Data envelopment analysis-based multi-criteria decision making for part orientation selection in fused deposition modeling

2017 ◽  
Author(s):  
Kasin Ransikarbum ◽  
Namhun Kim
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Fused Deposition Modeling ◽  
Data Envelopment ◽  
Multi Criteria Decision Making ◽  
Orientation Selection ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Part Orientation

scholarly journals Evaluating 3D Printers Using Data Envelopment Analysis

2021 ◽  
Vol 11 (9) ◽  
pp. 4209
Author(s):  
Theodore Papatheodorou ◽  
John Giannatsis ◽  
Vassilis Dedoussis
Keyword(s):  
Data Envelopment Analysis ◽  
Fused Deposition Modeling ◽  
Production Systems ◽  
Manufacturing Sector ◽  
Data Envelopment ◽  
Programming Technique ◽  
Fused Deposition ◽  
Efficiency Performance ◽  
3D Printers ◽  
Using Data

Data Envelopment Analysis (DEA) is an established powerful mathematical programming technique, which has been employed quite extensively for assessing the efficiency/performance of various physical or virtual and simple or complex production systems, as well as of consumer and industrial products and technologies. The purpose of the present study is to investigate whether DEA may be employed for evaluating the technical efficiency/performance of 3D printers, an advanced manufacturing technology of increasing importance for the manufacturing sector. For this purpose, a representative sample of 3D printers based on Fused Deposition Modeling technology is examined. The technical factors/parameters of 3D printers, which are incorporated in the DEA, are investigated and discussed in detail. DEA evaluation results compare favorably with relevant benchmarks from experts, indicating that the suggested DEA technique in conjunction with technical and expert evaluation could be employed for evaluating the performance of a highly technological system, such as the 3D printer.

Influence of Part Orientation on the Surface Roughness in the Process of Fused Deposition Modeling

2021 ◽  
Vol 896 ◽  
pp. 29-37
Author(s):  
Ján Milde ◽  
František Jurina ◽  
Jozef Peterka ◽  
Patrik Dobrovszký ◽  
Jakub Hrbál ◽  
...  
Keyword(s):  
Surface Roughness ◽  
3D Printing ◽  
Fused Deposition Modeling ◽  
Orientation Angle ◽  
Acrylonitrile Butadiene Styrene ◽  
Lower Surface ◽  
Geometrical Model ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Part Orientation

The article focused on the influence of part orientation on the surface roughness of cuboid parts during the process of fabricating by FDM technology. The components, in this case, is simple cuboid part with the dimensions 15 mm x 15mm x 30 mm. A geometrical model is defined that considers the shape of the material filaments after deposition, to define a theoretical roughness profile, for a certain print orientation angle. Five different print orientations in the X-axis of the cuboid part were set: 0°, 30°, 45°, 60°, and 90°. According to previous research in the field of FDM technology by the author, the internal structure (infill) was set at the value of 70%. The method of 3D printing was the Fused Deposition Modeling (FDM) and the material used in this research was thermoplastic ABS (Acrylonitrile butadiene styrene). For each setting, there were five specimens (twenty five prints in total). Prints were fabricated on a Zortrax M200 3D printer. After the 3D printing, the surface “A” was investigated by portable surface roughness tester Mitutoyo SJ-210. Surface roughness in the article is shown in the form of graphs (Fig.7). Results show increase in part roughness with increasing degree of part orientation. When the direction of applied layers on the measured surface was horizontal, significant improvement in surface roughness was observed. Findings in this paper can be taken into consideration when designing parts, as they can contribute in achieving lower surface roughness values.

THE INTEGRATION OF ANALYTICAL HIERARCHY PROCESS AND DATA ENVELOPMENT ANALYSIS IN A MULTI-CRITERIA DECISION-MAKING PROBLEM

2006 ◽  
Vol 05 (02) ◽  
pp. 263-276 ◽  
Author(s):  
NORITA AHMAD ◽  
DANIEL BERG ◽  
GENE R. SIMONS
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Analytical Hierarchy Process ◽  
Data Envelopment ◽  
Multi Criteria Decision Making ◽  
Analysis Model ◽  
Decision Tool ◽  
Manufacturing Enterprises ◽  
Decision Making Problem ◽  
Hierarchy Process

This research focuses on developing a model that can be used to assess the performance of Small to Medium-Sized Manufacturing Enterprises (SMEs). The model will result from the integration of a decision tool called the Analytical Hierarchy Process (AHP) and a data analysis model called Data Envelopment Analysis (DEA). This research demonstrates that by eliminating flaws and taking advantage of each methodology's specific characteristics in identifying and solving problems, the new integrated AHP/DEA model appears to be a logical and sensible solution in multi-criteria decision-making problem.

scholarly journals Using Data Envelopment Analysis and Multi-Criteria Decision-Making Methods to Evaluate Teacher Performance in Higher Education

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 563 ◽  
Author(s):  
Milena Popović ◽  
Gordana Savić ◽  
Marija Kuzmanović ◽  
Milan Martić
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Data Envelopment Analysis ◽  
Conjoint Analysis ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Multi Criteria Decision Making ◽  
Weight Restrictions ◽  
Analytic Hierarchy ◽  
Discrimination Power

