autonomic optimization in high pressure die casting - simulation was yesterday - die casting porosity

For more than 5,000 years, the metal has been cast to turn the original ore into a tool available.
At first, the casting was limited to very simple and small structures, but now we see the weight of the casting ranging from an ounce to several thousand pounds.
The new casting process developed over the last few hundred years allows modern casters to produce very thin and complex castings that can have predetermined quality features at a level far below sight.
These are not individual castings produced in the laboratory;
These are mass production with small tolerances for size, grain structure, mechanical properties and strength.
Initially in the 19 th century, casting was limited to pouring liquid metal gravity into the mold.
In the 19 th century, a more mechanical casting method was developed.
The first die-casting-
In 1849, the relevant patents were granted for small manual machines produced by mechanized printing types (1)
Is the pioneer of high pressure die casting machinery. In the high-
Pressure die casting, the process of liquid metal is not poured into the sand type by gravity, but forced into the steel mold by high pressure.
The advantage of this process is the shortest path from liquid metal to the final product.
The casting wall can be very thin and most sizes do not have to be processed after the casting process.
A mold can make thousands of castings, maintaining low cost and high quality.
There are shadows where there is light.
These advantages are through an expensive investment in die casting machines and related equipment, especially high quality steel, molten feed systems in casting shapes (runner)
And processed into a cooling line.
Finding the right mold design that meets its purpose requires a lot of experience from responsible engineers, as well as a lot of attempts to use trial and error.
The 21 st century has made great progress in the modernization and improvement of high pressure die casting in the past few decades, including automatic sprayer and casting extraction system, more efficient furnace and pouring device, better control
Monitoring System for casting machinery and computer.
All these improvements make the die casting process more efficient and controllable and help to produce higher quality castings.
At the same time, however, today's die-casting industry faces challenges that were not seen by early casters.
Experienced metal casters are about to retire
At the same time, however, many stores have encountered difficulties in recruiting young engineers for training as a replacement.
Higher requirements for casting quality standards, international competition, customer requirements for lower prices and difficult economic situations around the world all affect profits and corporate profit margins.
In addition, the demand for shortening product development time is increasing, which requires casters to produce good castings for the first time, otherwise the cost structure of making money is at stake.
The process simulation was introduced into the die casting field in the late 1980s s.
Metal Casters allowed for process simulation (
Designer or engineer)
Create simulations of the parts to be cast, predict possible results based on input variables, and optimize these results by using computer processing power rather than traditional experiencebased trial-and-
Error method.
With desktop computers and workstations appearing on each table, process simulation can be used by each engineer.
Computer-aided design support (CAD)
A system volume model can be created quickly and used as a direct input to the simulation.
The simulation conducted in 1993 may take a month of casting shape input, and the calculation and results evaluation may take a month.
Today, 20 years later, the full cast file is loaded into the software with a mouse click and calculated in minutes.
The most important thing now is the outcome assessment.
The intensive part of the simulation takes the longest time.
Engineers must look at different result files and compare them with each other in order to better understand the design and process parameters used.
Despite the fact, soft
The hardware is much faster than it was a few years ago, and the human factor is not that it takes hours or days for the project to make the final proposal.
Autonomous optimization leading software providers do see results evaluation as an engineering bottleneck and shift their proprietary software from a single simulation approach to autonomous optimization.
The software adopts a set of defined designs and parameters in the first simulation iteration.
These designs and parameters are then changed based on the given tolerances and the results found.
This process follows the rules of evolution: Each layout change is retained, eliminated, modified, or combined with an already calculated or new design (2).
This "change and comparison" allows the software to optimize the casting process within a given tolerance range, but the engineer does not have to take the time to look at the results and make improvements manually.
Engineers have time to focus on project tasks that are more important than simulation sets --
Ups, evaluation and comparison of results.
The filling parameter optimizes the filling process by pushing the liquid melt into the piston motion of the mold cavity.
