Empirical Exploration of Optimal Gating System Design for Sand Casting Process
DOI:
https://doi.org/10.26437/ajar.v11i1.888Keywords:
Casting. gating scheme. gravity. mould cavity. productivityAbstract
Purpose: This paper aims to analyse and optimise the gating system used in the sand casting process to produce drainage doors at Deepshikha Casting in Nagpur. It focuses on understanding how gate design impacts productivity and the quality of the cast, drawing attention to common defects and the role of gravity casting techniques.
Design/Methodology/Approach: This paper discusses the present gating system of Deepshikha Casting in detail to identify defects, such as sand inclusions, blow holes, pinholes, gas holes, shrinkage, and misruns. The present gating ratio and system weight assessment are thus used to suggest changes in the design to improve the process efficiency and quality of the product.
Findings: The research indicates that the existing gating system has an inappropriate gating ratio, resulting in a high rate of faults and reduced productivity. The system also weighs a lot, which deters efficiency. Improving the gating design reduces flaws, increases the quality of castings, and enhances molten metal flow.
Research Limitation: The output of the present work is limited to Deepshikha Casting alone, which is used for drainage door casting. Further research must be conducted on different casting products and technologies for a broad application.
Practical Implication: This sector of sand casting can benefit from optimising the gating system, maximising productivity and minimising casting defects, thus reducing costs and improving efficiency.
Social Implication: The environment will also benefit from efficient casting because of reduced use of resources, reduced waste, and fewer consumables. Better procedures also translate to increased production of safer products.
Originality/Value: This paper provides practical, applied solutions for optimising the gating system of sand casting. Its insights are particularly informative for a foundry working with fragile metals and using gravity casting.
References
Alagarsamy, A. (2003). Casting Defect Analysis Procedure and a Case History. http://www.castingsolutions.com
Aloni, S. N. (2019). Optimization of Essential Parameters in Green Sand Process to Minimize Persisting Casting Defects Using Taguchi Approach. Journal of engineering science & technology review, 12(5).
Ambekar, S. A., & Jaju, S. B. (2014). A Review on Optimization of Gating System for Reducing Defect. International Journal of Engineering Research and General Science, 2(1). www.ijergs.org
Beckermann, C. (2003). Simulation of Dimensional Changes in Steel Casting.
Bhatt, J., Vyas, D., Rajput, A., Somasundaram, M., & Kumar, U. N. (2021). A systematic review on methods of optimizing riser and gating system based on energy Nexus approach. Energy Nexus, 1, 100002.
Chougule, R. G., & Ravi, B. (2005). Variant process planning of castings using AHP-based nearest neighbour algorithm for case retrieval. International Journal of Production Research, 43(6), 1255–1273. https://doi.org/10.1080/00207540412331320517
Dojka, R., Jezierski, J., & Campbell, J. (2018). Optimized Gating System for Steel Castings. Journal of Materials Engineering and Performance, 27(10), 5152–5163. https://doi.org/10.1007/s11665-018-3497-1
Duan, Z., Chen, W., Pei, X., Hou, H., & Zhao, Y. (2023). A multimodal data-driven design of low pressure die casting gating system for aluminum alloy cabin. Journal of Materials Research and Technology, 27, 2723-2736.
Edlabadkar, A. P., & Chaudhari, S. S. (2023). Literature Review on Optimization Techniques Used for Minimization of Casting. Journal of Production and Industrial Engineering, 4(1), 36–41. https://doi.org/10.26706/JPIE.4.1.ICRAMEN202308
Edlabadkar, A. P., Chaudhari, S. S., & Mankar, C. (2023). Experimental Investigation for Minimization of Casting Defects Using Taguchi Method. Key Engineering Materials, 965, 35–42. https://doi.org/10.4028/P-M25J7Y
Ghuge, A., Solunke, P., Pandit, C., Salphale, S., & Yadav, S. (2018). Effects of Gating System on the Mechanical Properties & Quality of Metal Castings. International Journal for Research in Engineering Application & Management, 4. https://doi.org/10.18231/2454-9150.2018.1428
He, B., Lei, Y., Jiang, M., & Wang, F. (2022). Optimal Design of the Gating and Riser System for Complex Casting Using an Evolutionary Algorithm. Materials 2022, Vol. 15, Page 7490, 15(21), 7490. https://doi.org/10.3390/MA15217490
Hu, J., Guo, Y., Wang, R., Ma, S., & Yu, A. (2022). Study on the Influence of Opposing Glare from Vehicle High-Beam Headlights Based on Drivers’ Visual Requirements. International Journal of Environmental Research and Public Health, 19(5), 2766. https://doi.org/10.3390/IJERPH19052766
Iqbal, H., Sheikh, A. K., Al-Yousef, A., & Younas, M. (2012). Mold Design Optimization for Sand Casting of Complex Geometries Using Advance Simulation Tools. Materials and Manufacturing Processes, 27(7), 775–785. https://doi.org/10.1080/10426914.2011.648250
ISO 28238:2010 Compression and injection moulds -Components for gating systems. https://www.iso.org/standard/44591.html. Retrieved April 2, 2024
Jakubski, J., & Dobosz, St. M. (2010). Selected parameters of moulding sands for designing quality control systems. Archives of Foundry Engineering, 10(3).
