Application of the Pentagonal W-Eco Model for Manufacturing Based on “SDGs”
1
Department of Mechanical Engineering, Nagaoka University of Technology, Japan
2
School of Engineering, Sanjyo City University, Japan
Submission date: 2021-09-27
Final revision date: 2022-01-12
Acceptance date: 2022-01-12
Online publication date: 2022-01-25
Publication date: 2022-03-30
Corresponding author
Ikuo Tanabe
Mechanical Engineering, Nagaoka University of Technology, 1603-1 Kamitomioka, Nagaoka, Niigata, 940-2188, Nagaoka, Japan
Mechanical Engineering, Nagaoka University of Technology, 1603-1 Kamitomioka, Nagaoka, Niigata, 940-2188, Nagaoka, Japan
Journal of Machine Engineering 2022;22(1):25–42
KEYWORDS
TOPICS
ABSTRACT
In this study, the manufacturing in response to the 17 goals and the 169 targets of the SDGs is considered, and the application of the pentagonal W-ECO model for manufacturing based on the SDGs was proposed. First, the current situation of manufacturing was considered from an environmental perspective, which is also important for the SGDs. Then three cases of development for environmental conservation were introduced to understand the current situation, and it was confirmed that they can contribute to the achievement of SDGs, however the degree of their contribution couldn’t be evaluated quantitatively. Finally, the previous three cases using the proposed pentagonal W-ECO model quantitatively evaluated, and confirmed that the results of the evaluation provide a quantitative indicator for achieving the SDGs. As a result, the effectiveness of the pentagonal W-ECO model for manufacturing based on SDGs is evaluated.
REFERENCES (35)
1.
Ministry of Foreign Affairs, Retrieved on February 19th 2021, https://www.mofa.go.jp/mofaj/g... index.html.
3.
MARINOVA D., ANNANDALE D., PHILLIMORE J., 2006, The International Handbook on Environmental Technology Management, Edward Elgar Publishing, Inc., United Kingdom.
4.
TANABE I., 2016, Double-ECO Model Technologies for and Environmentally Friendly Manufacturing, Procedia CIRP: 23rd CIRP Conference on Life Cycle Engineering, 48, 495–501.
5.
SALING P., KICHERER A., DITTRICH-KRÄMER B., et al., 2002, Eco-Efficiency Analysis by BASF: The Method, The International Journal of Life Cycle Assessment, 7/4, 203–218.
6.
TANABE I., 2017, Consideration Regarding Environmentally-friendly in Manufacturing Field, Proceedings of the 2nd World Congress on Civil, Structural and Environmental Engineering (CSEE-17), ICESDP 104, 1–10.
7.
PENA-GONZALEZ L.E., DA SILVA P., TANABE I., 2018, Development of Environmentally Friendly Technolo-gies Based on Double Eco Model – An Evaluation Platform, Journal of Machine Engineering, 18/1, 18–31.
8.
LABIDI A., TANABE I., TAKAHASHI S., 2021, A Study on Extending Technologies Lifespan for the Environment Safety, Journal of Machine Engineering, 21/1, 109–120.
9.
MOURTZIS D., DOUKAS., M., 2014, The Evolution of Manufacturing Systems: From Craftsmanship to the Era of Customization, Handbook of Research on Design and Management of Lean Production Systems, IGI Global, 1–29.
10.
ELMARAGHY H., MONOSTORI L., SCHUH G., ELMARAGHY W., 2021, Evolution and Future of Manufacturing Systems, CIRP Annals, 70/2, 635–658.
11.
DIMITRIS M., 2020, Simulation in the Design and Operation of Manufacturing Systems: State of The Art and New Trends, International Journal of Production Research, 58/7, 1927–1949,.
12.
FOIVOS P., GÖKAN M., PAUL-ARTHUR D., DIMITRIS K., 2020, Zero Defect Manufacturing: State-of-The-Art Review, Shortcomings and Future Directions in Research, International Journal of Production Research, 58/1, 1–17.
13.
MOURTZIS D., ANGELOPOULOS J., PANOPOULOS N., 2021, Equipment Design Optimization Based on Digital Twin Under the Framework of Zero-Defect Manufacturing, Procedia Computer Science, 180, 525–533.
14.
MOURTZIS D., DOUKAS M., PSAROMMATIS F., (2013). Environmental Impact of Centralised and Decentralised production Networks in The Era of Personalisation, Robust Manufacturing Control, Springer, Berlin, Heidelberg, 371–384.
15.
