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Metal Casting Technologies : September 2006
86 TECHNICAL FEATURE The feeder design is verified by simulating casting solidification using the Vector Element Method which traces the feed metal paths in reverse to accurately pinpoint the location and extent of shrinkage defects such as cavity, porosity and centreline shrinkage. The method is based on the principle that the direction of the highest temperature gradient (feed metal path) at any point inside the casting is given by the vector sum of individual thermal flux vectors in all directions around the point. Multiple hot spots, if present, are detected by starting from several directions. Ideal feeding implies that all feed metal paths meet and converge inside a feeder. The most important steps in gating system design include deciding the number and location of ingates, and designing the choke (smallest cross-section among sprue, runner and ingates) so that the mould fills in a predetermined range of time. This is required to eliminate the defects caused by slow filling (cold shuts and misruns), or fast filling (mould erosion and inclusions). The ideal filling time (function of casting weight, section thickness and fluidity) is suggested by the program, followed by choke velocity (metallostatic head), and choke area, using the gating ratio. The ingate locations are suggested by the program, which hunts for thick sections near the parting line that have low free fall height and fewer obstructions (such as cores blocking the path of metal emerging from an ingate). The mould filling is simulated to determine the actual filling time (to check the gating design for the ideal filling time), and identify the location and velocity of metal impingement on mould (to determine the possibility of mould erosion/sand inclusions). A layer-by-layer filling algorithm that considers the instantaneous velocity of metal through the ingate (which depends on the instantaneous metallostatic head), and the area of casting cross-section being filled up, is adequate to estimate the mould filling time. This approach is however, applicable to gravity processes only. INDUSTRIAL APPLICATION The program has been successfully validated by troubleshooting and optimising over one hundred different industrial castings of ferrous and non-ferrous alloys, ranging from a few grams to several tonnes, produced in sand as well as metal moulds, without any major discrepancy between predicted and actual observed results (shrinkage porosity defects). It is now being used by several dozen foundries (ferrous as well as non-ferrous), as well as a few OEM firms and consulting service providers Figure 2 shows an industrial case study of an aluminium-alloy switchgear tank produced by gravity die casting. The casting is about 280 mm in size, and weighed 6.1 kg. It was found to leak during pressure-test, and rejections were as high as 35%. The methoding was modelled as produced in the foundry, and simulated to locate two regions of shrinkage locations leading to leakage. The methoding was improved by placing a chill in the cores and insulation on feeders, and verified by simulation. This enabled rejections to be reduced to less than 5% without additional shop floor trials. Adopting this methodology during product development phase itself would have ensured even lower rejections and saving of resources (material, energy, labour, and time) otherwise spent for casting trials. CONCLUSION The bottlenecks and non-value added time in casting development can be minimised by adopting CAD, intelligent methoding and simulation technologies. These have been developed, successfully demonstrated on industrial castings, and now being used in several organisations. Several innovative algorithms, including VEM, geometric reasoning, and automatic solid modelling dramatically compressed the iteration time for methoding modification and simulation to less than one hour for even complex castings. Further, the simple and logical user interface greatly improved the learning curve for engineers, to just a few hours. As a result, even small foundries with little or no previous exposure to CAD/CAM software are able to effectively use the program to improve their casting quality, yield and productivity. It has also proven to be very useful for verifying the manufacturability of a casting and improving it by minor modifications to part geometry, before freezing the design. ● Figure 2 Troubleshooting and improvement of an aluminium-alloy gravity-die casting REFERENCES 1. B. Ravi, Metal Casting: Computer-Aided Design and Analysis, Prentice-Hall India, New Delhi, 2005. 2. B. Ravi, R.C. Creese and D. Ramesh, "Design for Casting -- A New Paradigm to Prevent Potential Problems," Transactions of the AFS, 107, 1999. 3. B. Ravi and M.N. Srinivasan, "Casting Solidification Analysis by Modulus Vector Method," International Cast Metals Journal, 9(1), 1-7, 1996. 4. B. Ravi, "Intelligent Design of Gating Channels for Casting," Materials Science and Technology, 13(9), 785-790, 1997. 5. AutoCAST information and case studies, Advanced Reasoning Technologies Pvt. Ltd., http://www.adva-reason.com. www.metals.rala.com.au B. Ravi, Associate Professor Mechanical Engineering, Indian Institute of Technology, Bombay firstname.lastname@example.org