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

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    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.
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    Cited by:

    1. 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.
    2. 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.
    3. 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).
    4. 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.
    5. 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.

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