rapid casting development -...
TRANSCRIPT
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Rapid Manufacturing Seminar, TEAMTECH 2006, Bangalore, Feb 28- Mar 2, 2006
Rapid Casting Development
B. Ravi, Associate Professor Mechanical Engineering, Indian Institute of Technology, Bombay
Dinesh Kumar Pal, Scientist, Terminal Ballistics Research Laboratory, Chandigarh
Nagahanumaiah, Scientist, Central Mechanical Engineering Research Institute, Durgapur
[email protected] ABSTRACT Rapid product innovation cycles prevalent today demand development of new castings in days instead of months. This is possible only by adopting new technologies and methodologies. We present three areas of our work contributing to rapid casting development: process simulation, rapid tooling and collaborative engineering. Casting process simulation enables optimising the methoding and process parameters without shop-floor trials. Several rapid prototyping-based routes are available today for casting pattern fabrication; and the most widely-used routes have been benchmarked for their impact on fabrication time, development cost, dimensional accuracy and surface quality. A web-based framework for exchange of casting project information between product, tooling and foundry engineers enables early identification of potential problems, and their prevention by more compatible product-process designs. The use of all three techniques significantly compresses the lead-time for developing a casting. The entire approach is illustrated through examples of industrial castings, and shown to be superior to the traditional approach in also achieving more predictable and consistent quality castings. Keywords: Casting; Computer-Aided Design; Collaborative Engineering; Process Simulation; Rapid Prototyping (RP); Rapid Tooling (RT). 1. INTRODUCTION In ancient times (circa 1000 AD), it would take 3-4 months to make a bronze casting idol through investment casting, starting from the carving of a wax statue, covering with clay, drying in the sun, dewaxing, metal pouring, demoulding, and finally finishing the casting [1]. In the last century, which witnessed manufacture of castings on a large scale, the lead-time for developing a typical casting was however, not very different: about 8-12 weeks. This was mainly due to several weeks (over 70% of total lead-time) consumed by tooling development and production trials. Such lead-times are no longer acceptable. With rapidly compressing product development times (typically 12-15 months for a new automobile), OEMs now expect a new casting to be developed in days, not weeks and months. This is however, easier said than done, since the demand for shorter lead-time is also accompanied by the need for quality assurance and cost reduction. All these cannot be simultaneously achieved unless new technologies (like CAD and simulation) and methodologies (like design for manufacture and collaborative engineering) are employed for casting development.
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In general, development of a new casting broadly comprises three distinct phases: product design (in OEM firm), tooling development (in a tool room), and casting production (in a foundry). Most OEM firms now make use of CAD programs for solid modelling and shape optimisation. Creating a 3D model of the part is a time-taking task, but essential for computer-aided casting development. For existing parts, the solid modelling time can be minimised by reverse engineering: scanning the part geometry using a contact or non-contact (laser) scanner. The tool rooms can use software programs for tool design (pattern and core box), including application of various allowances like draft, shrinkage and machining. The foundry engineer can use software programs for (1) methoding or rigging (design of feeders and gating system), and (2) casting simulation (mould filling and solidification) to predict casting defects, and to optimise the methoding for achieving the desired quality and yield. The fabrication is tooling is facilitated by CAM programs for tool path generation and CNC manufacture of tooling. This lead-time can be further compressed by using rapid prototyping based tooling, referred to as rapid tooling. Feedback from tooling development and casting trial (real or virtual) is useful and indeed necessary to improve the design of product and tooling considering manufacturability (Fig.1). For example, undercut features that necessitate an additional core or non-planar parting can be eliminated to reduce the tooling costs. Similarly, thin intermediate features that cool early and hinder mould filling or solidification feeding can be increased in size to prevent cold shut and shrinkage porosity defects, respectively. This can be facilitated through collaborative engineering between foundry, tooling and OEM engineers, resulting in early prediction and prevention of potential production problems (better quality assurance), and saving valuable time and costs [2].
