Climbing hardware manufacturer DMM International Ltd. (Wales) has found that using QForm forging simulation software to prevent errors at the design phase of production tools significantly reduces the cost of bringing their product to market. In applications where life is (literally) on the line, simulations improve product quality, enhance safety and reduce process costs.
Engineering practice shows that the cost of fixing errors at the manufacturing stage is an order of magnitude higher than preventing them at the design stage, and fixing the same error at the operational phase is two orders of magnitude higher than at the design stage. This is a compelling argument to prevent errors during the product design phase.
The design of forging technology consists of the development of the basic technology, the assessment of its quality (defects, tool life, selection of equipment) and the refinement and optimization of the technology to eliminate any problems found and improve the process efficiency.
Traditional technology design and optimization through full-scale experiments and trial forging is expensive. In addition to equipment and material expenses, there is the cost of the time lost on equipment setup, dies and technology refinement. Since the first attempt at fixing a problem may not be successful, the technology refinement required to produce complex forged pieces may take several iterations. This causes the development cost and time spent to grow considerably, which adds up to an increase in production cost. Full-scale experiments have been required to predict surface properties of the finished part, as well as determine the wear and stress patterns of die tools used during the forging process.
Software packages for simulation of forging processes provide error detection and tools to eliminate errors during the product design phase, as well as comprehensive verification of the technology. Simulation allows assessment of the structure and properties of the finished part without the need for trial forgings. It also estimates tool loads and tool wear, which allows for optimization of tool geometry to increase its service life. This approach significantly reduces product-development time and production cost, since all tests may be performed using a computer with simulation software.
An innovative climbing hardware manufacturer called DMM International Ltd. (DMM) in Gwynedd, Wales, has found that using QForm forging simulation software to prevent errors at the design phase of the production tools significantly reduces the cost of bringing their product to market.
DMM uses QForm to detect defects such as flow-through defects, laps, under-fill of die impression, excess flash, fracture caused by exhausting the resource of plasticity, positioning and buckling problems in the body of forged pieces. The location of material grains and the application of loads may be correlated at the design phase to avoid problems with undesirable macro- and microstructures. These are essential in the development of forging technologies for critical parts with different heights and thicknesses throughout the part.
The software allows prediction of macro- and microstructure of finished parts using both standard functions and customized model algorithms programmed in LUA language. Heat-treatment simulation after forging is also possible for predicting strength properties of finished parts. A convenient interface for simulation planning improves process efficiency and allows for quick simulation of several technology options in batch mode.
DMM produces a forged belay pivot. Since lives depend on this critical piece of climbing gear, it is crucial to ensure the highest production quality. DMM encountered a flow-through defect on the body of the forged piece while trial-testing their initial forging technology. The defect is circled in Figures 1b and 1c.
The exact location of the defect was identified by simulation using a special field in the program tools for detecting these types of defects as well as subsurface Lagrangian flow lines. The simulation results are shown in Figure 2. The
subsurface flow lines clearly show that the defect visible on the surface also penetrates deeply into the body of the forged piece.
The most likely areas of defect formation in forgings of complex 3-D geometry are easily identified visually using a special field (Fig. 2b) and then further analyzed by under-surface Lagrangian flow lines (Fig. 2a).
Once the defect was identified, it was eliminated through several iterations of tool geometry and process refinement and verified by simulation software. The optimized final design provided a 20% reduction of the workpiece volume, which is an important aspect of cost reduction during the development of a production process.
The comparative analysis of the initial and optimized tool geometry is shown in Figure 3. The metal flow at the end of the forging operation was changed by modifying the central part of the tool impression to keep the metal from flowing in the opposite direction (Fig. 4).
The simulation results for the optimized technology (Fig. 4) demonstrate complete absence of the defect. Subsurface flow lines do not penetrate deeply into the body of the forged piece. Production based on the improved technology design has confirmed that parts have no defect.
