Computer-Aided Casting Design –

Past, Present and Future

Dr. B. Ravi

Associate Professor of Mechanical Engineering, In-Charge, Casting Simulation Laboratory,

Co-Founder, Rapid Prototyping Cell

Department of Mechanical Engineering Indian Institute of Technology

Powai, Mumbai-400076

Tel: (+91-22) 576 7510 Fax: (+91-22) 578 3480

Email: bravi@me.iitb.ernet.in

Abstract Compared to the history of metal casting, the use of computers for casting is nascent, spanning less than three decades. Being a knowledge intensive process, metal casting stands to benefit greatly from the development and deployment of tailor-made software tools. The paper describes the evolution of software tools for casting design, broadly segregated into three phases spanning the decades 1980s (basic CAD), 1990s (desktop simulation) and 2000s (intelligent design). While computer-aided design and simulation software can greatly enhance productivity, quality assurance and casting yield, their penetration in small/medium foundries and engineering companies has been poor. The latest software tools combine heuristic knowledge, geometric reasoning and information management. They essentially behave like electronic assistants - performing the tasks automatically, while allowing the user ultimate control over decisions. The paper presents such an intelligent assistant for casting engineers (AutoCAST) and describes how it assists in designing, modeling, simulating, analyzing and improving cast products over electronic networks - providing a glimpse of the way castings will be designed in future. Keywords: Casting, Computer-Aided Design, Concurrent Engineering, Simulation. 1 Casting Industry Today Nearly 70 million tons of cast components worth more than $100 billion are produced annually for automobile, industrial machinery, municipal fittings and many other sectors, by over 33,300 foundries worldwide. An even larger number of companies are involved in designing, machining, testing and assembling cast components and in related activities such as tool making and material supply. According to the census of world casting production made in 1996, the USA is the leading producer as well as consumer of castings followed by China, CIS, Japan, Germany and India [1]. The top ten producers together account for 82% of the total production of castings and 87% of the number of foundries worldwide (Table 1). A comparison with an earlier census made in 1993 shows that in most countries the number of foundries is reducing [2] which is however, being compensated by a corresponding increase in the production. India quickly moved up in the rankings, doubling its production between 1993-96.

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Table 1. Top ten producers of castings [1,2]

COUNTRY PRODUCTION (million tons)