Fig.1 Computer-aided rapid casting development The above technologies are briefly described in this paper, highlighting our efforts toward indigenous development and application, focussing on bottleneck and least-explored areas with the largest potential for lead-time reduction. The first major work involved developing a software program for semi-automatic methoding and simulation of castings, considering its use by foundry engineers with very little exposure to computers. The second major work involved benchmarking some of the most widely used rapid prototyping routes for tooling (pattern) fabrication. The third contribution was in
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creating a framework for facilitating casting project management and exchange of information between product, tooling and foundry engineers over the Internet. These three works are briefly described in the following sections. 2. CASTING METHODING AND SIMULATION Casting methoding or rigging involves three major design elements: (1) casting orientation and mould parting, (2) feeders (or risers) and feed-aids, and (3) gating channels comprising mainly sprue, runner(s) and ingate(s). The methoding is verified by a virtual casting trial (mainly simulation of mould filling and casting solidification) to detect defects, if any. Several iterations of methoding modification and trials are required for ensuring the desired quality with high yield (ratio of weight of casting to the weight of casting plus feeders and gating). For casting simulation, several programs are available today: Magma (magmasoft.com), Pamcast/Procast (esi-group.com), Novasolid/Novaflow (novacast.se), Solidcast (finitesolutions.com) and a few others. They are however, rarely used by the large number of small and medium size foundries, owing to the high cost of the software and support involved, and difficulty in attracting and retaining the technical manpower required to run the programs. To overcome the limitations of the above programs, and to further reduce the lead-time for developing a casting, the methoding and simulation functions have been integrated in a single program called AutoCAST (Fig. 2). Its main functions are briefly described here. The orientation and parting are usually decided during the design of tooling (pattern and core box). The three coordinate axes are considered, and the direction in which the part has the least number and volume of undercuts is suggested as the best one. After selecting the orientation, the mould parting line is generated to minimise the draw distance and draft volume. Casting orientation and parting line are important decisions that affect the design of feeding and gating system. Feeder design mainly involves decisions regarding the number, location, shape and dimensions of feeders and feed-aids (like chill and insulation). The feeder is usually located near a hot spot, and designed to solidify later, so that it can supply feed metal as the casting undergoes volumetric contraction during cooling from liquidus to solidus temperature (contraction between solidus and room temperature is compensated by pattern shrinkage allowance). Automated feeder design uses geometric reasoning to suggest the best location of feeder (closest to the hot spot, on a flat surface at the top or side, to facilitate its removal afterwards). Its dimensions are calculated based on geometric modulus (since solidification time of a simple shape is proportional to the square of the ratio of heat content volume to cooling surface area). Finally, the feeder model is automatically created and attached to the casting. Solidification rate and time at different points inside a casting are mainly influenced by its geometry (part and feeders), metal/alloy characteristics (thermo-physical properties and freezing range), and boundary conditions (heat transfer rate at the interface between metal and other elements: mould, core and feedaids). The major related defect, shrinkage porosity occurs at locations of high temperature and low gradients. This is simulated 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 [3]. 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 multiple points inside the casting. Ideal feeding implies that all feed metal paths meet and converge inside a feeder.
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Fig. 2 Casting methoding and simulation program showing part model import,
core design, feeding and gating design, and casting simulation The most important steps in gating system design are 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 determined first, followed by choke velocity (metallostatic head), and choke area, using the gating ratio [4]. The ingate locations are suggested by looking for thick sections near the parting line that have low free fall height and fewer obstructions. 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
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metallostatic head), and the area of casting cross-section being filled up, is adequate to estimate the mould filling time. The casting methoding and simulation program has been successfully validated by troubleshooting and optimising over one hundred different industrial castings of ferrous and non-ferrous alloys, produced in sand as well as metal moulds, without any major discrepancy between predicted and actual observed results (shrinkage porosity defects). Figure 3 shows an industrial case study of an aluminium-alloy switchgear tank produced by gravity die casting (courtesy, Crompton Greaves Ltd., Mumbai). 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 6% 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.
