advances in numerical modeling of manufacturing processes

More documents

Recommendations

Info

TRANS. INDIAN INST. MET., VOL. 57, NO. 4, AUGUST 2004 problems such as, • Optimal machining parameters for a given material, heat treatment and part geometry • Increased material removal rates for minimizing machining times • Improved workpiece functional attributes such as surface integrity and precision • Design of cutting tool geometries and materials for increased tool lives and reduced tool changes. 4. SOLIDIFICATION PROCESSING AND POROSITY CONTROL 4.1 Die Casting of Engine Block: Application in 44, 45 Automotive Industry With the emphasis on light weight cars, automotive companies are increasingly using die cast engine blocks from high silicon aluminum alloys (Fig. 13). In these castings, the main cause of defect is leaker paths in certain critical areas of the castings due to microporosity. These leaker defects cause the cylinder block to fail the pressure leakage test and such castings have to be discarded as scrap. The aim of this study was to redesign the gate and optimization of the ingate parameters with a focus on minimum air entrapment for minimum gas porosity and better filling of thick sections for reduces shrinkage related defects. 4.2 Location and Identification of Porosity Analysis of pressure test results on the die cast and machined engine blocks indicated that most of the leakage occurred from two locations shown in Fig. 13: Region 1 near the bearing area and Region 2 near the coolant entry area (the vent area for the die casting). Sections were cut from these locations in the cast dies, polished and examined. While Region 1 showed classical porosity linked to shrinkage due to thermal gradients, Region 2 showed the presence of pores which were not spherical, Fig. 14. The latter pores were analyzed using SEM techniques. It was found that while the composition on the outside regions of the pores represented the typical composition of the Al 380 die casting alloy, that in the inner regions showed a high presence of oxygen, Fig. 15. This is an indication of air being trappped during the die casting process (poor filling during metal injecttion). It was decided to focus on reducing or eliminating air or gas entrapment during metal injection by optimizing the the metal flow die runner system. 4.3 Flow Optimization procedure The parameters used in this optimization study were gate velocity, fill time and flow angle for the fan and the tangent gates. This simulation study was based on CastView®, a software developed at The Ohio State University with support from NADCA (North American Die Casting Association). The design alternatives considered are shown in Fig. 16. Fig. 13: A five cylinder engine block produced by die casting aluminum. Location of regions of interest: Region 1 near the bearing area, Region 2 near the vent area. 356
RAJIV SHIVPURI : NUMERICAL MODELING OF MANUFACTURING PROCESSES Fig. 14: Porosity location in the vent region and its relationship to die configuration Fig. 15: Analysis of the pore composition using SEM: Note the presense of oxygen inside the pore (picture on the right) A Box-Behnken design array with 15 runs, inclusive of 3 center runs, was chosen for this three -level / three-factor study, Fig. 16. Simulations were performed in CastView for all the runs and the results were analyzed with a view for optimization the filling process. An appropriate response variable was chosen with the objective to obtain a proper fill in which the region closest to the vent fills last, and the adjoining areas fill immediately before this region, and so on. A regression model was built with the results of the analysis. The regression model was maximized using Microsoft Excel® software, in keeping with the objective of maximizing the response (the regions near the vents should fill last). The regression equation is as follows, Response Variable = 2.37523 – 10.123372 A + 0.000370338 B – 0.022142558 C + 32.057016 A2 + 0.00001824 B2 – 0.0002299 C2 –0.0131143 AB + 0.030074282 AC + 0.000019886 BC Where A refers to the fill time (sec), B refers to the gate velocity (m/s),C refers to the flow angle (degrees) The range of variation used for the parameters was as defined in the design array. It was found that the optimum values for maximum response correspond to the maximum value of the gate velocity, minimum value of the fill time and flow angle in the range of variation. A runner was designed for the best design alternative using standard NADCA guidelines. 4.4 Comparison of the new design and existing design using FLOW3D A cavity filling simulation using the new gate design parameters was performed using the software package Flow3D (a finite difference software for fluid dynamics) and compared with simulations performed with existing gate designs 45 . For this simulation the best design alternative was chosen. Using design 357
Page 1 and 2: Trans. Indian Inst. Met. Vol.57, No
Page 3 and 4: RAJIV SHIVPURI : NUMERICAL MODELING
Page 11: RAJIV SHIVPURI : NUMERICAL MODELING

advances in numerical modeling of manufacturing processes

Create successful ePaper yourself

Delete template?

Save as template?