NUMBER OF FOUNDRIES

1997 1994 1997 1994 USA 14.07 11.71 2950 3100

CHINA 10.90 12.36 10997 13934 CIS 8.95 15.59 4000 4000

JAPAN 6.96 6.68 1418 1428 GERMANY 3.93 3.48 780 889

INDIA 3.22 1.58 6000 6000 FRANCE 2.27 2.03 507 507 ITALY 2.12 - 428 - KOREA 1.64 1.48 777 838 BRAZIL 1.58 1.49 997 934

This vital industry is facing many challenges today. On one hand, metal casters have to meet the rising expectations of customers in terms of quality assurance, shorter lead time, smaller lot size and competitive pricing. On the other hand, foundries are severely outpaced by the rapid technological and management changes taking place in other manufacturing sectors. One example is the increasing use of NC machines for finishing operations, which require dimensionally stable castings with uniform surface hardness to prevent damage to cutting tools. Another example is the adoption of Just-In-Time philosophy by assemblers to reduce their inventory costs, which requires foundries to deliver on-time (often in terms of a particular date, time and factory gate number). Increasing pressure from regulatory bodies in terms of energy conservation, environment protection and operational safety is of additional concern. Many leading customers, particularly in the automobile sector, are therefore moving toward long-term strategic partnerships with a few capable foundries instead of short term cost-based purchasing agreements with a number of foundries as in the past [3]. This means that in order to survive, foundries have to offer dimensionally stable and sound castings (preferably with self-certification) and ensure reliable on-time delivery, more so in the case of export orders. To achieve customer satisfaction without sacrificing profitability, foundry engineers need to precisely model and control the casting process to obtain the desired quality and optimize the yield without repetitive and time consuming shop floor trials. This is not easy, since casting is an inherently complex process. Flow, solidification and cooling of molten alloy in an intricately shaped cavity surrounded by heterogeneously packed mold material is complex enough; the range of geometric, material and process parameters involved in a foundry and the changing nature of customer requirements make each casting project a new challenge indeed. A lifetime of experience may well be inadequate to confidently predict the outcome of a new casting project. It is no surprise that even in advanced countries, casting yields continue to be low, the average scrap rate is as high as 7% [4] and the average lead time for the first article of approval is 10-14 weeks [5]. One reason for this state of affairs is that casting sector has attracted much less research and development work compared to other manufacturing processes. The relatively nascent machining sector has grown far more rapidly in terms of processes, equipment, control, optimization and reliability, as evident by the large number of research publications, industry journals and general awareness among engineers. Casting has perhaps been considered a no-man's land between mechanical and metallurgical disciplines, aggravated by the difficulty in attracting and retaining qualified personnel in this area, both in industry and academia. Thus despite being a 5000 year old process, casting continues to be more of an art than science. Compared to the age of metal casting, computer and information technology is barely 50 years young. In fact, it was only in 1980s that the inexpensive IBM PC (and its compatibles) led the widespread proliferation of computers in all walks of life. Word processing, accounting, reservations, catalogues, banking, e-mail - computers have helped in speeding up information retrieval, data-intensive transactions and decision-making, enabling us to perform routine tasks in lesser time.

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The success of computerization arises from the ease of programming the computers to carry out a specific set of instructions, handle a large amount of data and process it rapidly. As sophisticated tools for programming appeared along with more powerful computers in terms of data storage and processing speed, the software has become more comprehensive and user-friendly. Thus the ratio of software cost to hardware cost, which was less than 1:10 in 1980s, is the other way round now and climbing further. The earliest programs for casting appeared almost as soon as personal computers became generally available around 1980s. These were simple calculation and drawing programs, which gave way to sophisticated computer-aided design and simulation software of the 1990s. As the new millenium is fast approaching, a new breed of intelligent software - which mimics the way expert engineers perform their tasks - is on its way. 2 Computer-Aided Casting Today, casting engineers have access to a range of software tools to assist in the design, manufacture and management tasks associated with casting projects. The following sections chart the evolution of these software tools, mainly focussing on casting design which has witnessed more progress in terms of computerization. 2.1 The 1980s - Basic CAD The earliest CAD programs enabled computer-aided drafting and simple design calculations (Fig.1). The popularity of electronic drafting was fuelled by AutoCAD software from Autodesk, Inc. USA. For the first time, it became possible to create and correct a drawing on a computer and automatically make its hard copy on a plotter. It also became possible to store a large number of drawings efficiently, retrieve a particular drawing instantaneously and modify it quickly to create a new one. Many design engineers preferred to use the software themselves, thus dramatically increasing the productivity of the design office, and rendering the job of conventional drafting fairly redundant. Though it is much easier (and with fewer errors) to create a casting drawing from a part drawing if available in electronic form, foundries continued to receive paper drawings of parts from their customers and relied on conventional drafting methods to create casting drawings. A few progressive foundries who might have installed drafting software had to recreate the part drawing from scratch because of the difficulty in transferring files of complex drawings (most castings are complex!) across isolated computers and different CAD programs. In the same decade, the earliest programs for casting engineers appeared. These were mainly small, interactive programs for design calculations running on PCs in MSDOS operating system. Published applications included interactive programs for the design of risers (feeders) and gating channels [6.7]. The user has to enter the type of cast metal, part weight, section modulus, average section thickness, type of risers and gating system, their location, etc., and the programs design the dimensions of the riser and gating channels. Other interactive programs were developed for weight estimation, charge calculation, cost estimation and quality control charts. Such programs, many of them written by enthusiastic foundrymen, laid the foundation for computer-aided casting. But the design equations and the required data were often hard-coded, which means that the programs could not be used by other foundries without rewriting them again. The programs were developed with proprietary data formats and were essentially stand-alone. They required painstaking entry of input parameters again and again for each iteration, and a single wrong entry could mean incorrect results. Since few such programs were commercially available, they remained little more than interesting gizmos in isolated companies and did not gain much popularity among foundry engineers in general.

