Measuring efficiency and productivity change in power electric generation management companies by using data envelopment analysis: A case study

Energy ◽  
2011 ◽  
Vol 36 (11) ◽  
pp. 6398-6405 ◽  
Author(s):  
Alireza Fallahi ◽  
Reza Ebrahimi ◽  
S.F. Ghaderi
Keyword(s):  
Data Envelopment Analysis ◽  
Productivity Change ◽  
Data Envelopment ◽  
Measuring Efficiency ◽  
Electric Generation ◽  
Using Data ◽  
Efficiency And Productivity ◽  
Generation Management

scholarly journals Measuring Efficiency of Knowledge Production in Health Research Centers Using Data Envelopment Analysis (DEA): A Case Study in Iran

10.19082/3266 ◽  
2016 ◽  
Vol 8 (11) ◽  
pp. 3266-3271
Author(s):  
Mohammad Meskarpour Amiri ◽  
Taha Nasiri ◽  
Seyed Hassan Saadat ◽  
Hosein Amini Anabad ◽  
Payman Mahboobi Ardakan
Keyword(s):  
Data Envelopment Analysis ◽  
Knowledge Production ◽  
Health Research ◽  
Data Envelopment ◽  
Research Centers ◽  
Measuring Efficiency ◽  
Using Data

scholarly journals Evaluation of Assembly Part Build Orientation in Additive Manufacturing Environment using Data Envelopment Analysis

2019 ◽  
Vol 293 ◽  
pp. 02002 ◽  
Author(s):  
Kasin Ransikarbum ◽  
Rapeepan Pitakaso ◽  
Namhun Kim
Keyword(s):  
Data Envelopment Analysis ◽  
Additive Manufacturing ◽  
Process Planning ◽  
Data Envelopment ◽  
3D Objects ◽  
Lathe Machine ◽  
Subtractive Manufacturing ◽  
Personal Use ◽  
Using Data

Whereas Subtractive Manufacturing (SM) is a process by which 3D objects are constructed by cutting material away from a solid block of material, such as milling and lathe machine; Additive Manufacturing (AM) is a synonym for 3D printing and other processes by which 3D objects are constructed by successively depositing material in layers. Recently, AM has become widespread for both industrial and personal use thanks to the freedom and benefits it provides in designing parts, reducing lead time, improving inventory, and supply chain. However, few studies examine process planning issues in AM. In addition, existing studies focus on production of an individual part alone. In this study, we examine the assembly orientation alternatives’ efficiency using Data Envelopment Analysis (DEA) technique for different AM technologies and their associated materials under conflicting criteria. A case study of hardware fasteners using bolt and nut fabrication is illustrated in the study. Our results show that different AM technologies and materials clearly impact efficiency of part production and thus suggest optimal orientation in AM process planning platform.

EFFICIENCY AND PRODUCTIVITY CHANGE IN FIELD CROP AND MILK FARMS IN LUBLIN PROVINCE IN 2014-2016

2018 ◽  
Vol XX (1) ◽  
pp. 137-142
Author(s):  
Alina Syp ◽  
Dariusz Osuch
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Dairy Farms ◽  
Productivity Change ◽  
Data Envelopment ◽  
Field Crop ◽  
Dea Model ◽  
Malmquist Indices ◽  
Efficiency And Productivity ◽  
Efficiency Indicators

The aim of the study was assessment of efficiency and productivity of farms in the Lublin province in the years 2014-2016. The analysis was based on the Data Envelopment Analysis (DEA) model oriented on inputs and Malmquist indices with its components. The calculations were made for medium-sized field and dairy farms that continuously collected data for the FADN system during the period under consideration. In our research all efficiency indicators for dairy farms were larger than for field crop farms. In the years 2014-2016, the average technical efficiency of dairy farms was 0.752, which means that in those farms it is possible to reduce inputs on average by 25% and the value of production will remain at the same level. In the case of field crop farms, inputs should be limited by 33%. The applied decomposition of calculated Malmquist indices allowed to define what factors influenced changes in productivity.

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