), 111–129.
Rebitzer, G., Ekvall, T., Frischknecht, R., Hunkeler, D., Norris, G., Rydberg, T., et al. (2004). Review—Life Cycle Assessment Part 1: Framework, goal and scope definition, inventory analysis, and applications. Environment International, 30, 701–720.
Shao, G., Brodsky, A., Shin, S. J., & Kim, D. B. (2014). Decision guidance methodology for sustainable manufacturing using process analytics formalism. Journal of Intelligent Manufacturing. doi:10.1007/s10845-014-0995-3.
Suh, S. H., Chung, D. H., Lee, B. E., Shin, S. J., Choi, I. J., & Kim, K. M. (2006). STEP-compliant CNC system for turning: Data model, architecture, and implementation. Computer-Aided Design, 38, 677–688.
Suh, S. H., Shin, S. J., Yoon, J. S., & Um, J. M. (2008). UbiDM: A new paradigm for product design and manufacturing via ubiquitous computing technology. International Journal of Computer Integrated Manufacturing, 21(5), 540–549.
Tangen, S. (2004). Performance measurement: From philosophy to practice. International Journal of Productivity and Performance Management, 53(8), 726–737.
Winter, M., Li, W., Kara, S., & Herrmann, C. (2013). Stepwise approach to reduce the costs and environmental impacts of grinding processes. International Journal of Advanced Manufacturing Technology, 71(5–8), 919–931.
Zein, A., Li, W., Herrmann, C., & Kara, S. (2011). Energy efficiency measures for the design and operation of machine tools: An axiomatic approach. In Proceedings of the 18th CIRP Conference on Life Cycle Engineering (pp. 274–279).
Acknowledgments
This research was in part supported by the International Research and Development Program funded by the Ministry of Education, Science and Technology (MEST) of Korea (Grant number: K21003001750-12B1300-03610) and the Korea Institute for Advancement of Technology (KIAT) grant funded by the Ministry of Trade Industry and Energy (MOTIE) of Korea. (2014 Establishment of GEM, Grant Number: H2001-13-1001).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Shin, SJ., Suh, SH., Stroud, I. et al. Process-oriented Life Cycle Assessment framework for environmentally conscious manufacturing. J Intell Manuf 28, 1481–1499 (2017). https://doi.org/10.1007/s10845-015-1062-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10845-015-1062-4