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Industrial Plants Performance Evaluation Using Dynamic Dea

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The objective of the paper is to evaluate the energy efficiency performance of industrial plants based on energy audit measures using dynamic Data Envelopment Analysis. The paper demonstrates a three-stage DEA based on slacks-based measure approach to evaluate the energy efficiency of U.S. industrial plants. Also, a 3-step approach to select relevant variables to be employed in slacks-based measure model. The paper has revealed inefficiencies of industrial plants, which were considered as efficient ones examined individually in energy audit procedure. The results indicate that half of analyzed plants are not performing at high energy efficiency, given a total of 6 facilities were operating efficiently. It shows that these industrial plants appear to have the potential to reduce their energy use and cost. Moreover, the results were enriched with the additional analysis of input excesses and output shortfalls and further suggestions for improving energy efficiency are provided.
Rocznik
Strony
465--476
Opis fizyczny
Bibliogr. 20 poz., fig., tab.
Twórcy
autor
  • Insitute of Organization of Production Systems, Faculty of Production Engineering, Warsaw University of Technology, Warsaw, 02-524 Poland
Bibliografia
  • 1. Alhourani F. & Saxena U. (2009), Factors affecting the implementation rates of energy and productivity recommendations in small and medium sized companies, Journal of Manufacturing Systems, Vol. 28, pp. 41–45.
  • 2. Anderson S.T. & Newell R.G. (2004), Information programs for technology adoption: the case of energy- efficiency audits, Resource and Energy Economics, Vol. 26, pp. 27–50.
  • 3. Charnes A., Cooper W.W. & Rhodes E. (1981), Evaluating program and managerial efficiency: an application of data envelopment analysis to program follow through, Management Science, Vol. 6, pp. 668–697.
  • 4. Daraio C. & Simar L. (2007), Advanced Robust and nonparametric methods in efficiency analysis, Methodology and applications, Studies in Productivity and Efficiency, Science+Business Media, LLC, New York.
  • 5. Duzakin E. & Duzakin H. (2007), Measuring the performance of manufacturing firms with super slacks based model of data envelopment analysis: An application of 500 major industrial enterprises in Turkey, European Journal of Operational Research, Vol. 182, pp. 1412–1432.
  • 6. Grösche P. (2008), Measuring Residential Energy Efficiency Improvements with DEA, Ruhr Economic Paper No. 60, http://dx.doi.org/10.2139/ssrn.1280878, 05-08-2016.
  • 7. Lovell C.A.K. (1993), Production Frontiers and Productive Efficiency, H.O. Fried, S.S. Schmidt (Eds.), The Measurement of Productive Efficiency: Techniques and Applications, University Press, Oxford, pp. 3–67.
  • 8. Lozano S. (2015), Alternative SBM model for Network DEA, Computers & Industrial Engineering, Vol. 82, pp. 33–40.
  • 9. Moritaa H., Hirokawa K. & Zhu J. (2005), A slack-based measure of efficiency in context – dependent data envelopment analysis, Omega, Vol. 33, pp. 357–362.
  • 10. Moritaa H. & Avkiran N.K. (2009), Selecting input and outputs in Data Envelopment Analysis by designing statistical experiments, Journal of the Operations Research society of Japan, Vol. 52, No. 2, pp. 163–173.
  • 11. Noro M. & Lazzarin R.M. (2014), Energy audit experiences in foundries, International Journal of Energy Environment and Energy, Vol. 7, pp. 1–15.
  • 12. Onüt S. & Soner, S. (2007), Analysis of energy use and efficiency in Turkish manufacturing sector SMEs, Energy Conversation and Management, Vol. 48, pp. 384–394.
  • 13. Saidur R. & Mekhilef S. (2010), Energy use, energy savings and emission analysis in the Malaysian rubber producing industry, Applied Energy, Vol. 87, pp. 2746–2758.
  • 14. Saricam C. & Erdumlu N., (2012), Evaluating efficiency levels comparatively: data envelopment analysis application for Turkish textile and apparel industry, Journal of Industrial Engineering and Management, Vol. 5, No. 2, pp. 518–531.
  • 15. Thanassoulis E. (2003), Introduction to the theory and application of Data Envelopment Analysis, Springer Science & Business, New York.
  • 16. Thollander P., Backlund S., Trianni A. & Cagno E. (2013), Beyond barriers – A case study on driving forces for improved energy efficiency in the foundry industries in Finland, France, Germany, Italy, Poland, Spain, and Sweden, Applied Energy, Vol. 111, pp. 636–643.
  • 17. Tone K. (2002), A slack-based measure of efficiency in data envelopment analysis, European Journal of Operational Research, Vol. 130, No. 3, pp. 498–509.
  • 18. Xue X., Wu H., Zhang X., Dai J. & Su C. (2015), Measuring energy consumption efficiency of the construction, Journal of Cleaner Production, Vol. 107, pp. 509–515.
  • 19. Yingjian L., Jiezhi L., Qi Q. &Yafei X. (2010), Energy auditing and energy conservation potential for glass works, Applied Energy, Vol. 87, No. 8, pp. 2438–2446.
  • 20. Zaim O. (2004), Measuring environmental performance of state manufacturing through changes in pollution intensities: a DEA framework, Ecological Economics, Vol. 48, pp. 37–47.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6b392b7f-81e0-4edd-9e39-fcf8170c7ee0
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