Effective Improvement Solutions in Organizations Using Data Envelopment Analysis (DEA) and TRIZ: A Case Study in Higher Education

One of the main goals of education policy is to enhance educational outcomes. If resources are used inefficiently, they will fail to maximise those outcomes. Data Envelopment Analysis was used to calculate technical efficiency of public spending on education for EU-28 using the latest higher education statistics available. Focusing on European higher education, conceptual and methodological issues related to the measurement and analysis of efficiency were discussed. The most efficient countries are identified and also countries for which real efficiency improvements are possible. A novel set of variables is used to highlight more appropriately the distinctiveness of the higher education sector and the relationship between input and outputs. The advantage of using Data Envelopment Analysis is that it identifies the best performing decision, making units and not the averages. This type of information about the efficiency of public spending on education is of importance to many parties. It can be used to promote ‘yardstick’ competition in the areas of education where the lack of market mechanisms is apparent, guide policy proposals, and to enhance the monitoring of education. Key words: efficiency in education, higher education, public spending, data envelopment analysis, European Union.

Download Full-text

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

MATEC Web of Conferences ◽

10.1051/matecconf/201929302002 ◽

2019 ◽

Vol 293 ◽

pp. 02002 ◽

Cited By ~ 1

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.

Download Full-text