Jezierski, J., Dojka, R., & Janerka, K. (2018). Optimizing the Gating System for Steel Castings. Metals 2018, Vol. 8, Page 266, 8(4), 266. https://doi.org/10.3390/MET8040266
Jezierski, J., Rafał, D., Krzysztof, K., & Wojciech, U. (2016). Experimental Approach for Optimization of Gating System in Castings.
Khan, M. A., Ali, M. K., & Sajid, M. (2022). Lean Implementation Framework: A Case of Performance Improvement of Casting Process. IEEE Access, 10, 81281-81295.
Kor, J., Chen, X., & Hu, H. (2009). Multi-objective optimal gating and riser design for metal-casting. Proceedings of the IEEE International Conference on Control Applications, 428–433. https://doi.org/10.1109/CCA.2009.5280821
Krause, D. E., & Shaw, W. F. (1969). Gray Iron-A Unique Engineering Material. American Society for Testing and Materials, 3–28.
Krötzsch, S., Hofmann, I., & Paul, G. (2001). Casting design with help of information fusion. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 5, 3343–3348. https://doi.org/10.1109/ICSMC.2001.972035
Kumaravadivel, A., & Natarajan, U. (2013). Application of Six-Sigma DMAIC methodology to sand-casting process with response surface methodology. International Journal of Advanced Manufacturing Technology, 69(5–8), 1403–1420. https://doi.org/10.1007/S00170-013-5119-2/METRICS
Lan, Q., Wang, X., Sun, J., Chang, Z., Deng, Q., Sun, Q., ... & Peng, L. (2022). Artificial neural network approach for mechanical properties prediction of as-cast A380 aluminum alloy. Materials Today Communications, 31, 103301.
Maniar, V., & Patel, P. (2023). Optimizing Shrinkage Defects in Grey Cast Iron Butterfly Valve Casting: A Simulation and Experiment-Based Approach. Suranaree Journal of Science & Technology, 30(6).
Rajkumar, I., Rajini, N., Siengchin, S., Ismail, S. O., Mohammad, F., Al-Lohedan, H. A., ... & Issa, Z. A. (2021). Effects of sand and gating architecture on the performance of foot valve lever casting components used in pump industries. journal of materials research and technology, 15, 1653-1666.
Ramnath, B. V., Elanchezhian, C., Chandrasekhar, V., Kumar, A. A., Asif, S. M., Mohamed, G. R., Raj, D. V., & Kumar, C. S. (2014). Analysis and Optimization of Gating System for Commutator End Bracket. Procedia Materials Science, 6, 1312–1328. https://doi.org/10.1016/J.MSPRO.2014.07.110
Ramu, T., Kumar, M. D., & Ganesh, B. K. C. (2012). Modeling, simulation and analysis in manufacturing of a flywheel casting by SG iron. Int J Materi Biomater Appl, 2(4), 25-28.
Ravi, B. (2008). Casting Simulation and Optimisation: Benefits, Bottlenecks and Best Practices Casting Simulation and Optimisation: Benefits, Bottlenecks, and Best Practices. https://www.researchgate.net/publication/228975218
Ravi, B. (2010). Casting Simulation - Best Practices.
Ravi, B., Rahul Chougule, & Durgesh Joshi. (2005). Survey of Computer Applications in Indian Foundry Industry: Benefits and Concerns. https://www.researchgate.net/publication/267809574
Raza, M. H., Wasim, A., Sajid, M., & Hussain, S. (2021). Investigating the effects of gating design on mechanical properties of aluminum alloy in sand casting process. Journal of King Saud University-Engineering Sciences, 33(3), 201-212.
Saikaew, C., & Wiengwiset, S. (2012). Optimization of molding sand composition for quality improvement of iron castings. Applied Clay Science, 67–68, 26–31. https://doi.org/10.1016/J.CLAY.2012.07.005
Samaraweera, L., Thalagala, S., Gamage, P., & Nanayakkara, N. K. B. M. P. (2017, December). Optimization of green sand casting parameters using taguchi method to improve the surface quality of white cast iron grinding plates—A case study. In 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 1723-1727). IEEE.
Seo, H. Y., Jin, C. K., & Kang, C. G. (2018). Design of a gate system and riser optimization for turbine housing and the experimentation and simulation of a sand casting process. Advances in Mechanical Engineering, 10(8). https://doi.org/10.1177/1687814018795045/ASSET/IMAGES/10.1177_1687814018795045-IMG3.PNG
Siodmok, B., Jezierski, J., Dorula, J., & Romelczyk, R. (2018). Impact of sprue base in gating system on quality of filling – The compromise between theory and practice. Archives of Foundry Engineering, 18(3), 167–172. https://doi.org/10.24425/123620
Shilpa, M., Prakash, G. S., & Shivakumar, M. R. (2021). A combinatorial approach to optimize the properties of green sand used in casting mould. Materials Today: Proceedings, 39, 1509-1514.
Yoo, S. M., Cho, Y. S., Lee, C. C., Kim, J. H., Kim, C. H., & Choi, J. K. (2008). Optimization of Casting Process for Heat and Abrasion Resistant Large Gray Iron Castings. Tsinghua Science & Technology, 13(2), 152–156. https://doi.org/10.1016/S1007-0214(08)70027-0
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2025 AFRICAN JOURNAL OF APPLIED RESEARCH
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
By submitting and publishing your articles in the African Journal of Applied Research, you agree to transfer the copyright of the Article from the authors to the Journal ( African Journal of Applied Research).