Optimization of plastic injection process using optimization techniques
Keywords:
Plastic injection parameters, genetic algorithm, response surface methodology, finite element analysis
Abstract
In this study, Moldflow analysis performed in accordance with the set of design of experiment by using statistical experimental design methods for optimization of injection parameters. In order to evaluate the results, firstly finite element analysis was applied with Moldflow. Secondly, in finding optimum values, Finite Element Analysis, Response Surface Methodology and Genetic Algorithm are integrated. To achieve efficient and effective integration, a computer program is written. Evaluated which method gives more accurate results by comparing to results being obtained by different optimization method in the final phase. From this study it is observed that process parameters improve injection significantly. Application of optimization method also improves further injection characteristics of plastic parts.
References
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[18] Oguz Kayabasi, Bulent Ekici, Automated design methodology for automobile side panel die using an effective optimization approach Materials and Design 28 (2007) 2665–2672.
[2] S. Kamaruddin, Z. A. Khan, ve S. H. Foong, “Application of Taguchi method in the optimization of injection moulding parameters for manufacturing products from plastic blend, †IACSIT International Journal of Engineering and Technology, c. 2, Sayı 6, ss. 574-580, 2010.
[3] H. Öktem ve F. Erzincanlı, “ Bir DVD-rom ön kapağının plastik enjeksiyonla basılması sonucunda oluşan çekmeye etki eden en uygun işlem parametrelerinin Taguchi yöntemiyle belirlenmesi, †3. Ulusal Tasarım İmalat ve Analiz Kongresi, Balıkesir, Türkiye, 2012, ss. 431-441.
[4] R. Pareek, ve J. Bhamniya, “ Optimization of injection moulding process using Taguchi and ANOVA, †International Journal of Scientific & Engineering Research, c. 4, Sayı 1, ss. 369-375, 2013.
[5] A.Cellere, ve G.Lucchetta, “ Determination of robust conditions for injection moulding of recycled polypropylene, †International Journal of Material Forming, c. 1, Sayı 1, ss. 691-694, 2008.
[6] K. Lee ve J.C. Lin, “ Optimization of injection molding parameters for lampshade,†Transactions of the Canadian Society for Mechanical Engineering, c. 37, Sayı 3, ss. 313-323, 2013.
[7] M. S. Meiabadia, A. Vafaeesefatb , ve F. Sharifi, “ Optimization of plastic injection molding process by combination of Artificial Neural Network and Genetic Algorithm, †Journal of Optimization in Industrial Engineering, c.13, ss. 49-54, 2013.
[8] D. Mathivanan, M. Nouby, ve R. Vidhya, “ Minimization of sink mark defects in injection molding process Taguchi approach, †International Journal of Engineering, Science and Technology , c. 2, Sayı 2, ss. 13-22, 2010.
[9] Y. Özek ve C. Çelik, “ Plastik enjeksiyon kalıplarında enjeksiyon sürelerinin yapay sinir ağları ile modellenmesi, †Fırat Üniv. Mühendislik Bilimleri Dergisi, c. 23 , Sayı 1, ss. 35-42, 2011.
[10] Y. Özek, C.Çelik, G. Gürgüze, “ Developing a new package program for manufacturing plastic injection moldings and cost calculation, †Journal of New World Sciences Academy , c. 5, Sayı 3, ss. 279-287, 2010.
[11] T. Erzurumlu, ve B. Ozcelik, “ Comparison of the warpage optimization in the plastic injection molding using ANOVA, neural network model and genetic algorithm, â€Journal of Materials Processing Technology, c. 171, Sayı 3, ss. 437-445, 2006.
[12] K. M. B. Jansen , D. J. Van Dijk, ve M. H. Husselman , “ Effect of processing conditions on shrinkage in injection molding, †Polymer Engineering and Science, c. 38, Sayı 5, ss. 838-846, 1998.
[13] H. S. Park, ve T. T. Nguyen, “ Optimization of injection molding process for car fender in considera-tion of energy efficiency and product quality, †Journal of Computational Design and Engineering, c. 1, Sayı 4, ss. 256-265, 2014.
[14] Akyürek, A. Keçe, A. Aksoy ve N. Öztürk, “ Termoplastik ürünlerin yeni ürün devreye alınma sürecinde bir yapay zeka yaklaşımı, †Uludağ Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, c. 14, Sayı 1, ss. 67-76, 2009.
[15] V. Erdem, M. Belevi, ve C. Koçhan, “ Taguchi metodu ile plastik enjeksiyon parçalarda çarpılmanın en aza indirilmesi, †DEÜ Mühendislik Fakültesi Fen ve Mühendislik Dergisi, c.12, Sayı 2, ss. 17-29, 2010.
[16] M. V. Kavade, ve S. D. Kadam, “ Parameter optimization of injection molding of polypropylene by using Taguchi methodology, †Journal of Mechanical and Civil Engineering, c.4, Sayı 4, ss. 49-58, 2012.
[17] S. Taghizaded, A. Özdemir, ve O. Uluer, “ Warpage prediction in plastic injection molded part using arttifical neural network, †Transactions of Mechanical Engineering, c. 37, Sayı M2, ss. 149-160, 2013.
[18] Oguz Kayabasi, Bulent Ekici, Automated design methodology for automobile side panel die using an effective optimization approach Materials and Design 28 (2007) 2665–2672.
Published
2020-07-04
How to Cite
Kayabasi, O. (2020). Optimization of plastic injection process using optimization techniques. Journal of Engineering Research and Applied Science, 9(1), 1366-1373. Retrieved from http://www.journaleras.com/index.php/jeras/article/view/195
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