IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i20p8629-d430804.html
   My bibliography  Save this article

Development of a New Green Indicator and Its Implementation in a Cyber–Physical System for a Green Supply Chain

Author

Listed:
  • Paula Morella

    (Design and Manufacturing Engineering Department, Universidad de Zaragoza, 50018 Zaragoza, Spain)

  • María Pilar Lambán

    (Design and Manufacturing Engineering Department, Universidad de Zaragoza, 50018 Zaragoza, Spain)

  • Jesús Royo

    (Design and Manufacturing Engineering Department, Universidad de Zaragoza, 50018 Zaragoza, Spain)

  • Juan Carlos Sánchez

    (Smart Systems, Tecnalia, 20009 Donostia-San Sebastian, Spain)

  • Lisbeth del Carmen Ng Corrales

    (Design and Manufacturing Engineering Department, Universidad de Zaragoza, 50018 Zaragoza, Spain
    Department of Industrial Engineering, Universidad Tecnológica de Panamá, 0819-07289 Ciudad de Panamá, Panama)

Abstract

This work investigates Industry 4.0 technologies by developing a new key performance indicator that can determine the energy consumption of machine tools for a more sustainable supply chain. To achieve this, we integrated the machine tool indicator into a cyber–physical system for easy and real-time capturing of data. We also developed software that can turn these data into relevant information (using Python): Using this software, we were able to view machine tool activities and energy consumption in real time, which allowed us to determine the activities with greater energy burdens. As such, we were able to improve the application of Industry 4.0 in machine tools by allowing informed real-time decisions that can reduce energy consumption. In this research, a new Key Performance Indicator (KPI) was been developed and calculated in real time. This KPI can be monitored, can measure the sustainability of machining processes in a green supply chain (GSC) using Nakajima’s six big losses from the perspective of energy consumption, and is able to detect what the biggest energy loss is. This research was implemented in a cyber–physical system typical of Industry 4.0 to demonstrate its applicability in real processes. Other productivity KPIs were implemented in order to compare efficiency and sustainability, highlighting the importance of paying attention to both terms at the same time, given that the improvement of one does not imply the improvement of the other, as our results show.

