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Engineering Applications of Data Envelopment Analysis

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Book cover Handbook on Data Envelopment Analysis

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 164))

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.

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Notes

  1. 1.

    There have been attempts in the literature to define the theoretical production function. However, the focus of this chapter is to build on the notion of the empirical production function and how it has been used in engineering applications.

  2. 2.

    Part of the material of this section is adopted from Hoopes, B., Triantis, K., and N. Partangel, 2000, The Relationship Between Process and Manufacturing Plant Performance: A Goal Programming Approach, International Journal of Operations and Quantitative Management, 6(4), 287–310.

  3. 3.

    Part of the material of this section is adapted from Triantis, K., Sarangi, S. and D. Kuchta, 2003, Fuzzy Pair-Wise Dominance and Fuzzy Indices: An Evaluation of Productive Performance, European Journal of Operational Research, 144, 412–428.

  4. 4.

    Part of the material in this section is adapted from Vaneman, W. and K. Triantis, 2003, The Dynamic Production Axioms and System Dynamics Behaviors: The Foundation for Future Integration, Journal of Productivity Analysis, 19 (1), 93–113 and Vaneman and Triantis, 2007, Evaluating the Productive Efficiency of Dynamical Systems, IEEE Transactions on Engineering Management, 54 (3), 600–612.

  5. 5.

    The term policy is used to describe how a decision process converts information into action to show a change in the system (Forrester (1961)). Forrester (1968) further identifies four concepts found within any policy statement:

    1. A goal.

    2. An observed condition of the system.

    3. A method to express any discrepancy between the goal and the observed condition.

    4. Guidelines of which actions to take based on the discrepancy.

  6. 6.

    Part of this discussion has been taken from Ozbek et al. 2010a, b.

  7. 7.

    Part of the material in this section is adapted from Triantis, K. and P. Otis, 2003, A Dominance Based Definition of Productive Efficiency for Manufacturing Taking into Account Pollution Prevention and Recycling, forthcoming, European Journal of Operational Research.

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  1. System Performance Laboratory, Grado Department of Industrial and Systems Engineering, Northern Virginia Center, Virginia Tech, 7053 Haycock Road, Falls Church, VA, 22043-2311, USA

    Konstantinos P. Triantis

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  1. McCombs School of Business, Dept. Management Science &, University of Texas, Austin, University Station 1, Austin, 78712-0212, Texas, USA

    William W. Cooper

  2. Dept. Industrial and, Operations Engineering, University of Michigan, Beal Avenue 1205, Ann Arbor, 48109-2117, Michigan, USA

    Lawrence M. Seiford

  3. Dept. Management, Worcester Polytechnic Institute, Institute Road 100, Worcester, 01609, Massachusetts, USA

    Joe Zhu

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Triantis, K.P. (2011). Engineering Applications of Data Envelopment Analysis. In: Cooper, W., Seiford, L., Zhu, J. (eds) Handbook on Data Envelopment Analysis. International Series in Operations Research & Management Science, vol 164. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-6151-8_14

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