Available online at ScienceDirect. Procedia Engineering 184 (2017 )

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1 Available online at ScienceDirect Procedia Engineering 184 (2017 ) Advances in Material & Processing Technologies Conference Optimisation of Injection Moulding Parameter towards Shrinkage and Warpage for Polypropylene-Nanoclay-Gigantochloa Scortechinii Nanocomposites M.H. Othman, S. Hasan, S.Z. Khamis, M.H.I Ibrahim, S.Y. M.Amin Department of Manufacturing and Industrial Engineering, Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor Darul Takzim, Malaysia Abstract The setting of suitable parameter's level and values were very crucial in determining the quality characteristic of the injection moulding's product, especially made from advanced polymer nanocomposites. Therefore, this research was proposed to optimise the injection moulding parameters towards the quality characteristics of samples made from polypropylene-nanoclay- Gigantochloa Scortechinii fibers. The quality characteristics that need to be controlled were shrinkage and warpage, and the selected parameters were packing pressure, barrel temperature, screw speed and filling time. The Gigantochloa Scortechinii fibers need to be preheated at C first, and then mixed with polypropylene, polypropylene grafted maleic anhydride and nanoclay through the compounding process by using Brabender Plastograph. The injection moulding process was performed based on the orthogonal array from Taguchi Optimisation Method. According to the results, the value of warpage was reduced when the fiber content was increased from 1 wt. % to 3 wt. %. The warpage value changed from 0.025mm to 0.009mm. The optimum parameter for warpage were 175 C barrel temperature, 40% packing pressure, % screw speed and 2 seconds filling time for both 1 wt. % and 3% of GS fiber. However, in terms of shrinkage, the increment of fiber content doesn't have much impact towards the response. The value of shrinkage was reduced but not significantly from mm to mm when the percentage of fiber was added. The optimum parameter for 1 wt. % fiber to control shrinkage are 170 C melt temperature, % packing pressure, % screw speed and 2 seconds of filling time. The findings of this research will be valuable for quality control and references for products made from polypropylene-nanoclay-gigantochloa Scortechinii fibers The The Authors. Authors. Published Published by Elsevier by Elsevier Ltd. This Ltd. is an open access article under the CC BY-NC-ND license ( Peer-review under responsibility of the organizing committee of the Advances in Material & Processing Technologies Peer-review Conference. under responsibility of the organizing committee of the Urban Transitions Conference Keywords: Injection moulding; polypropylene; nanoclay; Gigantochloa Scortechinii; Taguchi Optimisation Method; shrinkage; warpage The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( Peer-review under responsibility of the organizing committee of the Urban Transitions Conference doi: /j.proeng

2 674 M.H. Othman et al. / Procedia Engineering 184 ( 2017 ) Nomenclature α GS h L L c L m NC gma S SN t T ambient T mould Z coefficient of thermal expansion barrel temperature filling time Gigantochloa Scortechinii height of sample length of sample (dimension) length of sample (cavity mould) length of sample (measured) nanoclay polypropylene polypropylene-grafted-maleic anhydride shrinkage signal to noise screw speed thickness of sample temperature (ambient) temperature (mould) warpage 1. Introduction Injection moulding is one of the methods that were highly regarded in the industry. This is because, this method can produce in large of quantities and also can save the time and cost to produce a product. However, an optimized processing condition is vital to ensure the desired properties of the product can be achieved [1]. In terms of Optimisation, Taguchi Optimisation Method had introduced several statistical approaches to define the optimum processing condition as well as the most contributable factor towards the selected responses. In the injection moulding process, several established researchers have achieved great results by adopting this method. Previous researchers have clearly defined the effect of parameters towards various types of response and material [2-6]. A number of past researches which are related to this project also have been performed by the author [7-13], whereby the findings shall be used as the guidance for selecting the factors and level in this study. A review had mentioned that polypropylene-nanoclay has become more commonly developed polymer composites due to the polypropylene and clay were widely used, naturally abundant and high aspect ratio [14]. As for further reference, the author had made a review about the preparation, properties and the application of polypropylene-nanoclay polymer nanocomposites [15]. However, the effects of clay content, the mixing of other fillers and the selection of appropriate parameters have been always the issues that affect the properties of the injected mould artefacts [16]. 2. Experimental The block diagramofr the experiment for the experiment process was shown in Fig.1. Fig 1. Block Diagram of the Experiment Processes.