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2.2 The 1990s - Desktop Simulation By early 1990s drafting programs had evolved into solid modeling programs (again, spurred by AutoCAD R12 with Advanced Modeling Extension). These programs enabled accurate calculation of geometric properties and realistic visualization of the part model, besides automatic generation of conventional 2D drawings. Simultaneously, programs for casting solidification and mold filling simulation based on Finite Difference and Finite Element methods started appearing. The part models could be transferred to simulation programs through standard data exchange formats such as DXF and IGES (Fig.2). Casting simulation programs essentially decompose the part model into a number of simpler elements (bricks in the case of Finite Difference and tetrahedrons in the case of Finite Element) and progressively apply the equations for heat transfer or fluid flow to all elements; the calculations are repeated for several time steps until solidification or mold filling is complete [8,9]. The progress of filling or solidification in the mold can be visualized through color coded plots, which helps in predicting the location and intensity of major casting defects such as shrinkage cavities, porosity, air entrapment, erosion and cold shuts. Thus foundry engineers can check several different alternatives for feeding and gating design and finalize the optimal layout without pouring a single casting. Today, a number of casting simulation programs are commercially available [10]. In general, Finite Element based programs are more complex to develop (therefore expensive) and use, but give better results because they can model the casting shape more accurately than Finite Difference methods. Some of these programs perform coupled simulation of mold filling and solidification, which gives better results for thin wall parts such as in investment casting and pressure die-casting. A few programs also simulate the cooling of the casting after solidification, which helps in predicting phase transformation and mechanical properties. All physics-based simulation programs require a comprehensive database of cast metal and mold materials with temperature-dependent properties for reliable results. Such databases are available only for common engineering metals, and usually need to be customized for a particular company. Another factor affecting the accuracy of predicted results is the size of elements. Smaller elements and more time steps give better results, which however requires higher computational power. Thus more sophisticated programs for simulation have been developed for Unix-based engineering workstations, and are in use mainly at large foundries (usually belonging to automobile giants) and research organizations. The majority of foundry users prefer PC-based simulation programs owing to lower cost and ease of use. A recent survey of 11 casting simulation software used in 154 foundries in the USA, carried out at the University of Iowa, provided a profile of their use and benefits [11]. About 25% of users designed and verified up to 25% of their castings using the software. Casting/tooling design time reduced by over 40%, cost of labor and rework reduced by 30% and the average improvement in casting yield was 25%. 2.3 The 2000s - Intelligent Design After the CAD programs of 1980s effected a sharp increase in productivity and the simulation software of 1990s greatly enhanced quality assurance, the focus is now shifting to global competitiveness. The increasing frequency of new product introductions is putting pressure on component suppliers to reduce their lead time from order to supply. This is most apparent in the case of automobile components. In the early 80s, new car models were introduced every 3-4 years, which is now down to 12-18 months. Progressive companies have been able to slash the development time as well as product costs by leveraging their internal knowledge base and access to experts outside the department or organization. Earlier, product requirements used to be defined by the marketing department, then R&D would evolve the conceptual design, the design department would create the detailed design, the engineering department would make and test the prototypes and then tooling and manufacturing departments would take over. This approach was characterized by a number of design changes, lost time and confusion. Today, it is well recognized that spending more time and effort on design can give far more benefits than a similar effort at tooling or

