Optimisation of Processing Condition Using Taguchi Method on Strength of HDPE-Natural Fibres Micro Composite

Ibrahim, Mohd Halim Irwan; Zainol, M.Z.R.; Othman, Mohd Hilmi; Amin, Azriszul Mohd; Asmawi, Rosli; Sa’ude, Nasuha

doi:10.4028/www.scientific.net/amm.660.33

Cited by 7 publications

(5 citation statements)

References 5 publications

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“…Ibrahim et al claimed that changes in the injection parameter setting give difference tensile strength of HDPE/kenaf composite. Optimization technique using Taguchi method has been implement in their study and defined that melt temperature was the most significant parameter [3]. Tuo et al approached the optimum parameters on mechanical properties of kenaf fiber-reinforced composites using Taguchi method of experimental design.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Injection Parameters of Kenaf Filler Polypropylene Composite by Taguchi Method

Radzi

Muhamad²,

Sulong³

et al. 2017

MSF

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Optimization of injection molding parameters provided a solution to achieve strength improvement of kenaf filler polypropylene composites. Since, molded polymers composites possibility being effected by machine parameters and other process condition that may cause poor quality of composites product. Thus in this study, composite of kenal filler reinforced with thermoplastic polypropylene (PP) were prepared using a sigma blade mixer, followed by an injection molding process. To determine the optimal processing of injection parameters, Taguchi method with L27 orthogonal array was used on statistical analysis of tensile properties of kenaf/PP composites. The results obtained the optimum parameters which were injection temperature 190°C, injection pressure 1300 bar, holding pressure 1900 bar and injection rate 20cm3/s. From the analysis of variance (ANOVA), both flow rate and injection temperature give highest contribution factor to the mechanical properties of the kenaf/PP composites.

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Section: Introductionmentioning

confidence: 99%

Optimizing Injection Parameters of Kenaf Filler Polypropylene Composite by Taguchi Method

Radzi

Muhamad²,

Sulong³

et al. 2017

MSF

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“…Process parameters (e.g., injection pressure and speed, melt and mold temperatures, cooling and holding time, and holding pressure) can strongly affect the mechanical properties, such as tensile strength and hardness (Gaaz et al 2016). In this optimization process, three different levels were employed to determine four notable molding parameters that affected the tensile strength and hardness values, which were melting temperature, injection pressure, injection speed, and cooling time, as presented in Table 2 (Ibrahim et al 2014). These parameters were chosen based on the machine setting capabilities.…”

Section: Specimen Preparationmentioning

confidence: 99%

Integration of Taguchi-Grey relational analysis technique in parameter process optimization for rice husk composite

Mohamed

Zainudin

Sapuan

et al. 2018

BioRes

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Injection molding is a widely used manufacturing process operation that generates polymer products. The selection of optimal injection molding process settings is essential due to the distinct influences of process parameters on polymeric material behavior and quality, particularly during the injection process. Therefore, it is vital to determine the optimized process parameters to enhance the mechanical properties of the products and ensure the most favorable performance. This paper examined the integration of Taguchi’s method with grey relational analysis (GRA) to determine the effects of varied injection molding parameters on the mechanical properties such as tensile strength and hardness values. The experiments were designed using Taguchi’s L9 orthogonal array after weighing in control factors, such as melting temperature, injection pressure, injection speed, and cooling time. The GRA revealed that the multiple responses correlation was successfully established. Finally, an analysis of variance was performed to validate the test outputs. The results revealed that the most inﬂuential factor was injection pressure, sequentially followed by melting temperature, cooling time, and injection speed.

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“…Few studies have focused on optimizing the compression molding process parameters of NFPCs manufacturing [11,[15][16][17][18]. Taguchi design of experiment (DOE) is the most commonly used method for optimizing the processing parameters of both compression molding [11,17] and injection molding [19,20]. Selmat et al [11] determined the optimum compression molding parameters for obtaining the highest tensile strength from a pineapple leaf fiber-PP composite.…”

Section: Introductionmentioning

confidence: 99%

“…The reported optimum parameters were 180 • C temperature, 50 rpm speed, 13 min time, and 125-300 µm fiber size. Ibrahim et al [20] employed the Taguchi approach to find the best combination of processing parameters using orthogonal array (OA) and signal-to-noise (S/N) ratio.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Compression Molding Process Parameters for NFPC Manufacturing Using Taguchi Design of Experiment and Moldflow Analysis

2021

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This paper presents the application of Taguchi design of experiment and Autodesk Moldflow® simulation in finding the optimal processing parameters for the manufacturing of natural fiber–polymer composite products. The material used in the study is a composite of recycled thermoplastic reinforced with 10% wood fibers. For the study, four critical processing parameters, namely compression time, mold temperature, melt temperate, and pressure, were selected for optimization. Process analysis was carried out in Moldflow® utilizing a combination of process parameters based on an L9 orthogonal array. Later, the warpage output from Moldflow® simulation was converted into a signal-to-noise (S/N) ratio response, and the optimum values of each processing parameter were obtained using the smaller-the-better quality characteristic. The results show that the optimum values were 60 °C, 40 s, 210 °C, and 600 kN for the mold temperature, compression time, melt temperature, and pressure, respectively. Afterward, a confirmation test was performed to test the optimum parameters. Using analysis of variance (ANOVA), melt temperature was found to be the most significant processing parameter, followed by mold temperature, compression time, and pressure.

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Optimisation of Processing Condition Using Taguchi Method on Strength of HDPE-Natural Fibres Micro Composite

Cited by 7 publications

References 5 publications

Optimizing Injection Parameters of Kenaf Filler Polypropylene Composite by Taguchi Method

Optimizing Injection Parameters of Kenaf Filler Polypropylene Composite by Taguchi Method

Integration of Taguchi-Grey relational analysis technique in parameter process optimization for rice husk composite

Optimization of Compression Molding Process Parameters for NFPC Manufacturing Using Taguchi Design of Experiment and Moldflow Analysis

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