OLÁH J., ABURUMMAN N., POPP J., KHAN M.A., HADDAD H., & KITUKUTHA N., 2020, Impact of Industry 4.0 on Environmental Sustainability. Sustainability, 12/11, 46–74.
16.
BURRITT R., CHRIST K., 2016, Industry 4.0 and Environmental Accounting: A New Revolution?, Asian Journal of Sustainability and Social Responsibility, 1/1, 23–38.
17.
LEBEL S.,2016, Fast Machines, Slow Violence: Icts, Planned Obsolescence, and E-Waste, Globalizations, 13/3, 300–309.
18.
SIRAIT M., BISWAS W., BOSWELL B., 2012, Personal Computer Life Cycle Assessment Study: The Case of Western Australia, Proceedings:10th Global Conference on Sustainable Manufacturing, 277–280.
19.
BABBITT C.W., KAHHAT R., WILLIAMS E., BABBITT G.A., 2009, Evolution of Product Lifespan and Implications for Environmental Assessment and Management: A Case Study of Personal Computers in Higher Education, Environmental Science & Technology, 43/13, 5106–5112.
20.
AHLUWALIA P.K., NEMA A.K., 2007, A Life Cycle Based Multi-Objective Optimization Model for the Management of Computer Waste, Resources, Conservation and Recycling, 51/4, 792–826.
21.
YOSHIDA A., TASAKI T., TERAZONO A., 2009, Material Flow Analysis of Used Personal Computers in Japan, Waste Management, 29/5, 1602–1614.
22.
WILLIAMS E., 2004, Energy Intensity of Computer Manufacturing: Hybrid Assessment Combining Process and Economic Input − Output Methods, Environmental Science & Technology, 38/22, 6166–6174.
23.
WILLIAMS E., HATANAKA T., 2005, Residential Computer Usage Patterns in Japan and Associated Life Cycle Energy Use, Proceedings of the 2005 IEEE International Symposium on Electronics and the Environment, 177–182.
24.
AL RAZI K.M.H., 2016, Resourceful Recycling Process of Waste Desktop Computers: A Review Study, Resources, Conservation and Recycling, 110, 30–47.
25.
HOANG A., TSENG W., VISWANATHAN S., EVANS H., 2009, Life Cycle Assessment of a Laptop Computer and its Contribution to Greenhouse Gas Emissions, Researchgate.net.
26.
CORTES M.A., PATIÑO M.L.D., RUÍZ N.L., VACA L.E. M., 2016, Importance of Life Cycle Analysis of the Printed Circuit Board Computer, Open Journal of Applied Sciences, 6/1, 1–6.
27.
KUEHR R., WILLIAMS E., 2003, Computers and the Environment: Understanding and Managing their impacts: Understanding and Managing Their Impacts, Springer, ISBN: 978-94-010-0033-8.
28.
Ministry of Economy, Trade and Industry, Retrieved on October 27th 2021, https://www.meti.go.jp/policy/... main/english/pamphlets/index.html.
29.
e-Gov, Ordinance related to calculation for carbon dioxide equivalent greenhouse gas emissions with their business activities of specified emitters, 2010, Article 2, http://elaws.e-gov.go.jp/searc... /detail?lawId=418M60001400003, (in Japanese).
30.
Ministry of the environment, Announcement of actual emission factor, adjusted emission per electric utility company in FY 2017, 2018, Retrieved on April 23th 2019, http://www.env.go.jp/press/fil..., (in Japanese).
31.
Ministry of the environment, Calculation method and emission factor on calculation, report and publication system, 2015, Retrieved on April 23th 2019, http://ghg-santeikohyo.env.go.... files/calc/itiran2015.pdf, (in Japanese).
32.
Greenhouse gas inventory office of Japan, National Greenhouse Gas inventory Report of JAPAN, 2019, Retrieved on April 15th 2019, http://www-gio.nies.go.jp/abou..., (in Japanese).
33.
TANABE I., WATANABE M., 2011, Development of Cost-effective and Eco-friendly Permanent Grease Lubrication for the Machine Tool Slides, 2011 IEEE International Symposium on Assembly and Manufacturing (ISAM).
34.
TANABE I., KANAKO Y., SAITOH Y., MORI H., URANO K., 2004, Simple and Intelligent Control Using Neural Network About Thermal Deformation of a Machine Tool, Transactions of the Japan Society of Mechanical Engineers, 70/698, 2954–2960, (in Japanese).
35.
SUZUKI M., 2012, Introduction to analysis method using MT system, Nikkankougyoushinbunsya, (in Japanese).
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