ADDITIVE MANUFACTURING PARAMETERS OPTIMIZATION OF Ti6AL4V ELI FOR MEDICAL IMPLANTS

Additive manufacturing (AM) of titanium (Ti) alloys has always fascinated researchers owing to its high strength to weight ratio, biocompatibility, and anticorrosive properties, making Ti alloy an ideal candidate for medical applications. The aim of this paper is to optimize the AM parameters, such as Laser Power (LP), Laser Scan Speed (LSS), and Hatch Space (HS), using Analysis of Variance (ANOVA) and Grey Relational analysis (GRA) for mechanical and surface characteristics like hardness, surface roughness, and contact angle, of Ti6Al4V ELI considering medical implant applications. The input parameters are optimized to have optimum hardness, surface roughness and hydrophilicity required for medical implants.

Parametric optimization of friction stir welding process parameters of dissimilar welded joints using grey relational analysis and desirability function approach

Purpose The main purpose of the present work is to study the multi response optimization of dissimilar friction stir welding (FSW) process parameters using Taguchi-based grey relational analysis and desirability function approach (DFA). Design/methodology/approach The welded sheets were fabricated as per Taguchi orthogonal array design. The effects of tool rotational speed, transverse speed and tool tilt angle process parameters on ultimate tensile strength and hardness were analyzed using grey relational analysis, and DFA and optimum parameters combination was determined. Findings The tensile strength and hardness values were evaluated from the welded joints. The optimum values of process parameters were estimated through grey relational analysis and DFA methods. Similar kind of optimum levels of process parameters were obtained through two optimization approaches as tool rotational speed of 1150 rpm, transverse speed of 24 mm/min and tool tilt angle of 2° are the best process parameters combination for maximizing both the tensile strength and hardness. Through these studies, it was confirmed that grey relational analysis and DFA methods can be used to find the multi response optimum values of FSW process parameters. Research limitations/implications In the present study, the FSW is performed with L9 orthogonal array design with three process parameters such as tool rotational speed, transverse speed and tilt angle and three levels. Practical implications Aluminium alloys are widely using in automotive and aerospace industries due to holding a high strength to weight property. Originality/value Very limited work had been carried out on multi objective optimization techniques such as grey relational analysis and DFA on friction stir welded joints made with dissimilar aluminium alloys sheets.

Mechanical and Thermomechanical Properties of Clay-Cowpea (Vigna Unguiculata Walp.) Husks Polyester Bio-Composite for Building Applications

This study investigates the feasibility of creating a clay polymer-based composite using cowpea husk (CPH) as filler for production of roof tiles. Polymeric composites were fabricated by mixing unsaturated polyester (UPT) resin with cowpea husk at different filler weights and curing. A hybrid composite was produced with the addition of 3 wt.% clay and all samples produced were subjected to flexural, hardness and dynamic mechanical analysis (DMA) tests. The effect of clay addition on the mechanical and thermo-mechanical behaviour of formulated composites was investigated. The morphological analysis of the mono and hybrid system shows a rough and coarse inhomogeneous surface with voids created due to the addition of CPH filler for the mono reinforced and clay uniformly filling the voids that were created by the CPH in the hybrid composite. It is observed that hardness, tensile modulus and flexural modulus of hybrid composites increase with an increase in the CPH contents, while the strength and flexural strength all decrease with filler content. The optimal composition was obtained using Grey relational analysis (GRA) at 18% CPH for both mono and hybrid composite. The results imply that the composite combination can be used in making rooftiles and/or also in applications where low strength is required.

Economic Indicators Selection for Property Crime Rates using Grey Relational Analysis and Support Vector Regression

Features selection is very important in the multivariate models because the accuracy of forecasting results produced by the model are highly dependent on these selected features. The purpose of this study is to propose grey relational analysis and support vector regression for features selection. The features are economic indicators that are used to forecast property crime rate. Grey relational analysis selects the best data series to represent each economic indicator and rank the economic indicators according to its importance to the property crime rate. Next, the support vector regression is used to select the significant economic indicators where particle swarm optimization estimates the parameters of support vector regression. In this study, we use unemployment rate, consumer price index, gross domestic product and consumer sentiment index as the economic indicators, as well as property crime rate for the United States. From our experiments, we found that the gross domestic product, unemployment rate and consumer price index are the most influential economic indicators. The proposed method is also found to produce better forecasting accuracy as compared to multiple linear regressions.

The effect of adding natural materials waste on the mechanical properties and water absorption of epoxy composite using grey relations analysis

Recently, there has been a tendency for scientific studies to deal with natural materials as fillers and reinforcement for polymer composites, which are used in many different applications due to their environmentally friendly properties when compared to synthetic materials. The current study aims to preserve the environment by dealing with natural materials and their influence on the mechanical properties and water absorption property of the polymer composites. In this study, epoxy composites were produced from local natural sourced non-hazardous raw natural materials using grey relational analysis (GRG). The materials used for fabrication include micro-filler of pollen palm 50 μm, seashell 75 μm and epoxy resin. Nine different composites were prepared using pollen palm and seashell as reinforcement material by varying the wt % of the micro-filler. Rule of the mixture was used for formulation and wt % of (0.5, 1 and 1.5) % reinforcement and 99.5, 99 and 98.5 % epoxy (binder) were used for composites. Grey relational analysis was conducted in order to scale the multi-response performance to a single response. The results indicate that optimum performance can be achieved with the addition of 1.5 wt % micro-filler of seashell, which achieved the first rank, while the second rank achieved by 0.5 wt % micro-filler of palm pollen and seashell when compared to other composites. The addition of micro-fillers has improved greatly the mechanical properties of epoxy composites. The loading of micro-fillers has influenced the water absorption property of composites based epoxy in ascending order

Grey Relational Analysis (GRA) as an Effective Method of Research into Social Preferences in Urban Space Planning

The appearance of urban space is most often determined by planners, urbanists, and officials who fail to consider social preferences in the planning process. According to recent scientific research, spatial design should take into account people’s preferences with regard to its shape, as it is they who are the target audience. Moreover, legal regulations in many countries require the public’s inclusion into the space planning process. This paper outlines the legal status of the issue of social participation in spatial planning and provides an overview of the methods and techniques applied in the research into preferences. The aim of the article is to determine the strength of the relationship between the features adopted for the study using the grey system theory and to investigate the model’s behaviour for varied input data. It also presents the results of a study into the effect of geospatial features on the perception of the sense of security within urban space. The features were extracted using a heuristic method for solving research problems (i.e., brainstorming) and the survey was conducted by the point-scoring method. The survey results were processed by the grey system method according to the grey system theory (GST) of the grey relational analysis (GRA) type to yield a sequence of the strength of dependence between the analysed features. The study was conducted five times, with the order of entering the survey results being changed. The conducted analyses indicated that a change in the order of data from particular surveys applied for calculations resulted in the order of the epsilon coefficients in the significance sequences being changed. The analysis process was modified in order to obtain a stable significance sequence irrespective of the order of entering survey results in the analysis process. The analysis results in the form of a geospatial feature significance sequence provide information as to which of them have the greatest impact on the phenomenon under consideration. The research method can be applied to solve practical problems related to social participation.