Effect Of Injection Moulding Parameters On The Shrinkage Using Taguchi Method

Effect Of Injection Moulding Parameters On The Shrinkage Using Taguchi Method

This project focuses on the optimization of injection molding machine using High Density Polyethylene (HDPE) material. The objective of this experiment is to provide statistical evidence for optimizing parameters of the injection molding process. Design of Experiment (DOE) is a powerful technique i...

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Main Author: Wan Azhari, Wan Noor Azrina
Format: Thesis
Language:English
English
Published: 2016
Subjects:
T Technology (General)
TS Manufactures
Online Access:http://eprints.utem.edu.my/id/eprint/20782/1/Effect%20Of%20Injection%20Moulding%20Parameters%20On%20The%20Shrinkage%20Using%20Taguchi%20Method%20-%20Wan%20Noor%20Azrina%20Wan%20Azhari%20-%2024%20Pages.pdf
http://eprints.utem.edu.my/id/eprint/20782/2/Effect%20Of%20Injection%20Moulding%20Parameters%20On%20The%20Shrinkage%20Using%20Taguchi%20Method.pdf
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id my-utem-ep.20782
record_format uketd_dc
institution Universiti Teknikal Malaysia Melaka
collection UTeM Repository
language English
English
topic T Technology (General)
TS Manufactures
spellingShingle T Technology (General)
TS Manufactures
Wan Azhari, Wan Noor Azrina
Effect Of Injection Moulding Parameters On The Shrinkage Using Taguchi Method
description This project focuses on the optimization of injection molding machine using High Density Polyethylene (HDPE) material. The objective of this experiment is to provide statistical evidence for optimizing parameters of the injection molding process. Design of Experiment (DOE) is a powerful technique in order to achieve the high quality of product especially in mass production industries. This experiment was conducted to find out the optimal parameter setting in Injection Molding process in order to minimize the time, waste and cost. In this case study, the Taguchi method is used. It is an alternative way compared with the traditional method which is inefficient and unreliable with One Factor At A Time (OFAT) approach. The Taguchi method had been chosen in these studies because instead of having to test all possibilities, it only performed as per standard orthogonal arrays to investigate the effects of the entire machining parameters through small number of experiments. The parameter and factor that involved in this case study are shot size, injection pressure, injection speed and clamping force. After gaining all the parameter and results from the experiment, it will be interpreted in Minitab 17 software using ANOVA to verify the optimal parameter. The samples yet to be evaluated for weight changes to find the best set of parameter with less value of shrinkage percentage. Finally, the result proved that the optimum parameter reduced the percentage of shrinkage and ANOVA identified shot size parameter as the most significance input towards volumetric shrinkage.
format Thesis
qualification_name Master of Philosophy (M.Phil.)
qualification_level Master's degree
author Wan Azhari, Wan Noor Azrina
author_facet Wan Azhari, Wan Noor Azrina
author_sort Wan Azhari, Wan Noor Azrina
title Effect Of Injection Moulding Parameters On The Shrinkage Using Taguchi Method
title_short Effect Of Injection Moulding Parameters On The Shrinkage Using Taguchi Method
title_full Effect Of Injection Moulding Parameters On The Shrinkage Using Taguchi Method
title_fullStr Effect Of Injection Moulding Parameters On The Shrinkage Using Taguchi Method
title_full_unstemmed Effect Of Injection Moulding Parameters On The Shrinkage Using Taguchi Method
title_sort effect of injection moulding parameters on the shrinkage using taguchi method
granting_institution Universiti Teknikal Malaysia Melaka
granting_department Faculty of Manufacturing Engineering
publishDate 2016
url http://eprints.utem.edu.my/id/eprint/20782/1/Effect%20Of%20Injection%20Moulding%20Parameters%20On%20The%20Shrinkage%20Using%20Taguchi%20Method%20-%20Wan%20Noor%20Azrina%20Wan%20Azhari%20-%2024%20Pages.pdf
http://eprints.utem.edu.my/id/eprint/20782/2/Effect%20Of%20Injection%20Moulding%20Parameters%20On%20The%20Shrinkage%20Using%20Taguchi%20Method.pdf
_version_ 1747834005080768512
spelling my-utem-ep.207822021-10-10T22:57:02Z Effect Of Injection Moulding Parameters On The Shrinkage Using Taguchi Method 2016 Wan Azhari, Wan Noor Azrina T Technology (General) TS Manufactures This project focuses on the optimization of injection molding machine using High Density Polyethylene (HDPE) material. The objective of this experiment is to provide statistical evidence for optimizing parameters of the injection molding process. Design of Experiment (DOE) is a powerful technique in order to achieve the high quality of product especially in mass production industries. This experiment was conducted to find out the optimal parameter setting in Injection Molding process in order to minimize the time, waste and cost. In this case study, the Taguchi method is used. It is an alternative way compared with the traditional method which is inefficient and unreliable with One Factor