Advertisement

Energy Loss Risk (ELOS R) in Supply Chain, Micro-processes to Decrease Greenhouse Gas Emissions

  • Salvador Ávila Filho
  • Ivone Cerqueira
  • Jade Spínola Ávila
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 793)

Abstract

The multi-scale analysis of energy loss in supply chains allows a causal link to be identified identifying the micro-processes and priority behaviors that cause the greatest socio-environmental impact on the macro-processes inside the global chains of product circulation. In this way, global programs and goals can be achieved in a proper way. This article intends to discuss concepts, goals and techniques applied to the work environment and the environment of the cities in their operational routine. These routines cause high frequency energy losses, low individual impact and high impact on event integration. This routine influences industrial activity, the local and global supply chain. The overall indicator to be monitored is the emission of greenhouse gases and the reduction in non-renewable fuel consumption. The local indicator to be measured is loss of energy in activities and operations, frequency and intensity based on the number of actors that act by losing energy.

Keywords

Energy Losses Human factors Supply chain Micro-processes 

References

  1. 1.
    Phylipsen, G.J.M.: Energy Efficiency Indicators: Best practice and potential use in developing country policy making. Phylipsen Climate Change Consulting (2010)Google Scholar
  2. 2.
    Abubakar, T.: A Study of Sustainability in the Oil and Gas Supply Chain. Doctoral thesis at University of Central Lancashire in Philosophy (2014)Google Scholar
  3. 3.
    Energy Efficiency 2017: Market Report Series. International Energy Agency (IEA) (2017)Google Scholar
  4. 4.
    Marchi, B., Zanoni, S.: Supply chain management for improved energy efficiency: review and opportunities. Energies 10, 1618 (2017)CrossRefGoogle Scholar
  5. 5.
    Saving energy in the oil and gas industry: The global oil and gas industry association for environmental and social issues. IPIECA, London (2013)Google Scholar
  6. 6.
    Letwin, O., Barker, G., Stunell, A.: Behaviour Change and Energy Use. Department of Energy & Climate Change (2015)Google Scholar
  7. 7.
    Farley, K., Mazur-Stommen, S.: Saving Energy with Neighborly Behavior: Energy Efficiency for Multifamily Renters and Homebuyers. American Council for an Energy-Efficient Economy, Washington (2014)Google Scholar
  8. 8.
    Avila, S: Methodology to minimize effluent at the source from the investigation of operational abnormalities: Cases of the chemical industry. 229f. Thesis, Master degree in master’s degree in environmental technologies in the production process - Environmental Engineering Department of UFBA, Federal University of Bahia, Salvador (2004)Google Scholar
  9. 9.
    Avila, S.: Etiology of Operational Abnormalities in Industry: A Model for Learning. 296f. Thesis, Doctorate degree in Technology of Chemical and Biochemical Processes - School Of Chemistry of UFRJ. Federal University of Rio de Janeiro, Rio de Janeiro (2010)Google Scholar
  10. 10.
    Robertson, A.: Energy Efficiency Commitment. In: Aberdeenshire’s Council Housing Stock – Aberdeenshire Council (2006)Google Scholar
  11. 11.
    Ávila, S.F., Costa, C.: Analysis of cognitive deficit in routine task, as a strategy to reduce accidents and industrial increase production. In: Safety and Reliability of Complex Engineered Systems, London, pp. 2837–2844Google Scholar
  12. 12.
    Avila, S.F., Drigo, E.S.: Evaluation of human factors through behavior, C4t. In: III Congress Brazilian Association for Risk Analysis, Process Safety and Reliability – ABRISCO, Rio de Janeiro (2017)Google Scholar
  13. 13.
    Avila, S.F.: Improving the task and communication for a fair culture in energy and safety, exercise of intervention in the metallurgical industry and offshore oil production. In: III Congress Brazilian Association for Risk Analysis, Process Safety and Reliability – ABRISCO, Rio de Janeiro (2017)Google Scholar
  14. 14.
    Drigo, E., Ávila, F.S.: Organizational communication: discussion of pyramid model application in shift records. In: Kantola, J.I., et al. (eds.) Advances in Human Factors, Business Management, Training and Education. Advances in Intelligent Systems and Computing, vol. 498. Springer International Publishing, Switzerland (2017b)Google Scholar
  15. 15.
    Avila, S.F., Sousa, C.R., Carvalho, A.C.: Assessment of complexity in the task to define safeguards against dynamic risks. Procedia Manuf. 3, 1772–1779 (2015). 6th International Conference on Applied Human Factors and Ergonomics (AHFE 2015)CrossRefGoogle Scholar
  16. 16.
    Galvão, C.: Operational practices for reducing energy consumption in production procedures. In: III Congress Brazilian Association for Risk Analysis, Process Safety and Reliability – ABRISCO, Rio de Janeiro (2017)Google Scholar
  17. 17.
    Ferreira, J.: Analysis of the impact of low operational reliability on the energy indicators of an oil refinery. In: III Congress Brazilian Association for Risk Analysis, Process Safety and Reliability – ABRISCO, Rio de Janeiro (2017)Google Scholar
  18. 18.
    Avila, S.F.: Thermal performance assessment through cooling tower modeling: refinery case. In: Cooling Technology Institute Annual Conference, Houston, Texas (2018)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Salvador Ávila Filho
    • 1
  • Ivone Cerqueira
    • 1
  • Jade Spínola Ávila
    • 2
  1. 1.Federal University of BahiaSalvadorBrazil
  2. 2.Federal University of Campina GrandeCampina GrandeBrazil

Personalised recommendations