A Proposed DEA Window Analysis for Assessing Efficiency from Asymmetry Dynamic Data
Nowadays, one of the main challenges facing production management is how to enhance the performance of manufacturing processes by utilizing asymmetry input and output data. This research, therefore, developed a framework for window analysis in data envelopment analysis (DEA) for evaluating the overa...
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MDPI AG
2023-08-01
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Online Access: | https://www.mdpi.com/2073-8994/15/9/1650 |
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author | Abbas Al-Refaie Natalija Lepkova |
author_facet | Abbas Al-Refaie Natalija Lepkova |
author_sort | Abbas Al-Refaie |
collection | DOAJ |
description | Nowadays, one of the main challenges facing production management is how to enhance the performance of manufacturing processes by utilizing asymmetry input and output data. This research, therefore, developed a framework for window analysis in data envelopment analysis (DEA) for evaluating the overall technical efficiencies from asymmetry dynamic input and output data. The framework was applied to assess the technical (TE), managerial (PTE), and scale (SE) efficiencies of a blowing machine under three fuzzy input variables (planned production quantity, number of defectives, and idle time) and a fuzzy output variable (actual or target production quantity). The efficiency measures were then evaluated for all DMUs at low (L), middle (M), and high (H) data levels. The obtained optimal fuzzy efficiencies were then transformed into a single crisp optimal efficiency. The results showed that all seven DMUs of the blowing machine were technically inefficient. The input and output slacks were estimated and utilized to determine the necessary improvement actions. Improvement results revealed that the optimal TE, PTE, and SE were significantly improved, which may result in significant savings in production and quality costs. In conclusion, the proposed framework is effective in improving the efficiency of the blowing process and can be utilized for efficiency assessment in a wide range of applications. |
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format | Article |
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institution | Directory Open Access Journal |
issn | 2073-8994 |
language | English |
last_indexed | 2024-03-10T21:54:56Z |
publishDate | 2023-08-01 |
publisher | MDPI AG |
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series | Symmetry |
spelling | doaj.art-d5575084a30549d3910bdd30215689ea2023-11-19T13:10:44ZengMDPI AGSymmetry2073-89942023-08-01159165010.3390/sym15091650A Proposed DEA Window Analysis for Assessing Efficiency from Asymmetry Dynamic DataAbbas Al-Refaie0Natalija Lepkova1Department of Industrial Engineering, University of Jordan, Amman 11942, JordanDepartment of Construction Management and Real Estate, Vilnius Gediminas Technical University, LT-10223 Vilnius, LithuaniaNowadays, one of the main challenges facing production management is how to enhance the performance of manufacturing processes by utilizing asymmetry input and output data. This research, therefore, developed a framework for window analysis in data envelopment analysis (DEA) for evaluating the overall technical efficiencies from asymmetry dynamic input and output data. The framework was applied to assess the technical (TE), managerial (PTE), and scale (SE) efficiencies of a blowing machine under three fuzzy input variables (planned production quantity, number of defectives, and idle time) and a fuzzy output variable (actual or target production quantity). The efficiency measures were then evaluated for all DMUs at low (L), middle (M), and high (H) data levels. The obtained optimal fuzzy efficiencies were then transformed into a single crisp optimal efficiency. The results showed that all seven DMUs of the blowing machine were technically inefficient. The input and output slacks were estimated and utilized to determine the necessary improvement actions. Improvement results revealed that the optimal TE, PTE, and SE were significantly improved, which may result in significant savings in production and quality costs. In conclusion, the proposed framework is effective in improving the efficiency of the blowing process and can be utilized for efficiency assessment in a wide range of applications.https://www.mdpi.com/2073-8994/15/9/1650fuzzy window analysistechnical efficiencypure technical efficiencyscale efficiency |
spellingShingle | Abbas Al-Refaie Natalija Lepkova A Proposed DEA Window Analysis for Assessing Efficiency from Asymmetry Dynamic Data Symmetry fuzzy window analysis technical efficiency pure technical efficiency scale efficiency |
title | A Proposed DEA Window Analysis for Assessing Efficiency from Asymmetry Dynamic Data |
title_full | A Proposed DEA Window Analysis for Assessing Efficiency from Asymmetry Dynamic Data |
title_fullStr | A Proposed DEA Window Analysis for Assessing Efficiency from Asymmetry Dynamic Data |
title_full_unstemmed | A Proposed DEA Window Analysis for Assessing Efficiency from Asymmetry Dynamic Data |
title_short | A Proposed DEA Window Analysis for Assessing Efficiency from Asymmetry Dynamic Data |
title_sort | proposed dea window analysis for assessing efficiency from asymmetry dynamic data |
topic | fuzzy window analysis technical efficiency pure technical efficiency scale efficiency |
url | https://www.mdpi.com/2073-8994/15/9/1650 |
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