At A Time (OFAT) approach. The Taguchi method had been chosen in these studies because instead of having to test all possibilities, it only performed as per standard orthogonal arrays to investigate the effects of the entire machining parameters through small number of experiments. The parameter and factor that involved in this case study are shot size, injection pressure, injection speed and clamping force. After gaining all the parameter and results from the experiment, it will be interpreted in Minitab 17 software using ANOVA to verify the optimal parameter. The samples yet to be evaluated for weight changes to find the best set of parameter with less value of shrinkage percentage. Finally, the result proved that the optimum parameter reduced the percentage of shrinkage and ANOVA identified shot size parameter as the most significance input towards volumetric shrinkage. 2016 Thesis http://eprints.utem.edu.my/id/eprint/20782/ http://eprints.utem.edu.my/id/eprint/20782/1/Effect%20Of%20Injection%20Moulding%20Parameters%20On%20The%20Shrinkage%20Using%20Taguchi%20Method%20-%20Wan%20Noor%20Azrina%20Wan%20Azhari%20-%2024%20Pages.pdf text en public http://eprints.utem.edu.my/id/eprint/20782/2/Effect%20Of%20Injection%20Moulding%20Parameters%20On%20The%20Shrinkage%20Using%20Taguchi%20Method.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=104956 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Manufacturing Engineering 1. Anthony C.A., 2001. One Hundred Years of The Design of Experiments on and off the Pages of Biometrika. Oxford University Press, U.S.A.. Volume: 88, issue 1, pp. 53-97. 2. Arthur J., 2007. Design of Experiment-DOE, Know Ware International Inc. [online] Available at: http://www.cncci.com/consultform.html [Accessed on 5 Jun 2014]. 3. Boza L.O.J., 2003. Full Factorial DOE [online]. Available at: http://www.doe/full factorial/full_factorial_DOE-247.html [Accessed on 31 May 2014]. 4. Bozzelli J., 2011. Calculate Shot Size Vs. Barrel Capacity. Injection Molding Solutions, Plastics Technology [online]. Available at: http://www.ptonline.com/columns/calculate-shot-size-vs-barrel-capacity [Accessed on 19 December 2015]. 5. Chen W.C., Wang M.W. and Fu G.L., 2008. Optimization of plastic injection molding process via Taguchi’s parameter design method, BPNN, and DFP, Machine Learning and Cybernetics International Conference. on Volume: 6, pp. 3315 – 3321 6. Elbinezar and Kamble B., 2014. Family Mould Design For Quality Levers. IJRET: International Journal of Research in Engineering and Technology, pp: 2319-1163 | pp: 2321-7308 7. Fryman M.A., 2002. Quality and Process Improvement, pp. 318-327 8. Harare I., 2009. Mould Theory. Indo-Zimbabwe Training Program. 9. Kappel E., Stefaniak D., and Huhne C., 2013. Process Distortions In Prepreg Manufacturing E An Experimental Study On CFRP L-Profiles, Compos. Struct. 106 615e625. 10. Kubade P.R., and Jadhav V.S., 2012. An Experimental of Electrode Wear Rate (EWR), Material Removal Rate (MRR) and Radial Overcut (ROC) in EDM of High Carbon-High Chromium Steel (AISI D3). International Journal of Engineering and Advanced Technology (IJEAT). Vol. 1, No. 5. 11. Dixon D., Eatock J., Meenan B.J., and Morgan M., 2006. Application of Design of Experiment (DOE) Techniques to Process Validation in Mediacal Device Manufacture, Journal of Validation Technology. 12. Palardy G., Hubert P., Haider M., and Lessard L., 2008. Optimization of RTM processing parameters for class A surface finish, Compos. Part B 39 (2008) 1280e1286. 13. Phadke M.S., 1989. Quality Engineering Using Robust Design. Prentice-Hall, Englewood cliffs, NJ. 14. Park K. and Ahn J., 2004. Design of Experiment Considering two-way interactions and its Application to Injection Molding Processes with Numerical Analysis, Journal of Materials Processing Technology, 146, pp. 221-227. 15. Richardson and Lokensgard, 1997. Industrial plastic theory and applications, 3rd Ed. Singapore: Delmar Publisher Inc, pp. 143-146. 16. Schauer C., 2007. Injection Molding. Department of Materials Science and Engineering. Drexel University. 17. Subramonian S., Salleh R., Taufik and Mohamad A., 2014. Design of Experiments Step by step practical Applications for beginners, 1st ed., Universiti Teknikal Malaysia Melaka 18. Taguchi G., 1998. Introduction to Quality Engineering: Designing Quality into Product and Process. Asian Productivity Organisation, Japan. 19. Exner W., Kuhna, A., Szewieczeka A., Opitz M., Mahrholza T., Sinapiusa M., and Wierach P., 2015. Determination of volumetric shrinkage of thermally cured thermosets using video-imaging. Polymer Testing, Volume 49, November 2015, Pages 100-106 20. Foster W.T., 2000. Basic Taguchi design of experiments. In: National Association of Industrial Technology Conference, Pittsburgh, PA. 21. Fowlkes W.Y. and Creveling C.M., 1997. Engineering Methods for Robust Product Design-using Taguchi Methods in Technology and Product Development, Addison Wesley, Reading, Massachusetts. 22. Zhao, C. and Gao, F., 1999. Melt Temperature Profile Prediction For Thermoplastic Injection Molding. Polymer Engineering and Science, 39(9), pp.1787-1801.

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