scholarly journals Statistical Analysis and Data Envelopment Analysis to Improve the Efficiency of Manufacturing Process of Electrical Conductors

2019 ◽  
Vol 9 (19) ◽  
pp. 3965 ◽  
Author(s):  
Marco Antonio Zamora-Antuñano ◽  
Jorge Cruz-Salinas ◽  
Juvenal Rodríguez-Reséndiz ◽  
Carlos Alberto González-Gutiérrez ◽  
Néstor Méndez-Lozano ◽  
...  
Keyword(s):  
Data Envelopment Analysis ◽  
Statistical Analysis ◽  
Manufacturing Process ◽  
Research Work ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Statistical Tools ◽  
Electrical Conductors ◽  
Productivity Measurements ◽  
Machine Operator

The main focus of this research was to develop an approach using statistical tools and Data envelopment analysis (DEA) to tackling productivity measurements and benchmarking problems in electrical conductor manufacturing environment. In the present work, a tooling efficiency study was carried out with a nozzle used for the manufacture of 23-AWG wires. The efficiency of five types of tooling, four non-Mexican-manufactured types and one Mexican-manufactured type, were compared. Analysis of Variance (ANOVA) and the Tukey test were applied. Six factors were considered that influence of the performance of the tooling during the manufacturing process: productivity, quality, time, machine, operator, and color of the insulating material, but the research work focuses on the efficiency of the tooling die-nozzle. The results demonstrated that two die-nozzle models exhibited the best performance; one of them was the Mexican model, surpassed by a non-Mexican model, the capability process index Cpk = 1.26 manifested a better performance for the 3DND die-nozzle according to the statistical analysis and the tests performed. Subsequently, through a super-efficiency DEA model of inputs-oriented with non-decreasing returns to scale (NDRS). The results obtained in the statistical analysis were corroborated using this technique, its application combined with statistical tools represents an innovation for knowledge in manufacturing processes of electrical conductors. Input data were obtained at a manufacturer of electrical conductors supplier of the automotive sector in the Querétaro City of Mexico.

scholarly journals Two-stage inference in experimental design using dea: an application to intercropping and evidence from randomization theory

2008 ◽  
Vol 28 (2) ◽  
pp. 339-354 ◽  
Author(s):  
Eliane Gonçalves Gomes ◽  
Geraldo da Silva e Souza ◽  
Lúcio José Vivaldi
Keyword(s):  
Data Envelopment Analysis ◽  
Statistical Analysis ◽  
Experimental Design ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Shadow Prices ◽  
Standard Analysis ◽  
Use Of Data ◽  
Constant Returns To Scale ◽  
Experimental Plots

In this article we propose the use of Data Envelopment Analysis (DEA) measures of efficiency, under constant returns to scale and input equal to unity, in the analysis of multidimensional nonnegative responses in the design of experiments. The approach agrees with the standard Analysis of Variance (Covariance) for univariate responses and simplifies the statistical analysis in the multivariate case. The best treatments provided by the analysis optimize a combined output defined by shadow prices, which are the solutions of the DEA problem. The approach is particularly useful for the analysis of intercropping (crop mixtures) experiments. In this context we discuss two examples. To properly address the issue of correlation and non-normality of DEA measurements in different experimental plots we validate the results via Randomization Theory.

A model to evaluate the effects of the returns to scale on the inverse data envelopment analysis

2021 ◽  
Author(s):  
M. Ebrahimzade Adimi ◽  
M. Rostamy-Malkhalifeh ◽  
F. Hosseinzadeh Lotfi ◽  
R Mehrjoo
Keyword(s):  
Data Envelopment Analysis ◽  
Returns To Scale ◽  
Data Envelopment

scholarly journals Does Farm Size and Specialization Matter for Productive Efficiency? Results from Kansas

2011 ◽  
Vol 43 (4) ◽  
pp. 515-528 ◽  
Author(s):  
Amin W. Mugera ◽  
Michael R. Langemeier
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Production Technology ◽  
Returns To Scale ◽  
Productive Efficiency ◽  
Farm Size ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Sample Period ◽  
Analysis Techniques

In this article, we used bootstrap data envelopment analysis techniques to examine technical and scale efficiency scores for a balanced panel of 564 farms in Kansas for the period 1993–2007. The production technology is estimated under three different assumptions of returns to scale and the results are compared. Technical and scale efficiency is disaggregated by farm size and specialization. Our results suggest that farms are both scale and technically inefficient. On average, technical efficiency has deteriorated over the sample period. Technical efficiency varies directly by farm size and the differences are significant. Differences across farm specializations are not significant.

scholarly journals The Efficiency of Waste Sector in Italy: An Application by Data Envelopment Analysis

2020 ◽  
Vol 24 (3) ◽  
pp. 225-238
Author(s):  
Massimo Gastaldi ◽  
Ginevra Virginia Lombardi ◽  
Agnese Rapposelli ◽  
Giulia Romano
Keyword(s):  
Data Envelopment Analysis ◽  
Environmental Performance ◽  
Returns To Scale ◽  
Sustainable Growth ◽  
Waste Reduction ◽  
Data Envelopment ◽  
Environmental Legislation ◽  
Dea Models ◽  
Developed Nations ◽  
Variable Returns To Scale

AbstractWith growing environmental legislation and mounting popular concern for the need to pursuing a sustainable growth, there has been an increasing recognition in developed nations of the importance of waste reduction, recycling and reuse maximization. This empirical study investigates both ecological and economic performances of urban waste systems in 78 major Italian towns for the years 2015 and 2016. To this purpose the study employs the non-parametric approach to efficiency measurement, represented by Data Envelopment Analysis (DEA) technique. More specifically, in the context of environmental performance we implement two output-oriented DEA models in order to consider both constant and variable returns to scale. In addition, we include an undesirable output – the total amount of waste collected – in the two models considered. The results show that there is variability among the municipalities analysed: Northern and Central major towns show higher efficiency scores than Southern and Islands ones.

scholarly journals Cost efficiency of the Czech and Slovak banking sectors: an application of the data envelopment analysis

2016 ◽  
Author(s):  
Iveta Palecková
Keyword(s):  
Data Envelopment Analysis ◽  
Cost Efficiency ◽  
Commercial Banks ◽  
Banking Sector ◽  
Banking Industry ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Cost Efficient ◽  
The Cost ◽  
Variable Returns To Scale

The aim of the paper is to estimate the cost efficiency of the Czech and Slovak commercial banks within the period 2010-2014. For empirical analysis the Data Envelopment Analysis input-oriented model with variable returns to scale is applied on the data of the commercial banks. The intermediation approach is adopted to define the inputs and outputs. The Czech commercial banks are more cost efficient than Slovak commercial banks. The development of average cost efficiency is similar in the Czech and Slovak banking industry. The most efficient Czech banks are Ceská sporitelna and Sberbank in the Czech banking sector, the most efficient Slovak bank is Privatbanka with 100% efficiency.

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