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manufacturing stage [12]. Many companies therefore constitute a task force comprising engineers from all departments and their past experience is exploited to identify potential problems in advance and prevent them through appropriate modifications to the product design. Since the entire team works together and plans in advance, this approach is aptly called concurrent engineering. One problem with concurrent engineering teams is that members have to be physically present at the same location for frequent design review meetings, which is difficult considering that experts are usually busy. One way to overcome this is by letting the team members exchange information and design data over electronic networks [13]. Virtual reality and virtual business have also been proposed to overcome the limitations of distance and time [14]. A more effective solution is to reduce the dependence on experts. This is possible by combining two new technologies which facilitate computer-aided concurrent engineering: intelligent CAD tools and software agents (Fig.3). Intelligent CAD software is distinguished from conventional CAD by its capability to perform tasks which require domain knowledge and geometric reasoning. (Expert Systems, which also contain domain knowledge and an inference engine, can not handle geometry directly). Geometric reasoning is required for automatic recognition of casting features such as cored holes from a solid model of the part [15]. The domain knowledge is required for determining whether the feature has to be produced by a core, designing the core print and evaluating the entire core in terms of strength, venting, cooling and other criteria. Intelligent CAD software will thus act like a manufacturing expert, on call anytime, to assist product engineers in design for manufacture. It can also be used by tooling or manufacturing engineers to verify their decisions and ensure that a feasible design alternative has not been overlooked. Software agents, one of the hottest areas of research today, promise to take over the task of searching for the right information [16]. This is important considering that engineers spend most of their time creating, exchanging, searching or waiting for information. Much of this can be delegated to agents. For example, if a design engineer is working on a titanium-based investment cast product with very thin wall thickness, the software agent can search the world-wide-web, identify foundries which produced similar parts, check their minimum wall thickness, compare with the current value and warn the designer if the part thickness is below the limit. Thus a combination of intelligent CAD and software agents promises to revolutionize the way products are designed. A few such systems, applicable to rapidly evolving manufacturing processes such as rapid prototyping, are under development [17]. They comprise of software agents which connect project engineers over a network through an information backbone and automatically fire heuristics-based simulation models to help the engineers optimize designs for manufacturability. Such a system has been developed for casting engineers, and is described in detail in the following section. 3 AutoCAST - The Intelligent Assistant The casting design system was developed based on a detailed study of the industry status, followed by proposing a conceptual system, obtaining feedback from potential users and incorporating their suggestions. The Foundry Benchmarking Survey conducted in 1995-96 by American Metalcasting Consortium and sponsored by the Department of Defense provided a clear picture of the industry status [5]. The survey team was led by Prof. R.C. Creese at the West Virginia University and the author was a consultant for analyzing the survey data. The study showed that the average lead time for the first article of approval is about 10 weeks for aluminum and steel foundries, 11 weeks for ductile iron and 14 weeks for gray iron foundries. Among various factors studied, tooling development emerged as the most important one, taking up as much as 80% of the total lead time. This showed that significant savings in overall lead time could be achieved by compressing the tooling development time alone, including the time for its design, manufacture and shop floor trials. For this purpose, close cooperation is necessary between all engineers involved in a casting project.