Suggested Citation

  • Paula Morella & María Pilar Lambán & Jesús Royo & Juan Carlos Sánchez & Lisbeth del Carmen Ng Corrales, 2020. "Development of a New Green Indicator and Its Implementation in a Cyber–Physical System for a Green Supply Chain," Sustainability, MDPI, vol. 12(20), pages 1-19, October.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:20:p:8629-:d:430804
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/20/8629/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/20/8629/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. de Sousa Jabbour, Ana Beatriz Lopes & Jabbour, Charbel Jose Chiappetta & Foropon, Cyril & Godinho Filho, Moacir, 2018. "When titans meet – Can industry 4.0 revolutionise the environmentally-sustainable manufacturing wave? The role of critical success factors," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 18-25.
    2. Ilie Mihai Tăucean & Matei Tămășilă & Larisa Ivascu & Șerban Miclea & Mircea Negruț, 2019. "Integrating Sustainability and Lean: SLIM Method and Enterprise Game Proposed," Sustainability, MDPI, vol. 11(7), pages 1-28, April.
    3. Sundarakani, Balan & de Souza, Robert & Goh, Mark & Wagner, Stephan M. & Manikandan, Sushmera, 2010. "Modeling carbon footprints across the supply chain," International Journal of Production Economics, Elsevier, vol. 128(1), pages 43-50, November.
    4. Dalenogare, Lucas Santos & Benitez, Guilherme Brittes & Ayala, Néstor Fabián & Frank, Alejandro Germán, 2018. "The expected contribution of Industry 4.0 technologies for industrial performance," International Journal of Production Economics, Elsevier, vol. 204(C), pages 383-394.
    5. Rosario Domingo & Sergio Aguado, 2015. "Overall Environmental Equipment Effectiveness as a Metric of a Lean and Green Manufacturing System," Sustainability, MDPI, vol. 7(7), pages 1-17, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Paula Morella & María Pilar Lambán & Jesús Antonio Royo & Juan Carlos Sánchez, 2021. "The Importance of Implementing Cyber Physical Systems to Acquire Real-Time Data and Indicators," J, MDPI, vol. 4(2), pages 1-7, May.
    2. Qinglan Liu & Adriana Hofmann Trevisan & Miying Yang & Janaina Mascarenhas, 2022. "A framework of digital technologies for the circular economy: Digital functions and mechanisms," Business Strategy and the Environment, Wiley Blackwell, vol. 31(5), pages 2171-2192, July.
    3. Ahmed Zainul Abideen & Jaafar Pyeman & Veera Pandiyan Kaliani Sundram & Ming-Lang Tseng & Shahryar Sorooshian, 2021. "Leveraging Capabilities of Technology into a Circular Supply Chain to Build Circular Business Models: A State-of-the-Art Systematic Review," Sustainability, MDPI, vol. 13(16), pages 1-26, August.
    4. Qiurui Liu & Juntian Huang & Ting Ni & Lin Chen, 2022. "Measurement of China’s Building Energy Consumption from the Perspective of a Comprehensive Modified Life Cycle Assessment Statistics Method," Sustainability, MDPI, vol. 14(8), pages 1-19, April.
    5. Govindan, Kannan & Kannan, Devika & Jørgensen, Thomas Ballegård & Nielsen, Tim Straarup, 2022. "Supply Chain 4.0 performance measurement: A systematic literature review, framework development, and empirical evidence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Ying & Dai, Jing & Cui, Li, 2020. "The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model," International Journal of Production Economics, Elsevier, vol. 229(C).
    2. Olumide Emmanuel Oluyisola & Fabio Sgarbossa & Jan Ola Strandhagen, 2020. "Smart Production Planning and Control: Concept, Use-Cases and Sustainability Implications," Sustainability, MDPI, vol. 12(9), pages 1-29, May.
    3. Andrea Chiarini, 2021. "Industry 4.0 technologies in the manufacturing sector: Are we sure they are all relevant for environmental performance?," Business Strategy and the Environment, Wiley Blackwell, vol. 30(7), pages 3194-3207, November.
    4. Bai, Chunguang & Dallasega, Patrick & Orzes, Guido & Sarkis, Joseph, 2020. "Industry 4.0 technologies assessment: A sustainability perspective," International Journal of Production Economics, Elsevier, vol. 229(C).
    5. Tao, Zhibin & Chao, Jiaxiao, 2024. "Unlocking new opportunities in the industry 4.0 era, exploring the critical impact of digital technology on sustainable performance and the mediating role of GSCM practices," Innovation and Green Development, Elsevier, vol. 3(3).
    6. Rafael, Lizarralde Dorronsoro & Jaione, Ganzarain Epelde & Cristina, López & Ibon, Serrano Lasa, 2020. "An Industry 4.0 maturity model for machine tool companies," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    7. Gillani, Fatima & Chatha, Kamran Ali & Sadiq Jajja, Muhammad Shakeel & Farooq, Sami, 2020. "Implementation of digital manufacturing technologies: Antecedents and consequences," International Journal of Production Economics, Elsevier, vol. 229(C).
    8. Wen-Hsien Tsai & Poching Su, 2024. "A Dynamic Approach to Sustainable Knitted Footwear Production in Industry 4.0: Integrating Short-Term Profitability and Long-Term Carbon Efficiency," Sustainability, MDPI, vol. 16(16), pages 1-24, August.
    9. Shih-Chia Chang & Hsu-Hwa Chang & Ming-Tsang Lu, 2021. "Evaluating Industry 4.0 Technology Application in SMEs: Using a Hybrid MCDM Approach," Mathematics, MDPI, vol. 9(4), pages 1-21, February.
    10. Cugno, Monica & Castagnoli, Rebecca & Büchi, Giacomo, 2021. "Openness to Industry 4.0 and performance: The impact of barriers and incentives," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    11. Kristoffersen, Eivind & Blomsma, Fenna & Mikalef, Patrick & Li, Jingyue, 2020. "The smart circular economy: A digital-enabled circular strategies framework for manufacturing companies," Journal of Business Research, Elsevier, vol. 120(C), pages 241-261.
    12. Abeer M. Abdelhalim & Nahla Ibrahim & Mohammed Alomair, 2023. "The Moderating Role of Digital Environmental Management Accounting in the Relationship between Eco-Efficiency and Corporate Sustainability," Sustainability, MDPI, vol. 15(9), pages 1-16, April.
    13. Laubengaier, Désirée A. & Cagliano, Raffaella & Canterino, Filomena, 2022. "It Takes Two to Tango: Analyzing the Relationship between Technological and Administrative Process Innovations in Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    14. Culot, Giovanna & Orzes, Guido & Sartor, Marco & Nassimbeni, Guido, 2020. "The future of manufacturing: A Delphi-based scenario analysis on Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    15. Duan, Wenqi & Khurshid, Adnan & Khan, Khalid & Calin, Adrian Cantemir, 2024. "Transforming industry: Investigating 4.0 technologies for sustainable product evolution in china through a novel fuzzy three-way decision-making process," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    16. Rodríguez-Espíndola, Oscar & Chowdhury, Soumyadeb & Dey, Prasanta Kumar & Albores, Pavel & Emrouznejad, Ali, 2022. "Analysis of the adoption of emergent technologies for risk management in the era of digital manufacturing," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    17. Wen-Hsien Tsai & Yin-Hwa Lu, 2018. "A Framework of Production Planning and Control with Carbon Tax under Industry 4.0," Sustainability, MDPI, vol. 10(9), pages 1-24, September.
    18. Riccardo Brozzi & David Forti & Erwin Rauch & Dominik T. Matt, 2020. "The Advantages of Industry 4.0 Applications for Sustainability: Results from a Sample of Manufacturing Companies," Sustainability, MDPI, vol. 12(9), pages 1-19, May.
    19. Mariani, Marcello & Borghi, Matteo, 2019. "Industry 4.0: A bibliometric review of its managerial intellectual structure and potential evolution in the service industries," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    20. Tortorella, Guilherme Luz & Fogliatto, Flavio S. & Cauchick-Miguel, Paulo A. & Kurnia, Sherah & Jurburg, Daniel, 2021. "Integration of Industry 4.0 technologies into Total Productive Maintenance practices," International Journal of Production Economics, Elsevier, vol. 240(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:20:p:8629-:d:430804. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.