Another example of optimization through simulation during the design phase is a D-Ring produced by DMM (Fig. 5). This part had a long history of production problems. A lap appeared on the surface of 60% of the pieces forged in production, which resulted in a fault or a requirement for additional machining. The problem was that the technology required extremely accurate positioning of the workpiece in the die. Just 2 mm or more deviation from the ideal positioning of the workpiece would result in a lap. Moreover, piercing a hole in the workpiece before the forging operation added an extra operation to the process chain. The dies also had significant and uneven tool wear. Simulated results of the incorrectly positioned forged piece are shown in Figure 6.
This technology was improved considerably through simulation without performing trial forgings (Fig. 7). The simulation verified the benefit of several improvements to the design. A cavity was added in the lower tool to allow space for excess metal to flow into. A standard workpiece could be used that did not require preliminary piercing, which reduced the number of operations in the process chain and, consequently, reduced the production cost. The modified metal flow reduced the abrasive wear on the tools and achieved uniform wear over the entire surface of the die impression and flash gutter.
The most important benefit was that the new technology, achieved and verified through simulation, was not so sensitive to positioning since it utilized a solid workpiece. Production saw a complete elimination of rejected parts because there is no lap on the critical part of the forging in the new design.
Economic Impact of QForm at DMM International
The implementation of QForm at DMM took several months and included training and commissioning of the software, as well as implementation of the software in the process of preproduction engineering. The forging processes for multiple sizes of the same type of D-Ring (Fig. 5) were modified during the implementation phase.
The economic benefits of eliminating the need for trial forgings and tool modifications while developing the process into full production were estimated. The company’s cost of full-scale experiments and trial forging was approximately $625 per test, including the costs of retooling and related expenses associated with interrupting production. The tool refinement cost is about $62.50 per working hour.
For this project, DMM performed approximately 20 experiments by computer simulation using QForm. Consequently, the savings from eliminating the laboratory testing are approximately $12,500. The designed tool did not require refinement, which saved approximately 60 working hours valued at $3,750. Thus, the total cost savings of eliminating the trial forging amounted to $16,250.
Regarding the data in Figure 8, Darren McMaster, DMM design engineer, said, “The product A column represented the estimated savings we would have realized if we had QForm at the time we were trying to get a particularly complex part to forge. The product range B column shows the estimated savings for a new product that we were considering at the time based on what problems QForm found before we had even cut tools.”
Cost-saving values, presented in Figure 8, have been obtained by extrapolation of the resulting economic effect on the production of other types of parts (columns A and B). Total savings by the aforementioned item of expenses is $65,625.
It should be noted that these numbers do not include calculations of economic benefits from reduced technology-development time, reduced material consumption, reduced tool cost or the reduced amount of rejected parts. Thus, the true economic benefit is actually greater.
Moreover, there are technology options that are not possible or rather expensive and difficult to assess without simulation. Among these analyses are, for example, predicting the grain structure and stress-strain state of a forged piece, evaluating the thermal conditions of the forging process and estimating the stress-strain state of the die to predict die wear. All of these imply a deeper analysis of the developing or existing technology, which allows the most-effective optimization of the technological process rather than conventional elimination of defects in the body of the forged piece.
- QFORM VX [electronic resource] // QFX Simulations Ltd.: company website – URL: http://qform3d.com/products/qform (date of access: 13.01.2017)
- DMM products [electronic resource] // DMM International: company website – URL: http://dmmclimbing.com/products/belay-abseil/ (date of access: 13.01.2017). – Screen Caps
Co-author Darren McMaster is with DMM International Ltd., Gwynedd, Wales. He can be reached at email@example.com. Co-author Stanislav Kanevskiy is with QFX Simulations Ltd., Gzira, Malta. He can be reached at firstname.lastname@example.org. Co-author Dr. Yury Gladkov, is with Bauman Moscow State Technical University, Moscow, Russia. He can be reached at email@example.com.