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Accordingly, the conceptual design of a computer-aided concurrent engineering system was developed and described in a web site called Casting 2000 which was hosted by the Concurrent Engineering Research Center in Morgantown, West Virginia during 1996-97. It described a suite of intelligent software tools for assisting and linking casting life-cycle engineers (product designers, tool makers, foundry engineers and supply managers) for better and faster decision making (Fig.4). The web site received encouraging feedback from all parts of the world, and the suggestions helped in designing the information backbone of the software. A prototype of the system, called AutoCAST, was developed and shown to casting engineers [18]. Their suggestions were incorporated to improve it further in terms of features, programs, database structure and user interface. These are described next. 3.1 Key Features AutoCAST has essentially been developed as an intelligent assistant to casting designers. It simulates the way expert engineers design various elements of a casting such as parting line, core, mold, feeders and gating. The entire casting design is analyzed using a set of castability criteria. Depending on the results of the analysis, suitable design changes to improve castability are suggested through context sensitive guidelines. All modules are linked through an in-built casting project database management system. The software runs on Pentium computers with Windows-NT or Windows-95/98 systems. It meets the wish list of the users in terms of the following features. Intelligent Routines: A powerful geometric reasoning engine has been incorporated in the software to intelligently suggest good first solutions, while allowing the user to modify its recommendations or impose additional constraints. This minimizes user input to achieve a specific task in casting design. Integrated Applications: The software has a range of functions useful to casting life-cycle engineers, including product designers, tooling engineers, foundry engineers, quality inspectors and managers. These functions enable the user to design, model, simulate, analyze and improve the casting design without switching between applications. Information Management: All functions are linked through a casting project database, serving as both input and output. Parts of the database can be notionally owned by a different person, department or organization, and exchanged between them over electronic networks. Internal Modeling: The software incorporates an internal solid modeler which automatically creates 3D models of feeders, feedaids, gating channels, cores, mold, etc. based on the results and attaches them to the part model, eliminating the need for an external solid modeler for this purpose. Intuitive Interface: The user interface combines database, applications and model display in a clutter-free, pleasant and easy to use environment. All programs have a uniform interface, compatible with Microsoft Windows, and can be learnt easily. Immediate Response: The software anticipates the needs of the user and positions itself to respond to the next command. Advanced techniques such as software agents, true 32-bit computing, and optimized algorithms enable real-time results. This is important to designers, who would like to minimize their time spent on manufacturability aspects. 3.2 Casting Design Programs AutoCAST comprises a suite of nine programs to perform various tasks associated with casting design (Fig.5). Each program comprises a set of modules for design, solid modeling, simulation, analysis and improvement. The programs are listed below.

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Product Design: This program helps in importing a solid model of the part from an external solid modeler through a standard exchange format, followed by computation of geometric properties. Wall thickness, section variation, complexity, holes and other criteria are used for castability analysis, followed by suggestions for design improvement. Parting Design: This program suggests the best orientation of the casting in the mold, generates several parting lines and determines the best alternative, aligns the parting line with the mold parting plane, and finally analyzes the current parting in terms of flatness, draw distance, draft volume, dimensional stability, etc. to suggest improvements. Core Design: This program first identifies cored features in the part model: through holes, deep pockets and undercuts. For each cored feature, it designs the core print and creates a solid model of the entire core. Finally, it analyzes the cored feature for failure, venting and other criteria, based on which guidelines for design improvement are presented. Mold Design: This program selects the most appropriate mold box to enclose the casting, determines the optimal number of cavities and displays the cavity layout. The mold design is analyzed in terms of metal to sand ratio, cavity shape and other criteria, based on which guidelines for design improvement are displayed. Rapid Tooling: This program suggests an appropriate route for producing master pattern, master mold, regular pattern, regular mold, master core, core box and regular core using a sequence of rapid prototyping, rapid tooling and conventional methods. It also suggests the best orientation for minimizing the fabrication time using the above techniques. Feeding Design: This program first simulates the solidification of the casting to determine the location of hot spots and suggests an appropriate location for the feeder. It also calculates the feeder dimensions, creates its solid model and attaches it to the casting. Feeding aids such as chills, insulating sleeves and exothermic covers can be modeled. The feeding design is further verified by progressive solidification plots on a section and directional solidification vectors (feed metal flow paths) inside the casting. Yield, feeding efficiency and ease of fettling are computed to compare different layouts. Gating Design: This program suggests the connection points for ingates and the location of sprue, followed by the layout of runners. It determines the optimal pouring time, designs the entire gating system and creates its solid model. Mold filling simulation is performed to determine the actual filling time, and to identify gating related defects. The gating design is analyzed in terms of yield, ease of fettling and other criteria based on which suggestions for design improvement are presented. Process Planning: This program suggests an appropriate casting process for producing the part (given its metal, weight, lot size, quality specifications, etc.). It plans the requirement of cast metal, mold sand, core sand and other materials. An activity based approach is used for analyzing the lead time and costs for producing the casting. Quality Assurance: This program helps in casting inspection in two ways. It assists in setting up reference dimensions between specified locations on the casting surface and determines the ideal distance between them. It also simulates radiography to produce the radiograph of a defect-free casting, which can be compared with actual radiographs to identify internal defects in the casting. 3.3 Project Database Management AutoCAST treats the design and manufacture of each individual cast component as a separate project. The casting project database acts like a medium of exchange (Fig.6) and serves the following objectives: • Provide a transparent window to the user to view the data related to the casting. • Enable user input required for some modules and to allow ‘what-if’ explorations.

