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Window Analysis and MPI for Efficiency and Productivity Assessment Under Fuzzy Data: Window Analysis and MPI

Window Analysis and MPI for Efficiency and Productivity Assessment Under Fuzzy Data: Window Analysis and MPI

Abbas Al-Refaie
Copyright: © 2022 |Volume: 12 |Issue: 1 |Pages: 22
ISSN: 2156-1680|EISSN: 2156-1672|EISBN13: 9781683182283|DOI: 10.4018/IJMMME.299058
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MLA

Al-Refaie, Abbas. "Window Analysis and MPI for Efficiency and Productivity Assessment Under Fuzzy Data: Window Analysis and MPI." IJMMME vol.12, no.1 2022: pp.1-22. http://doi.org/10.4018/IJMMME.299058

APA

Al-Refaie, A. (2022). Window Analysis and MPI for Efficiency and Productivity Assessment Under Fuzzy Data: Window Analysis and MPI. International Journal of Manufacturing, Materials, and Mechanical Engineering (IJMMME), 12(1), 1-22. http://doi.org/10.4018/IJMMME.299058

Chicago

Al-Refaie, Abbas. "Window Analysis and MPI for Efficiency and Productivity Assessment Under Fuzzy Data: Window Analysis and MPI," International Journal of Manufacturing, Materials, and Mechanical Engineering (IJMMME) 12, no.1: 1-22. http://doi.org/10.4018/IJMMME.299058

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Abstract

This research develops a procedure for DEA window analysis and MPI evaluation of a manufacturing process with fuzzy inputs and outputs. A real case study was provided to illustrate relative efficiency and MPI assessment of a blowing machine over a period of one a year. The proposed approach was implemented to measure the technical, pure technical, and scale efficiency scores for decision making unit. The results showed that the blowing process was technically inefficient due to scale inefficiency. Therefore, management should optimize the size of operations and better utilize resources. Then, the lower and upper MPI values and their corresponding technology change and efficiency change were calculated. The MPI results revealed the reasons behind MPI progress or regress in current period measured with respect to next period. This procedure provides great assistance to process engineering in obtaining reliable feedback on process performance and guide them to take proper actions.