The melt is poured into the tube through a hole, called the shot sleeve, closed by one side of the piston and the other by the mold.
After filling the sleeve to a specific level, the piston moves slowly forward, pushing the melt to the mold.
When the melt reaches the casting cavity, the piston accelerates to high speed and fills the cavity at a speed of 1/10 seconds.
The filling speed is crucial because the slower filling speed will make the melt too cold, while the faster filling speed will not give the trapped air the time to escape.
Melting too cold or too much air will reduce the casting quality.
Finding the right compromise is an important task.
For optimization software, it is a simple task to use the changes of these fill parameters.
Engineers can take over simply by creating a template that includes the parameters to be changed, step changes, and tolerances.
It chooses to start the design and changes the parameters based on the changes and tolerances of a single simulation.
The interpretation of the filling result is done automatically according to the melting or mold temperature at the end of the filling, the filling time or the air volume value.
Once boring and time
Now the engineering task has been downgraded to an automatic, more precise process.
It would be nice to simulate all possible changes and compare them, but based on a large number of possible changes, this is impractical in most cases.
For example, in 7,776 simulation runs, simulations with only six parameters and five variations will end.
Assuming the average time for each simulation is three minutes, the whole project will take more than 16 days to complete, which is the time that most metal casting engineers no longer have.
Today's software uses genetic optimization algorithms.
As in the biological world, the evolutionary process of autonomous optimization occurs in several generations of computing.
The general algorithm creates new changes to fill parameters based on defined targets such as high temperature and/or low air volume.
The process is repeated before the design modifications do not result in additional improvements.
Component optimization the opportunity to obtain a new project or to change the design of the casting or mold, such as adding fins, more wall materials, overflow positions, gate positions, ingate changes, cooling or heating lines, mold materials, etc.
, Requires action in the engineering team.
Choosing the best design from all given possibilities is usually related to failure, even if the person involved is experienced.
On the other hand, autonomous optimization provides the possibility for casting projects to simulate and find suitable elements.
For software, it is an easy task to simply design these individual objects and switch them from simulation to simulation.
For example, calculate a specific set of components and select the runner model to be replaced by a branch with more or less branches;
In the absence of engineering intervention, the software automatically loads the new design and performs calculations.
According to the defined target, the computer will find the best component configuration in a short time.
What the engineer is going to do is evaluate the best simulation results and then release the best design to build the tool.
The most exciting choice to optimize using a parameter object is to manipulate the object by simply changing the value.
Numerical parameters can be used to manipulate the runner system, rather than drafting and designing multiple runner systems to be selected for optimization.
You can increase or decrease the Ingate area by simply adjusting the parameters of the ingate thickness or width.
By changing the numerical values of the runner length, angle and/or direction, it is easy to balance the runner system of one or more cavity molds.
With a given template, you can define, build, and prepare to run the system for optimization in a matter of minutes, including changes to multiple running branches and ingates.
Overflow and vent sizes can be adjusted in size and volume to reduce air retention and air holes.
Balancing the hot profile of the mold to reduce the flashing of the mold, cold transportation and increase the life of the mold, it is crucial to place the cooling pipe line, but when using the optimization tool, this becomes a simple task.
The start and end positions of the line are defined digitally, can be changed easily, and dependencies can be easily defined.
By changing the line temperature value, cooling and heating can be simulated as needed.
Summing up for thousands of years, foundry technology has changed a lot until the dawn of the computer era.
Electronic equipment allows the construction of fully automatic production processes using handling robots and monitoring systems to improve quality and productivity by reducing hard-working labor.
With the help of independent optimization tools, the research and development work in the direct production area can be realized.
Due to the waste of time, casting volume and cost of the production machine, the factory workshop no longer makes trial and error.
In a very short period of time, the optimization took over the simulation process, eliminating the high cost of manual correction and waste of engineering time.
Engineers today define a process with a tolerance window and what the process must achieve, and optimization will produce the best results. 1. )
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Casting Design becomes self