IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v28y2017i2d10.1007_s10845-014-0986-4.html
   My bibliography  Save this article

Solving dynamic systems with multi-responses by integrating desirability function and data envelopment analysis

Author

Listed:
  • Abbas Al-Refaie

    (University of Jordan)

  • Wafa’a Al-Alaween

    (University of Jordan)

  • Ali Diabat

    (Masdar Institute of Science and Technology)

  • Ming-Hsien Li

    (Feng Chia University)

Abstract

Today’s complexity of product design requires improving multiple quality characteristics. This research proposes an approach that integrates the desirability function and data envelopment analysis to enhance process performance with dynamic multi-responses. Firstly, the desirability function is employed. Then, data envelopment analysis is used to obtain the best settings of controllable factor levels that make the effect of noise factors as small as possible. Three case studies are utilized to demonstrate the effectiveness of the proposed approach, in all of which the proposed approach is found an effective procedure in reducing the effect of noise factors, does not need huge data for the analysis or any subjective information and human judgment, and can be used regardless of linearity or nonlinearity relationship between the signal factor and responses. Such advantages should provide great assistance to product engineers in improving performance of dynamic systems with multiple responses.

Suggested Citation

  • Abbas Al-Refaie & Wafa’a Al-Alaween & Ali Diabat & Ming-Hsien Li, 2017. "Solving dynamic systems with multi-responses by integrating desirability function and data envelopment analysis," Journal of Intelligent Manufacturing, Springer, vol. 28(2), pages 387-403, February.
    • Handle: RePEc:spr:joinma:v:28:y:2017:i:2:d:10.1007_s10845-014-0986-4
    DOI: 10.1007/s10845-014-0986-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-014-0986-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-014-0986-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ruggiero, John, 1998. "Non-discretionary inputs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 111(3), pages 461-469, December.
    2. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. Abbas Al-Refaie & Ibrahim Rawabdeh & Reema Abu-alhaj & Issam S. Jalham, 2012. "A Fuzzy Multiple Regression Approach for Optimizing Multiple Responses in the Taguchi Method," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 2(3), pages 13-34, July.
    5. Muniz, M. A., 2002. "Separating managerial inefficiency and external conditions in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(3), pages 625-643, December.
    6. Rajiv D. Banker & Richard C. Morey, 1986. "Efficiency Analysis for Exogenously Fixed Inputs and Outputs," Operations Research, INFORMS, vol. 34(4), pages 513-521, August.
    7. Abbas Al-Refaie, 2010. "Super-Efficiency DEA Approach for Optimizing Multiple Quality Characteristics in Parameter Design," International Journal of Artificial Life Research (IJALR), IGI Global, vol. 1(2), pages 58-71, April.
    8. Abbas Al-Refaie & Ming-Hsien Li, 2011. "Optimizing the Performance of Plastic Injection Molding Using Weighted Additive Model in Goal Programming," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 1(2), pages 43-54, April.
    9. Chao-Ton Su & Mu-Chen Chen & Hsiao-Ling Chan, 2005. "Applying neural network and scatter search to optimize parameter design with dynamic characteristics," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(10), pages 1132-1140, October.
    10. Kwang‐Jae Kim & Dennis K. J. Lin, 2000. "Simultaneous optimization of mechanical properties of steel by maximizing exponential desirability functions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(3), pages 311-325.
    11. Ruggiero, John, 1996. "On the measurement of technical efficiency in the public sector," European Journal of Operational Research, Elsevier, vol. 90(3), pages 553-565, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mouhamadou Mansour Mbow & Christelle Grandvallet & Frederic Vignat & Philippe Rene Marin & Nicolas Perry & Franck Pourroy, 2022. "Mathematization of experts knowledge: example of part orientation in additive manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 33(5), pages 1209-1227, June.
    2. Chien-Yi Huang & Kuo-Ching Ying, 2019. "Intelligent parametric design for a multiple-quality-characteristic glue-dispensing process," Journal of Intelligent Manufacturing, Springer, vol. 30(5), pages 2291-2305, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lee, Boon L. & Worthington, Andrew C., 2014. "Technical efficiency of mainstream airlines and low-cost carriers: New evidence using bootstrap data envelopment analysis truncated regression," Journal of Air Transport Management, Elsevier, vol. 38(C), pages 15-20.
