Papers by Keyword: Material Selection

Abstract: Material selection of natural fiber for composite based products is an essential process in product design development especially in application of automotive components. Several factors need to be considered concurrently and dependency among the factors should be evaluated during the judgement. Therefore, a proposed approach is presented in this study by using Analytic Hierarchy Process/Analytic Network Process (AHP/ANP) to prioritize the criteria for material selection of natural fiber composites automotive components. AHP computes the priority values from pairwise comparison basis and ANP derives the global priority values based on the inner dependency of the criteria. As in a case study, flax fibers obtained the highest value (19%) and rank as number one fibers in the selection where tensile strength is the most significant criteria. Thus, application of AHP/ANP would derive a more reliable and accurate judgement in material selection and their flexibility allows integration with other decision making tools.

Abstract: Solid Oxide Fuel Cell (SOFC) systems are considered to be the most competitive green energy technology in the future because of their high energy conversion rates, low emissions and multiple fuels available. High temperature heat exchanger plays an important role in the system. The process system requires the design of heat exchangers to achieve operating temperature (700-800 °C), cross-temperature (>500°C) and low pressure drop in the smallest space, which is a challenge to the choice of materials. In this paper, the performances (Tensile strength, yield strength, linear expansion coefficient, and thermal conductivity coefficient) and price of high temperature alloy materials (304H, 310S, incoloy800H and Incoloy625) in the current application environment are compared. The applicable material (310S) of heat exchanger is determined. It provides a material basis for research and development of high temperature heat exchangers in SOFC system and commercialization.

Abstract: In this study, a novel fuzzy behavioral TOPSIS model was proposed. Sensitivity analysis is conducted according to the behavioral TOPSIS model parameter (λ) for the different case studies taken from the literature. The ranking results are slightly different according to different λ values. The results of the study can be used in material and manufacturing method selection problems.

Abstract: The materials in the skin care products have many types such as the whitening agent in the whitening cream. In general, researchers have conducted experiments to determine the effectiveness of such substances in the form of a single material in vitro. In practice, performance testing of material has conducted in Vivo that it is more than acceptable. In addition to use the materials altogether (synergistic) make higher performance or jump higher in a non-linear manner. The amount of these materials should be used in the right proportions. But to test the performance of materials in the real trial, each time it has a very high cost from volunteer, tracking, and duration of the experiment. We were unable to test the performance in several formulations. For this reason, the research objective is to develop algorithms to solve the problem of restrictions on such experiments to reduce time and cost. With a wide range of experimental design and use techniques to predict the outcome in early stage, then those results to design experiments and collect data. In this work, the effects of artificial neural networks (ANNs) to predict the effectiveness of the materials in whitening cream products were used incorporate with Genetic Algorithm (GA). In this article will experiment with simulated data from the experts as close to real data. To test the performance of the algorithm was developed and will extend the experimental results in the future. The algorithm of ANNs developed a multi-layer feed forward structure (4-13-1) with the lowest MSE is 6.00895e^-4 and largest R² is 0.979164. The best materials formulations optimized by GA were Arbutin=3%, Aloesin=0.658%, Niacinamide=0.007%, and Oxyresveratrol=0.993% that conduct lowest of 0.0823817 melanin value. Therefore, the algorithm developed in this study can be applied to develop the reality experiment in the future.

Abstract: It is well known fact that materials play an important role in engineering design. Nowadays over a hundred thousand available materials can be distinguished with constant tendency for increasing the novel designed materials. Therefore material selection process becomes a complex and time consuming task. Selection of the most suitable material for a given application can be regarded as a multi-criteria decision making (MCDM) problem with conflicting and diverse objectives. New MCDM methods have been developed, and existing methods improved, showing that research in the decision-making is important and still valuable. This paper describes the use of recently developed MCDM methods, i.e. Complex Proportional Assessment (COPRAS) and Weighted Aggregated Sum Product Assessment (WASPAS) for selecting the most suitable hard coating material.

Abstract: The first part of the work shortly describes possible mathematical methods for decision making. The paper gives an overview with general comments on multi-criteria problems, related to the preferences and the priorities of the decision-makers. The paper proposed and solves an example for material rating by a multiple attribute decision making. The MADM and PCA methodologies have been applied to rank out ten alternatives. Similar materials were selected using both techniques.

Abstract: The selection of the most desirable material contains many evaluation attributes, and thus leads to hard be solved. The material selection is actually a multiple attributes decision making problem, which has been studied by many authors. The aim of this study is to propose a new material selection method, which is an improved double base points method through defining the entropy weight and used the relative approach degree to measure the distance measures. The method may avoid the influence of subjective factors through the entropy weight, is very suitable for material selection problem. The applied example proves that the method is both effective and exercisable.

Abstract: The aim of this paper is to put forward a new material selection method based on COPRAS method. The method combines the COPRAS method and coefficient of variation method. The new method is simple and easy to use, and coefficient of variation method can objectively determine the attributes weights. Thus it can be easily accepted by decision makers. Finally, a practical example is used to demonstrate the feasibility and effectiveness of the proposed method.

Abstract: The aim of this paper is to develop a new method for the material selection problem, which is important for the product design. Material selection problem is actually a multi-attribute decision making (MADM) problem which contains many influence factors. The new material selection method is an extension of projection method with evaluation attribution values expressed with triangular fuzzy numbers. Coefficient of variation method is used to determine weights of evaluation attribute. A grinding wheel abrasive material selection problem is used to illustrate the effectiveness and practicability of the proposed method.

Abstract: Material selection is an important step of product design process. There are often several influence factors in the grinding wheel abrasive material selection problem. This article will put forward a fuzzy grey relation analysis method to the grinding wheel abrasive material selection problem which influences factor (evaluation attribute) values expressed with triangular fuzzy numbers. The Coefficient of variation method will be adopted to determine the evaluation attributes’ weight. Finally, an example is used to analysis the effectiveness and feasibility of the proposed method.