The Present and Future of Forging Simulation

The Present and Future of Forging Simulation

Computer programs can predict die fill, load, energy, and defect formation. As applications advance and technology matures, simulation will continue to evolve into a daily production activity, even at the smallest forge shops.

Initially, forging simulation software was used by a small group of companies in the U.S. in the 1980s. The Analysis of Large Plastic Incremental Deformation (ALPID) program was developed at the Battelle Memorial Institute under sponsorship by the U.S. Air Force to support the development of gas-turbine forgings, to be used in the Advanced Tactical Fighter and other USAF systems.

Fig. 1. Forging of an aluminum component was simulated using DEFORM-3D to evaluate material flow and die fill. A piping defect was predicted prior to finalizing the quote. A trial of the original design confirmed the prediction.

Fig. 2. Process simulation is used today to develop the production of helical gears by cold extruding or hot forging.

Fig. 3. Forged steel bomb lugs were produced with a range of problems including die wear, forging laps, locating the buster in the blocker cavity, and an 11% scrap rate. Simulation led to changing the dies to include roll, bust, block, and finish stations with a resulting scrap rate of only 3%.

Fig. 4. Image shows the simulation of a forged axle beam before (white) and after (yellow) heat treatment.

Fig. 5-When a part is machined, internal stresses are disturbed, which can result in part distortion. This image shows the machined state (yellow) superimposed over the distorted part (orange).

At the time, it was a challenge to set up a simulation with very primitive preprocessing tools, extended simulation times, minimum graphics, and technical problems. Realistically, one could expect to spend several days to run a typical turbine disk simulation; with quite a bit of manual intervention. Despite those early challenges, ALPID flourished at companies striving for any edge in a very competitive market.

While ALPID was successful as a project code, Battelle staff applied their experience and background to the development of DEFORM. ALPID was limited to two-dimensional (2D) simulation for axi-symmetric (round) parts due to computer speed and software limitations. Initial applications included optimizing billet and blocker design, die fill, forging loads, and defects.

One by one, companies adopted simulation as a critical element of the design process. In 1991, the former Battelle staff that developed both ALPID and DEFORM founded Scientific Forming Technologies Corp.. The barriers to forging simulation were significant. SFTC executive vice president and co-founder Dr. Wei-Tsu Wu recalls that “practical 3D simulation was unthinkable. Problems included computing speed, mesh generation, element performance, and user interface.”

Fast forward to today. Forging (see November/December 2005, p.16) reports that 80% of the large companies (250+ employees), 75% of the mid-sized companies (100-249), and even 50% of smaller firms (50-99) are using process simulation. These numbers have more than doubled over the last decade, similar to the expanded use of CAD systems in the early 1980s. Computer modeling has become an integral part of the design and development process not only at the leading organizations, but at most forging companies.

For those not familiar with the subject, forging simulation is a computer program used to predict die fill, load, energy, and defect formation. This is based on the fact that the workpiece flows to the path of least resistance when displaced by one or more dies. The load is based on the forging size, shape, friction, temperature, and material properties. With the die fill defined, simulation can directly calculate critical process information including strain, stress, and temperature. With maturity, the prediction of grain flow, shear banding, and fracture have evolved.
Typical forging applications

Simulation applications are widely published in conference journals, magazine articles, and marketing material by simulation suppliers. Examples of common applications include:

Defect prediction—During the quotation process, an aluminum component was simulated using

DEFORM-3D to evaluate material flow and die fill. A piping defect was predicted prior to finalizing the quote (see Fig. 1). At that time, when little was committed, the supplier and customer were in a good position to discuss and consider alternatives. A trial of the original design confirmed the solution accuracy, as shown.

Product development—Competition and customer requirements have led to the development of more complex parts being produced to tighter tolerances, at a lower cost, and in less time. While most developments evolve over time, some are revolutionary. Ten years ago, helical gears for automobiles were machined from round forgings or bar stock. Today, high-volume gears are cold-extruded or hot-forged with gear teeth in a finished or nearly finished geometry. In these cases, process simulation (see Fig. 2) has been used extensively to develop the process, preform, and tooling.

Product optimization—The Forging Defense Manufacturing Consortium’s (FDMC) PRO-Fast Project, sponsored by the Defense Logistics Agency, has been documented in Forging.

One of its success stories involved a hammer forging of steel bomb lugs. This high-volume forging experienced a range of problems including die wear, forging laps, locating the buster in the blocker cavity, and an 11% scrap rate. DEFORM-3D was used to test ideas and designs from Delfasco, New Die (the toolmaker), and SFTC personnel. (see Fig. 3)

Simulation provided quantitative feedback on the influence of each idea. Studying total energy required to deform the part provided an indication of the number of hammer blows. Process stability could be determined by running multiple cases with slight variations in location. At the end of the day, the dies were changed to include roll, bust, block, and finish stations. Fewer hits in the roll station (and overall) were required. The scrap rate was reduced to 3% after 16,000 forgings (48,000 lugs). Simulation was integral to this process improvement.

