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Engineering Applications of Data Envelopment Analysis

In: Handbook on Data Envelopment Analysis

Author

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  • Konstantinos P. Triantis

    (Virginia Tech)

Abstract

Engineering is concerned with the design of products, services, processes, or in general with the design of systems. These design activities are managed and improved by the organization’s decision-makers. Therefore, the performance evaluation of the production function where engineering plays a fundamental role is an integral part of managerial decision-making. In the last 20 years, there has been limited research that uses data envelopment analysis (DEA) in engineering. One can attribute this to a number of issues that include but are not limited to the lack of understanding of the role of DEA in assessing and improving design decisions, the inability to open the input/output process transformation box, and the unavailability of production and engineering data. Nevertheless, the existing DEA applications in engineering have focused on the evaluation of alternative design configurations, have proposed performance improvement interventions for production processes at the disaggregated level, assessed the performance of hierarchical manufacturing organizations, studied the dynamical behavior of production systems, and have dealt with data imprecision issues. This chapter discusses the issues that the researcher faces when applying DEA to engineering problems, proposes an approach for the design of an integrated DEA-based performance measurement system, summarizes studies that have focused on engineering applications of DEA, and suggests some systems thinking concepts that are appropriate for future DEA research in engineering.

Suggested Citation

  • Konstantinos P. Triantis, 2011. "Engineering Applications of Data Envelopment Analysis," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 363-402, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-6151-8_14
    DOI: 10.1007/978-1-4419-6151-8_14
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    Citations

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    Cited by:

    1. Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
    2. Topcu, Taylan G. & Triantis, Konstantinos & Roets, Bart, 2019. "Estimation of the workload boundary in socio-technical infrastructure management systems: The case of Belgian railroads," European Journal of Operational Research, Elsevier, vol. 278(1), pages 314-329.
    3. Kottas, Angelos T. & Bozoudis, Michail N. & Madas, Michael A., 2020. "Turbofan aero-engine efficiency evaluation: An integrated approach using VSBM two-stage network DEA," Omega, Elsevier, vol. 92(C).
    4. Adel Hatami-Marbini & Per J. Agrell & Hirofumi Fukuyama & Kobra Gholami & Pegah Khoshnevis, 2017. "The role of multiplier bounds in fuzzy data envelopment analysis," Annals of Operations Research, Springer, vol. 250(1), pages 249-276, March.
    5. Fallah-Fini, Saeideh & Triantis, Konstantinos & Rahmandad, Hazhir & de la Garza, Jesus M., 2015. "Measuring dynamic efficiency of highway maintenance operations," Omega, Elsevier, vol. 50(C), pages 18-28.

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