Fig. 3 Troubleshooting and improvement of an aluminium-alloy casting
Several innovative algorithms (such as the VEM for hot spot detection), coupled with a high level of automation (driven by geometric reasoning algorithms for feeder and gating location and design), 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 with little or no previous exposure to software programs, to just a few hours. 3. RAPID TOOLING FABRICATION The rapid prototyping technologies developed over the last decade enable automatic fabrication of a physical model directly from its 3D CAD data without any part-specific tooling. A special software slices the CAD model into a stack of cross-sections and sends these to an RP machine. The machine builds the sections one on top of another from bottom up. Major RP processes include: Fused Deposition Modeling (stratasys.com), Stereolithography, (3DSystems.com), 3D Printing (zcorp.com and 3DSystems.com), Selective Laser Sintering (www.eos-gmbh.de), and Layered Object Manufacturing (helisys.com). At present, there are over 30 companies world wide offering a variety of RP machines, differing in terms of the materials and techniques for building and binding the layers
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(wohlersassociates.com). There have been continuous improvements in the accuracy, surface finish and build speed of RP parts. The use of rapid prototyping techniques to fabricate the tooling is referred to as rapid tooling. In a strict sense, rapid tooling must also refer to any technique that can significantly reduce the lead-time, including high speed machining. We will however, restrict the discussion to RP-based tooling in this paper. The rapid tooling methods can be mainly classified as direct, indirect and semi-direct [6]. Direct tooling involves use of RP models themselves as patterns and core boxes for sand casting application. Indirect tooling makes use of RP models as intermediate masters for producing final patterns and core boxes, through processes such as epoxy mass casting, polyurethane face casting, metal spray and silicone rubber moulding. This category of tooling, also known as soft tooling, can only be used for small quantity batches, due to more pronounced deterioration in comparison to conventional metal or wooden patterns. Semi-direct tooling involves the use of RP systems to make dies for producing wax patterns for investment casting. The RP-based tooling routes can also be classified as single step, double step and triple step based on the number of steps required for reaching the final tooling that is used for casting. In liquid-based RP systems, the portions of the part lying above any undercuts are supported on independent structures created along with the part (using a different material as in FDM, or the same material as in Stereolithography). The support structures need to be manually removed after the fabrication is complete, which is a difficult and time-consuming task, especially for intricate shapes. Even in LOM patterns the removal of excess paper outside the cross-section boundary (which acts as the support) is somewhat difficult for intricate shapes. This difficulty is eliminated in powder-based systems (Thermojet and Zprinter), since loose powder provides the support in undercut regions and can be simply shaken off after fabrication is complete. The patterns built by the RP processes mentioned above are made of materials different from the those used in regular casting, and the casting process may require some experimentation and adjustment to use the RP patterns. For example, direct RP patterns require more careful handling and have a shorter life compared to regular metal patterns. The direct investment casting patterns produced by Stereolithography and LOM leave an undesirable ash residue during burnout. This can be overcome by preferring indirect routes, such as a silicone rubber or polyurethane mould for producing the investment patterns in industrial wax. It is clear from the above that a large number of feasible routes exist to fabricate the tooling for metal casting. Each route however, differs in terms of the tooling development time, cost, quality and life. While several researchers have carried out benchmarking studies of different RP machines for various applications, most of them have focussed on quality issues (mainly accuracy and surface finish). To study the techno-economic feasibility of various routes for metal casting application, we fabricated a single impeller pattern by the most widely-used RP-based routes [5]. This part suited our study also because it had features appropriate for geometric comparisons: thin straight blades, a curved surface, a thick bottom portion and axi-symmetry. The part solid model was used for fabricating non-expendable patterns for sand casting as well as expendable patterns for investment casting using RP techniques (Fig.4). The non-expendable RP patterns were fabricated using SLA, FDM and LOM RP techniques. The patterns FDM2 and FDM3 were made on the same machine, but the latter was made with a widely spaced cross-hatching for the interior region, reducing its fabrication time (given later). The expendable RP patterns were fabricated using SLA QuickCast and Thermojet. The RP pattern ‘SLA1’ made by Stereolithography was also used as a master to fabricate a silicone rubber mould (Fig.4j), which can be used for producing 40-50 wax patterns (Fig.4k) before the mould surface starts showing wear. These wax patterns are used for investment casting. Table 1 shows the summary of the various routes and relevant parameters.