    2. Huguenin, Jean-Marc, 2015. "Adjusting for the environment in DEA: A comparison of alternative models based on empirical data," Socio-Economic Planning Sciences, Elsevier, vol. 52(C), pages 41-54.
    3. Paolo Liberati & Raffaele Lagravinese & Giuliano Resce, 2017. "How Does Economic Social And Cultural Status Affect The Efficiency Of Educational Attainments? A Comparative Analysis On Pisa Results," Departmental Working Papers of Economics - University 'Roma Tre' 0217, Department of Economics - University Roma Tre.
    4. Mushtaq Taleb & Ruzelan Khalid & Ali Emrouznejad & Razamin Ramli, 2023. "Environmental efficiency under weak disposability: an improved super efficiency data envelopment analysis model with application for assessment of port operations considering NetZero," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6627-6656, July.
    5. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    6. Hua, Zhongsheng & Bian, Yiwen & Liang, Liang, 2007. "Eco-efficiency analysis of paper mills along the Huai River: An extended DEA approach," Omega, Elsevier, vol. 35(5), pages 578-587, October.
    7. Henriques, C.O. & Chavez, J.M. & Gouveia, M.C. & Marcenaro-Gutierrez, O.D., 2022. "Efficiency of secondary schools in Ecuador: A value based DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    8. Reilly, Allison C. & Davidson, Rachel A. & Nozick, Linda K. & Chen, Thomas & Guikema, Seth D., 2016. "Using data envelopment analysis to evaluate the performance of post-hurricane electric power restoration activities," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 197-204.
    9. Syrjanen, Mikko J., 2004. "Non-discretionary and discretionary factors and scale in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 158(1), pages 20-33, October.
    10. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    11. Bjørndal, Endre & Bjørndal, Mette & Cullmann, Astrid & Nieswand, Maria, 2018. "Finding the right yardstick: Regulation of electricity networks under heterogeneous environments," European Journal of Operational Research, Elsevier, vol. 265(2), pages 710-722.
    12. Ruggiero, John, 2004. "Performance evaluation when non-discretionary factors correlate with technical efficiency," European Journal of Operational Research, Elsevier, vol. 159(1), pages 250-257, November.
    13. Brennan, Shae & Haelermans, Carla & Ruggiero, John, 2014. "Nonparametric estimation of education productivity incorporating nondiscretionary inputs with an application to Dutch schools," European Journal of Operational Research, Elsevier, vol. 234(3), pages 809-818.
    14. Thyago Celso Cavalcante Nepomuceno & Katarina Tatiana Marques Santiago & Cinzia Daraio & Ana Paula Cabral Seixas Costa, 2022. "Exogenous crimes and the assessment of public safety efficiency and effectiveness," Annals of Operations Research, Springer, vol. 316(2), pages 1349-1382, September.
    15. Julie Harrison & Paul Rouse & Jamie Armstrong, 2012. "Categorical and continuous non-discretionary variables in data envelopment analysis: a comparison of two single-stage models," Journal of Productivity Analysis, Springer, vol. 37(3), pages 261-276, June.
    16. Alireza Amirteimoori & Mahnaz Maghbouli & Sohrab Kordrostami, 2016. "Multi-dimensional Nondiscretionary Factors in Data Envelopment Analysis: A Slack-Based Measure," Computational Economics, Springer;Society for Computational Economics, vol. 48(2), pages 211-223, August.
    17. Andrew Johnson & John Ruggiero, 2014. "Nonparametric measurement of productivity and efficiency in education," Annals of Operations Research, Springer, vol. 221(1), pages 197-210, October.
    18. José Manuel Cordero & Cristina Polo & Daniel Santín & Gabriela Sicilia, 2016. "Monte-Carlo Comparison of Conditional Nonparametric Methods and Traditional Approaches to Include Exogenous Variables," Pacific Economic Review, Wiley Blackwell, vol. 21(4), pages 483-497, October.
    19. Forsund, Finn R. & Sarafoglou, Nikias, 2005. "The tale of two research communities: The diffusion of research on productive efficiency," International Journal of Production Economics, Elsevier, vol. 98(1), pages 17-40, October.
    20. Suzuki, Soushi & Nijkamp, Peter, 2016. "An evaluation of energy-environment-economic efficiency for EU, APEC and ASEAN countries: Design of a Target-Oriented DFM model with fixed factors in Data Envelopment Analysis," Energy Policy, Elsevier, vol. 88(C), pages 100-112.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:joinma:v:28:y:2017:i:2:d:10.1007_s10845-014-0986-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.