Development of biodegradable composite micro-perforated panel made from natural fibre composites with evaluation of its acoustic and mechanical properties

Micro-perforated panel (MPP) has been widely considered as a promising alternative for sound absorption purposes. Plenty of research has been done to improve the sound absorption of MPP but no specific work highlights the material structure effect towards its sound absorption performance. MPP is mostly made from metallic or plastic materials which does not exhibits any pores or tortuous structure and therefore, material structure issue is often being eliminated from analysis. In order to study the material structure effect, alternative material must be used to fabricate MPP. Numerous research found that natural fibre possesses excellent sound absorption properties due to its porous and tortuous structure. Yet, natural fibre has low tolerance towards mechanical processing and thus binder must be incorporated to overcome this shortcoming. This thesis basically describes the development process of biodegradable composite micro-perforated panel (BC-MPP) made from natural fibre (kenaf, wood, and coconut) and polylactic acid (PLA) composites. BC-MPP samples were fabricated with different material composition percentage of natural fibre and PLA. The effect of material composition percentage, perforation ratio, perforation diameter, and air cavity thickness were investigated. The effect of material structure towards the sound absorption performance of BC-MPP sample was studied. It has been found that existence of pores and tortuous structure can indeed influence the sound absorption performance of BC-MPP sample. The sound absorption performance of BC-MPP sample was compared to conventional MPP and it has been found that BC-MPP possessed better sound absorption performance courtesy to its porous and tortuous structure. BC-MPP sample also possessed better tensile strength compared to common sound absorption panel such as medium density fibreboard, hardboard, commercial ceiling board, and plywood

Modeling and optimization of cold extrusion process by using response surface methodology and metaheuristic approaches

Obtaining the optimal extrusion process parameters by integration of optimization techniques was crucial and continuous engineering task in which it attempted to minimize the tool load. The tool load should be minimized as higher extrusion forces required greater capacity and energy. It may lead to increase the chance of part defects, die wear and die breakage. Besides, optimization may help to save the time and cost of producing the final product, in addition to produce better formability of work material and better quality of the finishing product. In this regard, this study aimed to determine the optimal extrusion process parameters. The minimization of punch load was the main concern, in such a way that the structurally sound product at minimum load can be achieved. Minimization of punch load during the extrusion process was first formulated as a nonlinear programming model using response surface methodology in this study. The established extrusion force model was then taken as the fitness function. Subsequently, the analytical approach and metaheuristic algorithms, specifically the particle swarm optimization, cuckoo search algorithm (CSA) and flower pollination algorithm, were applied to optimize the extrusion process parameters. Performance assessment demonstrated the promising results of all presented techniques in minimizing the tool loading. The CSA, however, gave more persistent optimization results, which was validated through statistical analysi

Diameter prediction and optimization of hot extrusion-synthesized polypropylene filament using statistical and soft computing techniques

In this study, statistical and soft computing techniques were developed to investigate effect of process parameters on diameter of extruded filament made of polypropylene in hot extrusion. A multi-factors experiment was designed with process parameters of screw speed, roller speed and die temperature. According to the design matrix, twenty four experiments were conducted. The diameter of the extruded plastic filament was measured in each experiment. Subsequently, statistical analysis was used to identify significant factors on diameter of extruded filament. Predictive models of response surface methodology (RSM) and radial basis function neural network(RBFNN)were applied to predict the diameter of extruded filament. The optimal process parameters to maintain the diameter of the filament closest to the target value were identified using the cuckoo search algorithm (CSA), and particle swarm optimization (PSO). Performance analysis demonstrated the superior predictive ability of both models, in which the prediction errors of 0.0245 and 0.0029 (in terms of mean squared error) were obtained byRSM and RBFNN, respectively. Considering the optimization methods, the optimization approaches of using CSA and PSO were promising, in which average relative error of 1.28% was obtained in confirmation tests

Sound absorption of microperforated panel made from coconut fiber and polylactic acid composite

This paper highlights the sound absorption performance of microperforated panel (MPP) made from coconut fiber and polylactic acid (PLA) composite named as biocomposite microperforated panel (BMPP). Coconut fiber was used to produce BMPP specimen and PLA was used as matrix. Impedance tube method was employed to identify the sound absorption performance of BMPP specimen while a porosity tester was used to determine the porosity of BMPP specimen. Comparison on the sound absorption performance between BMPP and steel MPP will be discussed in this paper. It has been found that BMPP with different composition percentage of coconut fiber and PLA possessed different sound absorption performance mainly due to the existence of pores and tortuous structure within the specimen itself. Scanning electron microscope (SEM) scan was performed to further analyze the structure of BMPP specimen

Effect Of Thickness And Infill Density On Acoustic Performance Of 3D Printed Panels Made Of Natural Fiber Reinforced Composites

Additive manufacturing (AM) of Natural Fiber-Reinforced Composites through Fused Deposition Modeling is receiving much attention in recent years. AM is very appealing for complex shape structures that can be inconvenient to produce by other methods. In this study, the acoustic panel made from polylactic acid reinforced with wood fiber composite was 3D printed by varying its thickness and infill density. The sound absorption coefficient was measured using an impedance tube. The thin panel with back air gap was found to absorb sound at mid-frequency range resembling the Helmholtz resonator. The absorption performance for the thick panel can be controlled by controlling the infill density of the panel. Customizing the acoustic absorption is therefore possible for panels from biodegradable materials by A