3 M.H. Othman et al. / Procedia Engineering 184 ( 2017 ) Material Preparation The materials used in this study were divided into two different composites, which was 1 wt. % and the other one was 3 wt. % of GS fiber. The other materials were polypropylene (), the compatibilizer which was polypropylenegrafted-maleic anhydride (gma) and nanoclay (NC). These mixtures were measured based on the formulation (wt. %) as shown in Table 1. Table 1. The Formulation of Nanocomposites Compounding. Formulation gma NC GS 1 79wt% 15wt.% 5wt.% 1wt.% 2 77wt% 15wt.% 5wt.% 3wt.% The material preparation starts from processing the fibers. The fibers was chopped and refined to become short fibers, as shown in Fig.2. Then, the GS fibers need to be pre-heated at temperature 120 C. The process of mixing was made by using a twin screw Brabender Lab-Compounder KETSE 20/40 and pallets were produced by using Brabender pelletizer with diameters of 1 to 4 mm specifically for the injection moulding process. (a) (b) Fig 2. (a) GS fibers before blended; (b) GS fibers in powder form 2.2. Injection Moulding and Orthogonal Array In this study, the injection moulding process using 0.7 tonne Nissei NP7-1F machine (Fig. 3) was the primary method for producing a tensile specimen using mould dog bone shaped. The Taguchi Optimisation Method that was chosen for this study was L (9 trials, 3 levels, and 4 factor parameters). This method was preferred in order to find the optimal values of the process to improve the quality characteristics. Fig 3. Injection moulding machine Nissei NP7-1T type

4 676 M.H. Othman et al. / Procedia Engineering 184 ( 2017 ) The parameters that were chosen are barrel temperature (); packing pressure (), screw speed () and filling time (). These four factors of injection moulding parameters were selected with three different levels which was low, medium and high. Tensile sample was injected mould from the experiment to be tested. There are 27 samples for 9 trials have been tested. The effects of several parameters based on the Taguchi s orthogonal design were determined effectively from the matrix of experiments. As for the orthogonal array for this experiment, the detail was stated in Table Measuring the shrinkage and warpage Table 2. The orthogonal array using Taguchi Method ( 0 C) (%) (%) (s) % of Packing Pressure equals to 1.6 MPa. 1 % of Screw Speed equals to 2.4 rpm. Warpage and shrinkage were related to each other. Warping is the result of the different shrinkage. This can be occurred due to several parameters which were expensive packing, fill rate too low, melt temperature too low and partially ejected too hot [1]. Warpage and shrinkage were chosen for optimisation by controlling the injection moulding parameter. These quality characteristics were measured on specimens after the injection moulding process was performed. The specimen that have been ejected from the mould need to be cleared from flashing and runner before measuring the specimen. Shrinkage was measured using two equations, first by finding the value of, and then used the specific equation to find the value of shrinkage. The equation are stated in equation (1) and (2), where, is the actual mould cavity length, is the average of actthe coefficientlength, α is coefficieofof thermal expansion for tool steel with value (6.45x10-6/ F ) is the mould temperature, and is the ambient temperature. (1) (2) After obtaining the required data the warpage of a specimen or deflection, the value of warpage plate will be calculated using equation (3) where, is the warpage of the plate, refer to the maximum of the plate and is the average plate thickness. (3)

5 M.H. Othman et al. / Procedia Engineering 184 ( 2017 ) Measuring the Signal to Noise ratio and Optimisation In this experiment, by adopting the Taguchi Optimisation Method, the signal to noise (SN) ratio need to be measured. The outcomes that need to be monitored in this study was the result of warpage and shrinkage which was influenced by the setting of parameters. The SN ratio for small the better quality characteristics was usually used for warpage and shrinkage as the desired output. The formula for the SN ratio is in a logarithmic function. The equation for the SN ratio specifically for smaller the better characteristics is [17]. Where is the value of observed data (warpage and shrinkage), is the number of observations. By using Statistical software-minitab version16, the data of signal to noise ratios were obtained To gain the optimized factors, the signal to noise response graph was constructed to find the optimum level from four factors and three levels based on the data taken from the warpage and shrinkage test. The highest value of the SN ratio indicates the best setting for the selected factors. The ranks of the most influential factors also have been obtained from the software. 3. Results and Discussion 3.1 Warpage Result Based on Table 3, the average warpage based on the trials have been attained. From the results, the lowest warpage for 1 wt. % of GS fiber achieved was mm on the trial no 9. As for the 3 wt. % of GS fiber, the lowest warpage was mm on the trial no. 7. Based on these results, it can be concluded that the increment of GS fibers content had reduced the warpage value. 3.2 Shrinkage Result Founded from Table 3, the average shrinkage values based on the trials have been attained. From the result, the lowest shrinkage value achieved was mm for the trial no 2, specifically for the compounding of 1 wt. % of GS fiber. As for the 3 wt. % of GS fiber, the lowest shrinkage was mm on the trial no. 6. These findings show that the increment of GS fibers doesn't have much effect towards shrinkage. 3.3 SN Ratio and Main Plot Effects Result Table 3 shows the SN ratio value for each trial of the experiment according to the GS fiber content. The best value is dbi for warpage and dBi for shrinkage for 1 wt. % of GS fiber. As for the 3 wt. % of GS fiber the best value is dbi for warpage at the trial number 7 while dbi for shrinkage on the trial number 6. Fig. 4 shows the main effects plot for SN ratios specifically for warpage with 1 wt. % GS. Based on this plot, the most influential factor was barrel temperature and then followed by filling time. Temperature is very important among the selected injection moulding parameter. It was due to the higher setting of temperature might contribute to poorer mechanical properties [18]. However, the most influential factor that controlling the warpage for 3 wt. % GS was not barrel temperature. According to Fig. 5, it was filling time, and then followed by screw speed. The changes happened was paralleled with the findings that the additional of GS fibers can reduce the value of warpage. Fig. 6 shows the main effects plot for SN ratios specifically for shrinkage with 1 wt. % GS. Based on this plot, the most influential factor was filling time and then followed by packing pressure. As for 3 wt. GS, the most influential factor was screw speed, as shown in Fig. 7. The changes happened, maybe due to the parameter setting was found to be slightly changed with the presence of nanoclay [13] and the changes of polymer molecular crystallinity was well as the orientation of fibers [18]. The defects such as warpage and shrinkage should be able to be reduced by choosing the right parameter setting, as well as with the additional of nanoclay [13]. (4)

