Papers by Keyword: Design of Experiment (DOE)

Abstract: The cervical spine is a structure subject to various vertebral injuries, namely, herniation of intervertebral discs and osteoporosis. Nowadays, several segments of society are vulnerable to these diseases that affect spine motion especially elderly people and women. Hence, various designs of cervical artificial discs are in use or under investigation claiming to restore the normal kinematics of the cervical spine. In this work, it is proposed to minimize the stress level by numerical size optimization in the Mobi-C cervical spine prosthesis to improve their biomechanical performances. For this aim, design of experiment (DoE) is employed as an optimization technique to investigate three geometrical parameters of the prosthesis design. Accordingly, DoE optimization allowed to minimize the equivalent stress value on Mobi-C from 20.3 MPa to 17.856 MPa corresponding to a percentage decrease of 12% from the original geometry. This provides an advantage for the durability of the prosthesis and also for the bone by reducing stress concentration.

Abstract: Utilization of natural fibers in a form of filler materials in composite structures has been successfully implemented in a broad range of industrial applications. In general, natural fibers have many advantages over synthetic counterparts, (e.g. glass and carbon) including lower density, ability to muffling vibration as well as its positive environmental impact. Hence, natural fibers can be used to enhance the characteristics of composite polymers. Expected improvements may include good thermal and acoustic insulating properties and better electrical resistance. However, in order to qualify any new developed material for commercialization, machining such as drilling, milling, cutting, bending, etc., becomes essential. In this experimental work, a newly developed Chopped Date Palm Fronds Polypropylene (CDPF/PP) bio-composite, which was mechanically characterized in a previous study, is investigated against conventional drilling operation. The data obtained through machining are processed and statistically analyzed based on Design of Experiment (DoE) to achieve the optimal input parameters using ANOVA and regression model. Moreover, the statistical evaluation of the results is useful to develop mathematical models that can be used with confidence to predict the drilling delamination for future works. In specific, optical microscopy was utilized to measure the dimension of the machined bio-composite surface to calculate the delamination factor.

Abstract: This study was aimed at finding appropriate levels of machine set up for small-sized rice milling machine in order to improve rice milling effectiveness. Small rice milling machines are used by farmers to reduce the reliance on commercial rice mill. However, they are found to produce greater quantities of broken rice grains than large-sized rice milling machine. This study investigated three factors of machine setup that would lead to smallest percentage of broken rice grains, i.e. size of hopper feed, gap adjuster, and outlet regulator. Each factor had three levels thus 3 x 3 factorial design was used to investigate the factors. It was found that all the three factors had significant impact on the number of broken grains. The optimum parameter settings that led to the smallest percentage of broken rice grains were as follows: size of hopper feed at 12 cm², gap adjuster at 5 mm, and outlet regulator at 5 cm.

Abstract: The Teflon coating on the hardened aluminum surface is the process of creating a film on the smooth surface which requires three layers of coating and each layer must be cured at a certain temperature. Due to a complexity of the process, peel off defect is one of the intimidate defects in the coating process. The objective of this research is, therefore to determine optimal coating parameters in order to reduce the peel off. A robot attached with a spray gun at the end effector is used to spray Teflon onto the hardened aluminum work-piece. Typically, there are three steps coating process i.e. primer, middle, and top. In this research, only the prime coating layer is studied due to the fact that the peel off defect normally occurs from this layer. A curing temperature immediately after coating is one of the root causes besides air pressure, an angle of the spray gun and fan pattern. Therefore, the experimental design technique is used to determine the relationship among these mentioned variables and identify the optimal condition. The 2^k factorial is used in the experimental design and analysis of variance is used to analyze the result. It is found that the optimal condition of curing temperature at 95 degree Celsius, air pressure at 2.5 bars, a gun angle at 60 degrees, and the fan size at 5 Volt setting at the robot controller provides a better result. The peel off defect is reduced from 2.88 to 1.60 percent.