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• Reuse of data between different functions of the software without repetitive entry. • Exchange of selected data between different users through email over a network. The database is primarily stored as a casting PROJECT, which in turn has six children: ADMIN, PRODUCT, TOOLING, PROCESS, MATERIAL and QUALITY. Each of these blocks contains information related to a specific aspect, and is notionally ‘owned’ by the corresponding person, department or organization in charge. The child blocks are arranged in a hierarchical tree structure (parent-child-grandchild). Each block in the casting project contains several pairs of fields and values. Some fields contain references to other blocks and geometric models (part, feeder, parting line, etc.). The blocks are displayed on the screen and the user can easily browse through the database, edit a value or its units, or copy a set of values from a library database (cast metal, mold boxes, etc.). 3.4 Solid Models A 3-dimensional model of the cast product is an important input for design and analysis functions in AutoCAST, and can be imported through a data exchange interface using the industry standard STL format. Other solid models: mold, cores, feeders, feedaids and gating channels are created by internal functions based on the data created during casting design. Thus the user need not switch between modeling and analysis programs once the part model is available, considerably saving time and effort. The user interface is compatible with Microsoft Windows, with a mouse being the main source of user input. The screen shows the program menu, casting database and geometric models simultaneously. The program menu lists various programs (Product, Parting, etc.) which can be clicked to display a list of modules, which can be clicked further to execute the related task. The solid models are manipulated (turn, zoom, shade, etc.) through a set of icon buttons; similarly a set of icon buttons are available to navigate through the project database. On-line help is available by clicking Help in the main menu. This includes a quick round-up of all the features, detailed information on any module and description of the database structure and related functions. 4 An Example Session The software has been used to analyze a number of castings in the industry. The range of metals include gray iron, ductile iron, steel, aluminum alloys and other common cast metals. Processes include sand casting, permanent mold and low pressure die casting. A typical session is described here using a real life example of a ductile iron automobile differential casing produced using sand casting. The part was first modeled using Pro-Engineer software (from Parametric Technologies Corp, USA) and exported as a standard exchange file in STL format. A new casting project was started in AutoCAST with preset default values. The part STL model was imported and the alloy properties were copied from the library of cast metals. The Mold program suggested an appropriate mold box considering the minimum gap between the casting and the mold wall, created a model of the mold box and centered the part model inside the mold. The Parting program suggested the orientation of the part in the mold, generated the parting line and aligned the parting line with the mold parting. The Product program computed the geometric properties, analyzed the part features and compared them with the geometric capabilities of the sand casting process. The criteria for complexity and wall thickness returned poor assessments and a guideline was displayed which suggested increasing the minimum wall thickness of the part (Fig.7). Solidification simulation performed by the Feeding program revealed four isolated hot spots inside the casting (Fig.8). Several feeding layouts were tried; each iteration involving automated feeder design, modeling, simulation and analysis. Finally, four feeders were attached to the casting and four chills were applied below the casting (Fig.9). Even then the solidification profile showed some shrinkage defects inside the casting for level 1 quality (Fig.10). This shows that a modified part design could have reduced the manufacturing cost by reducing the number of feeders and eliminating the need for chills. The gating