This paper proposes an approach that combines data envelopment analysis (DEA) with the analytic hierarchy process (AHP) and conjoint analysis, as multi-criteria decision-making methods to evaluate teachers’ performance in higher education. This process of evaluation is complex as it involves consideration of both objective and subjective efficiency assessments. The efficiency evaluation in the presence of multiple different criteria is done by DEA and results heavily depend on their selection, values, and the weights assigned to them. Objective efficiency evaluation is data-driven, while the subjective efficiency relies on values of subjective criteria usually captured throughout the survey. The conjoint analysis helps with the selection and determining the relative importance of such criteria, based on stakeholder preferences, obtained as an evaluation of experimentally designed hypothetical profiles. An efficient experimental design can be either symmetric or asymmetric depending on the structure of criteria covered by the study. Obtained importance might be a guideline for selecting adequate input and output criteria in the DEA model when assessing teachers’ subjective efficiency. Another reason to use conjoint preferences is to set a basis for weight restrictions in DEA and consequently to increase its discrimination power. Finally, the overall teacher’s efficiency is an AHP aggregation of subjective and objective teaching and research efficiency scores. Given the growing competition in the field of education, a higher level of responsibility and commitment is expected, and it is therefore helpful to identify weaknesses so that they can be addressed. Therefore, the evaluation of teachers’ efficiency at the University of Belgrade, Faculty of Organizational Sciences illustrates the usage of the proposed approach. As results, relatively efficient and inefficient teachers were identified, the reasons and aspects of their inefficiency were discovered, and rankings were made.

Introducing Hierarchical Particle Swarm Optimization to Optimal Part Orientation in Fused Deposition Modeling

2006 ◽  
Author(s):  
Amol Ghorpade ◽  
Yogesh Dashroa ◽  
M. K. Tiwari ◽  
K. P. Karunakaran
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Fused Deposition Modeling ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Fused Deposition ◽  
Critical Issues ◽  
Deposition Modeling ◽  
Efficient Alternative ◽  
Part Orientation

This article presents hierarchical particle swarm optimization algorithm to determine optimal part orientation for the complex parts produced by fused deposition modeling. Owing to the importance of efficient prototyping during product development phase, it is necessary to address critical issues involved in fused deposition modeling. The best part orientation is explored by taking into account volumetric error, build cost and orientational efficiency in the form of an aggregate objective. This paper exploits the search efficiency exhibited by hierarchical particle swarm optimization (HPSO), an optimization algorithm working on the basis of swarm intelligence, with the aim to resolve underlying optimal part orientation (OPO) problem. Further, in order to establish efficacy of HPSO a comparative study has been performed with a genetic algorithm based search. The results indicate outperforming behavior of HPSO and thus it is claimed to be a viable and efficient alternative to OPO problem.

Selection of Prototyping Process and Part Orientation for Virtually Manufactured Gears

2020 ◽  
pp. 353-369
Author(s):  
Divya Zindani ◽  
Kaushik Kumar
Keyword(s):  
Rapid Prototyping ◽  
Fused Deposition Modeling ◽  
Mechanical Analysis ◽  
Fused Deposition ◽  
Modeling Process ◽  
Product Profile ◽  
Deposition Modeling ◽  
Part Orientation ◽  
Profile Accuracy ◽  
Selection Of

This chapter explores transformation of a virtually produced gear to a physical product using rapid prototyping technique. The same can be segregated into two parts. The first being selection of the best possible rapid prototyping technique using dynamic mechanical analysis and the next was optimization of the process parameters of the selected rapid prototyping technique considering tensile strength as the criteria. The results indicated that fused deposition modeling process provides the best solution amongst the techniques studied. Moreover, as orientation of the product in rapid prototyping techniques plays an important role in providing the strength and also accuracy of the product profile, from results it was also ascertained that strength and profile accuracy of the product was optimized with horizontal position.

Selection of Prototyping Process and Part Orientation for Virtually Manufactured Gears

2018 ◽  
pp. 364-380
Author(s):  
Divya Zindani ◽  
Kaushik Kumar
Keyword(s):  
Rapid Prototyping ◽  
Fused Deposition Modeling ◽  
Mechanical Analysis ◽  
Fused Deposition ◽  
Modeling Process ◽  
Product Profile ◽  
Deposition Modeling ◽  
Part Orientation ◽  
Profile Accuracy ◽  
Selection Of

This chapter explores transformation of a virtually produced gear to a physical product using rapid prototyping technique. The same can be segregated into two parts. The first being selection of the best possible rapid prototyping technique using dynamic mechanical analysis and the next was optimization of the process parameters of the selected rapid prototyping technique considering tensile strength as the criteria. The results indicated that fused deposition modeling process provides the best solution amongst the techniques studied. Moreover, as orientation of the product in rapid prototyping techniques plays an important role in providing the strength and also accuracy of the product profile, from results it was also ascertained that strength and profile accuracy of the product was optimized with horizontal position.

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