6 678 M.H. Othman et al. / Procedia Engineering 184 ( 2017 ) Trial Table 3. Results of Warpage, Shrinkage and their SN ratio 79 wt. %, 15 wt. % gma, 5 wt. % NC, 1 wt. % GS. 77 wt. %, 15 wt. % gma, 5 wt. % NC, 3 wt. % GS. Z(mm) SN Z (dbi) S (mm) SN S(dBi) Z(mm) SN Z (dbi) S (mm) SN S(dBi) Main Effects Plot for SN Ratios Warpage 1 wt. % GS Main Effects Plot for SN Ratios Warpage 3 wt.% GS Mean of SN ratios Mean of SN ratios Signal-to-noise: Smaller is better Signal-to-noise: Smaller is better Fig 4. Main Effects Plot for SN Ratios- Warpage with 1 wt. % GS Fig 5. Main Effects Plot for SN Ratios- Warpage with 3 wt. % GS Main Effects Plot for SN Ratios Shrinkage 1 wt.% GS Main Effects Plot for SN Ratios Shrinkage 3 wt.% GS Mean of SN ratios Mean of SN ratios Signal-to-noise: Smaller is better Signal-to-noise: Smaller is better Fig 6. Main Effects Plot for SN Ratios- Shrinkage with 1 wt. % GS Fig 7. Main Effects Plot for SN Ratios- Shrinkage with 3 wt. % GS

7 M.H. Othman et al. / Procedia Engineering 184 ( 2017 ) Optimisation of Shrinkage and Warpage Table 4 shows the optimisation of warpage and shrinkage for compounding 79 wt. %, 15 wt. % gma, 5 wt. % NC, 1 wt. % GS. Based on this table, the optimum values for warpage were C for barrel temperature; 40% for packing pressure, % for screw speed and 2 seconds for filling time. The values were same for 3 wt. % GS, as shown in Table 5. As for the optimisation of shrinkage, the optimum values were C for barrel temperature; % for packing pressure, % for screw speed and 2 seconds for filling time. However, the values change to C for barrel temperature; 40% for packing pressure, % for screw speed and 3 seconds for filling time in Table 5 for the compounding of 77 wt. %, 15 wt. % gma, 5 wt. % NC, 3 wt. % GS. Table 4. The optimisation of warpage and shrinkage for compounding 79 wt. %, 15 wt. % gma, 5 wt. % NC, 1 wt. % GS. Barrel Temperature ( 0 C) Packing Pressure (%) Screw Speed (%) Filling Time (s) Factor Z S Z S Z S Z S Max S/N Level Value Table 5. The optimisation of warpage and shrinkage for compounding 77 wt. %, 15 wt. % gma, 5 wt. % NC, 3 wt. % GS. Barrel Temperature ( 0 C) Packing Pressure (%) Screw Speed (%) Filling Time (s) Factor Z S Z S Z S Z S Max S/N Level Value Conclusion As for the conclusion, the optimum parameter for injection moulding parameters towards the quality characteristics of samples made from polypropylene-nanoclay-gigantochloa Scortechinii fibers had been achieved, by adopting the Taguchi Method. The value of warpage was reduced when the GS fiber content was increased from 1 wt. % to 3 wt. %. The warpage value changed from mm to mm. The optimum parameter for warpage were 175 C barrel temperature, 40% packing pressure, % screw speed and 2 seconds filling time for both 1 wt. % and 3% of GS fiber. However, in terms of shrinkage, the increment of fiber content doesn't have much impact towards the response. To the value of shrinkage was changed, but not significantly, from mm to mm when the percentage of fiber added. The optimum parameter for 1 wt. % fiber to control shrinkage are 170 C melt temperature, % packing pressure, % screw speed and 2 seconds of filling time. However, the values change to C for barrel temperature; 40% for packing pressure, % for screw speed and 3 seconds for filling time in Table 5 for the compounding of 77 wt. %, 15 wt. % gma, 5 wt. % NC, 3 wt. % GS. The existence of GS fiber obviously giving a promising manufacturing opportunity and the findings of this research could be useful for more detailed studies and as guideline to enhance the injection moulding process in the future. Acknowledgements The authors would like to acknowledge the Ministry of higher Education (MOHE) Malaysia for sponsoring the fundamental research grant scheme (FRGS) under VOT 1595 and Universiti Tun Hussien Onn Malaysia (UTHM) for short term grants under VOT U7 as well as well as the facilities provided for this research.

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