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design was done as suggested by the program; the filling simulation showed the sequence of filling the mold and actual filling time (Fig.11). Finally, a radiography simulation was performed to produce the image of an ideal radiograph (Fig.12), useful for comparing with actual radiographs during inspection. All the tasks described above, starting from part model importing, were completed in just over one hour on a Pentium 166 computer. 5 Conclusions Computer-aided casting design has come a long way since the early programs of 1980s and has proved its benefits in terms of enhanced productivity, quality assurance and improved casting yield. Most casting design/simulation programs usually pay back for themselves within an year. However, the software has to be comprehensive and user-friendly for widespread penetration, specially in small/medium foundries and engineering companies. The paper showed how an intelligent software can automate casting design, modeling, simulation, analysis and suggestions for improvement while allowing the user ultimate control over all decisions. While it is of great use to casting engineers in better and faster decision-making, greater benefits will be achieved by analyzing cast products at the design stage itself and preventing potential problems through suitable changes to part features. In addition, product engineers, tool makers and casting engineers will be able to share relevant information with each other over electronic networks, thereby avoiding confusion and errors and significantly reducing the non-productive time for completing a casting project. 6 Acknowledgements The motivation of and discussions with many eminent people shaped the ideas in this paper, including Prof. M.N. Srinivasan (IISc Bangalore), Prof. Robert C. Creese (West Virginia University), Dr. Shuichi Fukuda (Tokyo Metropolitan Institute), Dr. Ahmet Er (Warwick University), Dr. Al Klosterman (SDRC, Cincinnati), Dr. Mark Sammonds (ProCAST, Maryland), Dr. Erwin Flender (Magma, Aachen), Mr. Rudolf Sillen (Novacast, Sweden), Mr. Arno Louvo (Castech, Finland), Mr. S. Bharadwaja (Ex-President, IIF) and many contemporaries in CAD/CAM sector. For software coding and support, the credit goes to Mr. Ramesh Dommeti and Mr. Krishna Mohan Rao, Globe Consultants, Mumbai. References 1. Editorial Staff, “31st Census of World Casting Production - 1996,” Modern Casting, Vol.87, No.12,

1997, pp.40-41. 2. Nancy J. Davis, “28th Census of World Casting Production - 1993,” Modern Casting, Vol.84, No.12,

1994, pp.32-33. 3. C. Soman, N. Rangaraj and B. Ravi, “A Supply Chain Perspective on Initiatives in the Casting

Industry,” Indian Foundry Journal, Vol.44, No.2, 1998, 15-22. 4. D. Kaniki, “The Current State of Casting Yield,” AFS Transactions, Vol.106, 1998. 5. R.C. Creese, “Benchmarking and Lead Time Reduction,” AMC Benchmarking Project Report, West

Virginia University, Oct 1996, pp.1-137. 6. P.C. Gerhardt, Jr., “Computer Applications in Gating and Risering System Design for Ductile Iron

Castings,” AFS Transactions, Vol.91, 1983, pp.475-476. 7. P.D. Webster and J.M. Young, “Computer Aided Gating Systems Design,” The British Foundryman,

Vol.94, 1986, pp.276-284. 8. R.W. Lewis, H.C. Huang, A.S. Usmani, M.R. Tadayon, “Solidification in Castings by Finite Element

Method,” Materials Science and Technology, Vol.6, 1990, pp.482-498. 9. H.-J. Lin and W.-S. Hwang, “Three-Dimensional Fluid Flow Simulation for Mold Filling,” AFS

Transactions, Vol.97, 1989, pp.855-862. 10. AFS, “Sources of Casting Modeling Software,” Modern Casting, Vol.87, No.10, 1997, pp.27-29.

