• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.183-188
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• 2005

Although it is widely used to find an optimum setting of manufacturing process parameters in a variety of engineering fields, the Taguchi method has a difficulty in dealing with multi-response situations in which several response variables should be considered at the same time. For example, electrode wear, surface roughness, and material removal rate are important process response variables in an electrical discharge machining (EDM) process. A simultaneous optimization should be accomplished. Many researches from various disciplines have been conducted for such multi-response optimizations. One of them is a fuzzy logic approach presented by Lin et al. [1]. They showed that two response characteristics are converted into a single performance index based upon fuzzy logic. However, it is pointed out that information regarding relative importance of response variables is not considered in that method. In order to overcome this problem, a desirability function can be adopted, which frequently appears in the statistical literature. In this paper, we propose a novel approach for the multi-response optimization by incorporating fuzzy logic into desirability function. The present method is illustrated by an EDM data of Lin and Lin [2].

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.434-435
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• 2012

Plasma enhanced chemical vapor deposition (PECVD) silicon dioxide thin films have many applications in semiconductor manufacturing such as inter-level dielectric and gate dielectric metal oxide semiconductor field effect transistors (MOSFETs). Fundamental chemical reaction for the formation of SiO2 includes SiH4 and O2, but mixture of SiH4 and N2O is preferable because of lower hydrogen concentration in the deposited film [1]. It is also known that binding energy of N-N is higher than that of N-O, so the particle generation by molecular reaction can be reduced by reducing reactive nitrogen during the deposition process. However, nitrous oxide (N2O) gives rise to nitric oxide (NO) on reaction with oxygen atoms, which in turn reacts with ozone. NO became a greenhouse gas which is naturally occurred regulating of stratospheric ozone. In fact, it takes global warming effect about 300 times higher than carbon dioxide (CO2). Industries regard that N2O is inevitable for their device fabrication; however, it is worthwhile to develop a marginable nitrous oxide free process for university lab classes considering educational and environmental purpose. In this paper, we developed environmental friendly and material cost efficient SiO2 deposition process by substituting N2O with O2 targeting university hands-on laboratory course. Experiment was performed by two level statistical design of experiment (DOE) with three process parameters including RF power, susceptor temperature, and oxygen gas flow. Responses of interests to optimize the process were deposition rate, film uniformity, surface roughness, and electrical dielectric property. We observed some power like particle formation on wafer in some experiment, and we postulate that the thermal and electrical energy to dissociate gas molecule was relatively lower than other runs. However, we were able to find a marginable process region with less than 3% uniformity requirement in our process optimization goal. Surface roughness measured by atomic force microscopy (AFM) presented some evidence of the agglomeration of silane related particles, and the result was still satisfactory for the purpose of this research. This newly developed SiO2 deposition process is currently under verification with repeated experimental run on 4 inches wafer, and it will be adopted to Semiconductor Material and Process course offered in the Department of Electronic Engineering at Myongji University from spring semester in 2012.

• Steel and Composite Structures
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• v.34 no.5
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• pp.681-698
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• 2020

The paper addresses contribution to the modeling and optimization of major machinability parameters (cutting force, surface roughness, and tool wear) in finish dry hard turning (FDHT) for machinability evaluation of hardened AISI grade die steel D₃ with PVD-TiN coated (Al₂O₃-TiCN) mixed ceramic tool insert. The turning trials are performed based on Taguchi's L₁₈ orthogonal array design of experiments for the development of regression model as well as adequate model prediction by considering tool approach angle, nose radius, cutting speed, feed rate, and depth of cut as major machining parameters. The models or correlations are developed by employing multiple regression analysis (MRA). In addition, statistical technique (response surface methodology) followed by computational approaches (genetic algorithm and particle swarm optimization) have been employed for multiple response optimization. Thereafter, the effectiveness of proposed three (RSM, GA, PSO) optimization techniques are evaluated by confirmation test and subsequently the best optimization results have been used for estimation of energy consumption which includes savings of carbon footprint towards green machining and for tool life estimation followed by cost analysis to justify the economic feasibility of PVD-TiN coated Al₂O₃+TiCN mixed ceramic tool in FDHT operation. Finally, estimation of energy savings, economic analysis, and sustainability assessment are performed by employing carbon footprint analysis, Gilbert approach, and Pugh matrix, respectively. Novelty aspects, the present work: (i) contributes to practical industrial application of finish hard turning for the shaft and die makers to select the optimum cutting conditions in a range of hardness of 45-60 HRC, (ii) demonstrates the replacement of expensive, time-consuming conventional cylindrical grinding process and proposes the alternative of costlier CBN tool by utilizing ceramic tool in hard turning processes considering technological, economical and ecological aspects, which are helpful and efficient from industrial point of view, (iii) provides environment friendliness, cleaner production for machining of hardened steels, (iv) helps to improve the desirable machinability characteristics, and (v) serves as a knowledge for the development of a common language for sustainable manufacturing in both research field and industrial practice.

• Journal of Dental Rehabilitation and Applied Science
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• v.38 no.1
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• pp.18-25
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• 2022

Purpose: This study aimed to evaluate the color stability and antibacterial properties of the surface of polyethyl methacrylate (PEMA) resin with zirconia nanoparticles added. Materials and Methods: The control group was pure PEMA resin, and the experiment group was PEMA resin 15 mm in diameter and 2.5 mm in thickness disk-shaped specimens with 2, 4 and 8 w/v% of zirconia nanoparticles added, which were respectively divided into Group Z2, Group Z4, and Group Z8. After analyzing the surface roughness and color stability of the specimens, their antibacterial properties were evaluated using Porphyromonas gingivalis (P. gingivalis). The Statistical analysis was performed using when normality was met in the Shapiro-Wilk test, one-way ANOVA was used to test parameters, and Tukey's test was used as a post hoc test. When normality was not met, the Kruskal-Wallis test, a non-parametric test was used (P < 0.05). Results: The surface roughness measurement found that there was no significant difference between the experimental and control groups. The color stability evaluation showed that the Z2, Z4, and Z8 groups were within the color range of natural teeth. The adhesion of P. gingivalis was evaluated to be significantly reduced in Group Z2 compared to the control group (P < 0.05). In the Z2 group, Z4 group, and Z8 group, dead cells bacteria than the control group were observed. Conclusion: In conclusion, PEMA resin with zirconia nanoparticles added was within the range of natural teeth in color and reduced the adhesion of P. gingivalis.