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Fig. 4. Fabrication of RP patterns by direct routes: (a) FDM1, (b) FDM2, (c) FDM3, (d) SLA1, (e) SLA2, (f) SLAQ1, (g) TJP1, (h) LOM1, and indirect route (i-k).
Table 1. Summary of techniques used for producing RP patterns
RP
Machine
System
manufacturer
Material
Accuracy XY-plane
(mm)
Accuracy Z-plane (mm)
Layer Thickness
(mm)
FDM1 FDM Titan Stratasys Polycarbonate 0.15 0.13 0.25 FDM2 FDM 250 ABS(P400) 0.15 0.13 0.25 FDM3 FDM 250 ABS (P400) 0.15 0.13 0.25 SLA1 SLA 5000 3D Systems SLA5530 epoxy resin 0.1 0.10 0.10 SLA2 SLA 250 SLA5530 epoxy resin 0.1 0.10 0.10 SLAQ1 SLA 5000 SLA5530 epoxy resin 0.1 0.10 0.10 TJP1 Thermojet TJ88 wax 0.1 0.10 0.10 LOM1 LOM- Helisys
h l iPaper
( i )0.25 0.30 0.20
a b
d
e f
g h
c
i
j
k
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Table 2. Cost and time comparison
The different RP routes for producing non-expendable and expendable patterns for casting were compared in terms of fabrication time and cost (Table 2). The per hour machine rate was calculated considering only the basic cost of the RP machine and 10% annual maintenance cost, and assuming 24 hour working over 365 days. The fabrication cost for a given part is given by the product of machine cost per hour and the fabrication time. The material cost is calculated by the product of material rate and part weight. The total cost of a RP part is given by the sum of the fabrication cost and material cost. The costs of conventional wooden and metal patterns are also given for comparison. These are estimated by a separate cost estimation program developed in our lab and verified by tooling experts.
Fig. 5: DMLS rapid hard mold along with PBT, LDPE and Nylon 66 moldings
Machine cost ($1000)
Machine rate ($/hr)*
Time taken (hr)
Material rate ($/kg)
Part weight (kg)
Total cost ($)
FDM1 100 12.56 7 330 0.19 150.62 FDM2 55 6.90 16 300 0.09 137.40 FDM3 55 6.90 8 300 0.09 82.20 SLA1 400 50.23 2.5 250 0.21 178.08 SLA2 200 25.11 4 250 0.21 152.94 SLAQ1 400 50.23 2.5 250 0.05 138.08 TJP1 60 7.53 6 225 0.16 81.18 LOM1 120 15.07 6 20 0.17 93.82 Conventional wooden pattern 200.00 Conventional metal pattern 450.00
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The above methods cannot produce tooling in conventional tool steels, which are required for better quality and larger quantity of sand cast parts, as well as for die casting and injection moulding of wax patterns required in large numbers. A few processes are available today for fabricating rapid tooling in steels. This includes 3D Keltool, selective laser sintering (SLS) mold, direct metal laser sintering (DMLS) mold, shape deposition modeling (SDM) steel mold and hot isostatic pressing (HIP) of SLS tooling. The 3D Keltool is an indirect RT process, which uses an RP model as pattern for making interim molds in silicone rubber, which are filled with slurry of tool steel, tungsten carbide and epoxy binder. The binder is then burnt out and the voids are infiltrated with copper to produce production mold inserts. The SLS process can directly build carbon steel or stainless steel molds. The DMLS process uses a laser for liquid phase sintering of metal powder. Two different powder systems: bronze based powder and steel based powder (with a nitrogen atmosphere) are employed. The DMLS tooling can be used for up to 10,000 injection molding cycles. The SDM process can build the tool steel dies with hardness up to 40 HRc, which can withstand high pressure and produce good quality castings comparable with those produced from H13 die material. It is also possible to make a metal mould for injecting the wax using an indirect route such as making a wax RP model of the mould halves followed by investment casting. To explore rapid development of hard tooling, direct metal laser sintered (DMLS) cavity inserts for a hub gear part were fabricated on EOS-M250 (DMLS) machine, using a Cu-Ni-Sn based alloy in powder form (Fig.5). The build time was about 16 hours. This mold could be successfully used to produce 5,000 polymer parts (LDPE and Nylon 66). While this mold may not be suitable for die casting, it is certainly useful for injection molding of wax patterns for investment casting [6].