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11. D.H. Jensen, “Survey Provides Profile of Casting Design Software Use,” Modern Casting, Vol.86, No.9, 1996, pp.29-33.

12. M.A. Gwyn, “Cost-Effective Casting Design,” Modern Casting, Vol.88, No.5, 1998, pp.32-36. 13. C.D. Orogo, H.D. Callihan, G.K. Sigworth and H.A. Kuhn, “A Vision of Computer-Aided Casting in

the Year 2000,” Modern Casting, Vol.83, No.10, 1993, pp.20-24. 14. G.F. Ruff, “Metalcasting - Virtual Reality and Strategies for Growth,” Modern Casting, Vol.88, No.7,

1998, pp.62-69. 15. P.D. Stefano, “Automatic Extraction of Form Features for Casting,” Computer-Aided Design, Vol.29,

No.11, 1997, pp.761-770. 16. C.J. Petrie, “Agent-Based, the Web, and Intelligence,” IEEE Expert, Vol.11, No.6, 1996, pp.24-29. 17. H.R. Frost and M.R. Cutkosky, “Design for Manufacture Via Agent Interaction,” Proceedings, ASME

Design for Manufacturing Conference, Irvine, California, August 18-22, 1996. 18. B. Ravi and R.C. Creese, “Collaborative Design and Manufacture of Cast Products,” Proceedings,

45th Indian Foundry Congress, Mumbai, January 1997, pp.257-270. List of Figures Fig. 1 Early stand-alone 2D/text-based programs in MSDOS. Fig. 2 Simulation programs import solid models from 3D CAD programs. Fig. 3 Intelligent CAD programs are linked through electronic networks. Fig. 4 Casting information highway as depicted in the Casting 2000 web site. Fig. 5 The suite of integrated programs for casting design in AutoCAST. Fig. 6 Casting project database acts as an exchange medium. Fig. 7 Guideline suggests increasing the wall thickness. Fig. 8 Solidification simulation detects hot spots inside the casting. Fig. 9 Feeder, chills and gating channels designed and modeled. Fig.10 Solidification profile shows persisting shrinkage defects. Fig.11 Mold filling simulation indicates actual time to fill. Fig.12 Radiography simulation helps in inspection.

Fig. 1 Early stand-alone 2D/text-based programs in MSDOS.

WEIGHTESTIMATION

GATING /RISERING

DRAFTING

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Fig. 2 Simulation programs import solid models from 3D CAD programs.

Fig. 3 Intelligent CAD programs are linked through electronic networks

MODELIMPORTING

CASTABILITYANALYSIS

PARTINGSELECTION

COREDESIGN

MOLDDESIGN

QUALITYASSURANCE

RAPIDTOOLING

FEEDINGDESIGN

GATINGDESIGN

PROCESSPLANNING

CASTING PROJECTDATABASE MANAGEMENT

PRODUCT DESIGN

PROCESSPLANNING

ELECTRONIC NETWORK (LAN / WAN / INTERNET)

PROCESSPLANNING

TOOLINGDESIGN

PROJECTMANAGEMT

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Fig. 4 Casting information highway as depicted in the Casting 2000 web site.

Fig. 5 The suite of integrated programs for casting design in AutoCAST.

DATABASELIBRARY OPTIONS MODULESRESULTS

USER

CONST

OTHERUSERS

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Fig. 6 Casting project database acts as an exchange medium.

Fig. 7 Guideline suggests increasing the wall thickness.

SOLIDMODELING

CASTINGSIMULATION

PATTERNDESIGN

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Fig. 8 Solidification simulation detects hot spots inside the casting.

Fig. 9 Feeder, chills and gating channels designed and modeled.

SHRINKAGE DEFECT ZONES

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Fig.10 Solidification profile shows persisting shrinkage defects.

Fig.11 Mold filling simulation indicates actual time to fill.

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Fig.12 Radiography simulation helps in inspection.