Abstract: Energy consumption of buildings is increasing steadily and occupying approximately 30-40% of total energy use. It is important to predict heating and cooling loads of a building in the initial stage of design to find out optimal solutions among various design options, as well as in the operating stage after the building has been completed for energy efficient operation. In this paper, an artificial neural network model has been developed to predict heating and cooling loads of a building based on simulation data for building energy performance. The input variables include relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, and glazing area distribution of a building, and the output variables include heating load (HL) and cooling load (CL) of the building. The simulation data used for training are the data published in the literature for various 768 residential buildings. ANNs have a merit in estimating output values for given input values satisfactorily, but it has a limitation in acquiring the effects of input variables individually. In order to analyze the effects of the variables, we used a method for design of experiment and conducted ANOVA analysis. The sensitivities of individual variables have been investigated and the most energy efficient solution has been estimated under given conditions. Discussions are included in the paper regarding the variables affecting heating load and cooling load significantly and the effects on heating and cooling loads of residential buildings.

Abstract: Metal injection moulding has gain much attention due to flexibility and high productivity of the plastics injection moulding with the powder metallurgy method of sintering. In order to gain better shape retention, optimum density of green part is required. This paper deals with the application of Taguchi optimisation technique on getting the optimum density for Metal Injection Moulding (MIM) components base on certain parameters in process injection. For this purposes only 3 process parameters were considered here including its interactions which are injection pressure, injection temperature and mould temperature. Since its more close to the final products these parameters were selected and other parameters will be kept constant. An orthogonal array of L16 experimental base design was conducted. Confirmation test will be done base on Signal-to-Noise (S/N) ratio and it Means.

Abstract: The improvement of the quality of the surface roughness of the polyurethane board (PB) has always been a challenge in the automotive industry. A suitable combination of the milling parameters is very important in order to get a high grade of smoothness specially when dealing with complex designs such as curved profiles. In this paper, a half factorial design of experiment (DoE) with 16 runs at two levels is applied in the milling operation of the checking fixtures of a car seat belt bracket under a dry cutting condition. The Feed rate, Depth of cut, Spindle speed, Step over and Plunge rate were taken as the variables for the DoE. Two different milling tools, a flat end mill of diameter10 mm for roughing, and a ball nose of diameter 5 mm for the finishing process were used. Minitab software was use to analyze the correlation between the parameters and the surface roughness. The most influential factor in the milling process was observed to be the Step over.

Abstract: Tolerance design plays a very important in any manufacturing process because this activity directly influences products cost and quality. In design activity the designer solve the quality problems selecting tight tolerances for components but this generates cost increasing. The practical problem is to assure the high quality characteristics using the maximum tolerances for components that influence them. The paper’s aim is to find optimal parameters setting which assure the desire value of quality characteristics using the DoE (Design of Experiments), and to find a mathematical model and a respective quality characteristic function of the parameters that it was influenced. Using the mathematical function, by imposing the desired tolerance for quality characteristic, it will be allocated the optimal tolerance for components. This tolerance allocation will be verified using Monte-Carlo method.

Abstract: In order to improve the mechanical properties of the layer deposited by anodic oxidation of aluminum on the material EN AW-1050 H24, in the contribution was investigated the microhardness of the deposited layer as a function of the physic-chemical factors affecting in the process of anodic oxidation at the constant anodic current density J = 3 A.dm^-2 in electrolyte formed by sulfuric acid and oxalic acid, with the emphasis on the influence of electrolyte temperature in the range – 1,78 °C to 45,78 °C. The model of the studied dependence was compiled based on mathematical and statistical analysis of matrix from experimental obtained data from composite rotation plan of experiment with five independent variable factors (amount of sulfuric acid in the electrolyte, the amount of oxalic acid in the electrolyte, electrolyte, anodizing time and applied voltage).

Abstract: This paper investigates the performance of design of experiment (DOE) in response surface methodology (RSM) for vibration-based damage detection. The ability of three major types of DOE, namely central composite design (CCD), Box-Behnken (BBD) and D-optimal (Dopt) for damage detection based on modal frequency are investigated and compared. A procedure comprising three main stages—sampling, response surface (RS) modelling and model updating—are employed for damage localisation and quantification. By considering Young’s modulus and modal frequency as respective input and output, a set of samples is generated from each DOE. Full quadratic functions are considered in RS modelling while model updating is performed for damage detection. The performances of DOE are compared based on damage detectability. A numerical simply supported beam is used as case study by considering several single damage cases. The results show that CCD provides better prediction compared to other DOEs.