Today’s simulation tools provide insight into and information about a design or process. Simulation does not design or develop the process. The mind of an experienced designer is still superior to any computer program for preform geometry, process development, and overall forging strategy.

Currently, simulation is used to provide critical information to improve the performance of the designer. As optimization techniques are developed, the contribution of simulation to the design details will continue to increase.
Advanced and future applications

While forging simulation continues to mature, software and applications are being developed at a rapid pace. A sampling of interesting developments include:

Heat-treatment simulation—A wide range of projects have contributed to the development of heat-treatment simulation. This is a far more challenging problem than forging simulation, due to complex material behavior at the microstructure level. Practical requirements include the prediction of mechanical properties and heat-treatment distortion. The image in Figure 4 shows the result of a DEFORM-HT simulation of a forged axle beam before (white) and after (yellow) heat treatment. Most of the volumetric change resulted from a phase transformation to martensite.

Machining distortion—Forming and heat-treatment operations induce internal stresses in metal components. These stresses come to equilibrium as the part distorts. Remaining stresses are called residual stress. When a part is machined, the internal stress balance is disturbed. Thus, a new equilibrium is established, resulting in part distortion. The image in Fig. 5 shows a turbine disk in the machined (yellow) state superimposed on the distorted part (orange). Several companies are running two-dimensional machining distortion simulations for turbine disk applications. Three-dimensional capabilities are under development.

Design optimization—A fully automated blocker design program has been envisioned by researchers for decades. To date, the human mind remains the best blocker design system. On the other hand, work is being done with sensitivity analysis, optimization, and other methodologies that will result in a workable system in the future.

In January/February 2000, Forging reported on the use of DEFORM-HT and iSIGHT to optimize heat-treatment processes in turbine disks. While this is an advanced application for the typical forge shop, industry leaders were using the technology for a decade or more. The article states, “Through the use of the program, residual stresses on the forged disks have been reduced by as much as 60%, and part distortion during subsequent machining has been reduced by as much as 30%. Such reductions have allowed every disk to meet machining tolerance.”
Industry changes

Simulation has been accompanied by cultural changes in the industry. Twenty-five years ago, very few designers or engineers even heard the term flow stress, effective (plastic) strain, or strain rate. Today, these are common terms.

The Forging Industry Assn. has recognized this important trend and responded by increasing simulation content in their Die Design and Press Design workshops. Initially, there was a one-hour lecture on this topic. Today, simulation examples are used throughout the courses.

Training of young engineers and designers has been influenced by simulation. The FDMC-sponsored Forging Fundamentals 101 was conducted prior to the 2005 Forging Industry Technical Conference. This workshop used simulation extensively to train attendees on the science behind forging. The cultural shift involves the ‘artisan’ methods of the past being supplemented, and in some cases replaced, by engineering and science.

Ease of use is not to be taken lightly. Researchers and analysts have used FEM codes for 25 years. Concepts such as element size, boundary conditions, convergence criteria, and time step are fairly routine. The forging market for simulation consists of designers and engineers that understand this very complex process through experience and intuition.

One challenge for code developers is to translate the user requirements into the FEM inputs. For example, SFTC released DEFORM-F3 in 2004. This three-dimensional program can be used easily by the designer or forging engineer. When setting up a forging simulation, there is a trade-off between speed and detail/accuracy. In DEFORM-F3, a slider bar was developed to automate the setup process based on the user requirement in very simple terms.

There are also a wide range of intermediate applications for forging simulation. Experienced users are modeling equipment interactions for hammers and presses, and analyzing die failures using die-stress analysis. They are comfortable with the science behind the process, and comfortable with advanced applications.

These advanced applications should be kept in perspective. Technically savvy analysts will find a way to take advantage of new capabilities as they are being developed. Designers with less modeling experience would be advised to start with proven applications. On the other hand, when selecting simulation software it can be useful to review the advanced applications to understand if it is on the leading edge of application development or in a catch-up mode.

In any case, simulation is useful in a wide range of production and development applications. Information is made available much faster than with shop trials or other experiments. Additionally, it is possible to visualize the process in a way that is not possible on a production forging press or hammer. As applications advance and technology matures, simulation will continue to evolve into a daily production activity, even at the smallest forge shops. Very few forge shops will succeed in the future without the effective use of process simulation.

Dr. Wu believes that within a decade, companies will model the surface condition, microstructure evolution, and microstructural properties. In fact, the limits may be related to material research and understanding.

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