4. WEB-BASED COLLABORATION The WebICE (Web-based Intelligent Collaborative Engineering) framework was developed to facilitate collaboration between casting development team members who may belong to different organisations and located in different places. The backbone is an XML-based format called CastML (Casting Markup Language) to store information related to a casting project [7]. The structure and contents of CastML were determined after a careful study of many casting projects, and the information requirements of product, tooling and foundry engineers. The team members of a casting development project can access the relevant information through a standard web browser (Fig. 5). The structure of CastML comprises two parts: tree and data blocks. The tree represents the hierarchical relationship between different types of information, whereas the data blocks are used for storing the actual project data. Project data includes part details (3D model, quality and order size), material properties, process plan, methoding details, evaluation and other details required or generated. The solid models of the part and tooling elements, as well as images (such as results of simulation), and even knowledge-bits (if-then rules) can be linked to various nodes. A library of options for materials (casting alloys, mould material, core material, etc.), and process steps (moulding, core-making, melting, pouring, etc.) for different processes (sand casting, shell moulding, gravity die casting, etc.) have been developed and included. This allows semi-automated process planning to determine the methods, parameters and checks for each step. The process plan is developed by identifying the closest previous casting project using case based reasoning, and modifying it, if necessary. The user can also select and copy a desired option, minimising interactive input. Another important function includes casting cost estimation, based on analytical and parametric equations to estimate the cost of material, tooling (amortised), energy, labour and overheads [8]. The team members (tooling engineer, foundry engineer and consultant) interact with the system using different utilities provided for collaboration. This includes a 3D model compression and linking utility for product designers to upload the casting 3D model. All team members can manipulate (view, rotate, zoom) the casting model. In addition, an annotation facility has been provided for
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communication. Team members can simultaneously view the casting project data and suggest modifications, if necessary.
Fig. 6 Web-based framework for exchanging casting project data In its present form, the facility is suitable for only exchanging casting project data, and executing simple functions (like material selection, process planning and cost estimation) that do not require high computation power or Internet bandwidth. To enhance the usefulness of the system, there is a need to provide methoding and simulation functions also through the web-based interface. 5. CONCLUSION The bottlenecks and non-value added tasks in casting development can be eliminated by adopting CAD, simulation, rapid tooling and web-based collaboration technologies. These technologies have been developed in our lab through several Masters and PhD projects, and successfully demonstrated on industrial castings. They have been shown to not only reduce the casting development lead-time to a few days, but also enable quality assurance and continuous cost reduction. Wide-scale deployment of these technologies however, requires better education of engineers in SME firms and networked support facilities. These can be taken up only with the active support of industry, professional bodies and Government agencies. REFERENCES 1. B. Ravi, “Metal Casting – Back to Future,” 52nd Indian Foundry Congress, Institute of Indian
Foundrymen, Hyderabad, Feb 2004. 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.
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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. D.K. Pal, B. Ravi, L.S. Bhargava and U. Chandrasekhar, “Rapid Casting Development using Reverse Engineering, Rapid Prototyping and Process Simulation,” Indian Foundry Journal, 53(4), 23-34, 2005.
6. Nagahanumaiah, B. Ravi and N.P. Mukherjee, “Rapid Hard Tooling Process Selection using QFD-AHP Methodology,” Journal of Manufacturing Technology Management, 17(6), 2005.
7. M.M. Akarte and B. Ravi, “Casting Data Markup Language for Web-based Collaborative Engineering,” Transactions of the AFS, 110, 93-108, 2002.
8. R.G. Chougule and B. Ravi, “Casting Cost Estimation in an Integrated Product and Process Design Environment,” International Journal of Computer Integrated Manufacturing, in press.