Autonomous Optimization of Uncertainties in the High Pressure Die Casting Process

Spray - Autonomous Optimization of Uncertainties in the High Pressure Die Casting Process

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The High Pressure Die Casting Process

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In theory, the high-pressure die casting process is simple: Molten metal is injected into the mould, solidifies a few seconds later and is then ejected as a casting. The mould gets treated with a lubricant to avoid having the casting stick to the mould then complete for the next "shot".

In reality, this simple-sounding process is highly unstable. For example, a nozzle intended to spray lubricant on the mould face may loosen and spray over a wider area than intended - or may clog partially or completely, restricting the whole and area of the spray. Missing a sufficient layer of lubrication, castings may stick in the mould, crack during ejection then have to be found within the yield batch and scrapped.Similarly, melt volume in the holding furnace at the die-casting machine can turn the melt volume dosing into the machine chamber. This in turn changes the metal fill pattern into the cavity by addition turbulences and the amounts of air that are entrapped in the casting creating porosities. Or think a basic variable: the climatic characteristic of the mould. In order to eliminate pre-solidification during cavity filling the mould has to be brought to working climatic characteristic of almost 400° F / 200°C.

However, the liquid melt injected into the mould heats it beyond this temperature, which, if left unaddressed, would affect the functional life of the mould. In an effort to regulate this variable, liquid cooling medium containing flowing water or oil is forced straight through channels in the die steel. Even so, the mould itself changes over the policy of a yield run; as it heats from room to yield temperature, it increases in size; components that held the mould complete in an unheated state may no longer function correctly or completely. Even the health of the die-casting machine itself changes during a yield week; adjustments made on a cold machine yield distinct scale readings when the machine reaches yield temperatures. Variations are gift when unexpected breaks occur; the longer the machine stops, the more difficult it becomes for the operator to equilibrate the temperatures again. Furthermore, mould aging affects casting results: the mould wears at distinct speeds in distinct areas, affected by melt flow patterns, location of clamps, scale build-up in cooling lines - all of which want the operator to permanently strive to equilibrate the mould temperature.

In short, the high-pressure die casting process is in continuous flux - and the outcome is in the hands of the shop floor personal.

Process Simulation

Blaming only the shop floor personnel for bad castings would be as easy as it is unfair. In the most cases, poor capability results not from the efforts of the floor personnel, but from far earlier in the engineering process: the yield process may have been insufficiently developed; the casting shape may have been poor designed. In whether case, a good capability casting will never be achieved. This is where process simulation can be of the many help.

In the first stage of process planning, casting simulations can be performed, long before cutting die steel or the publish of the final casting design. Using Cad files of the early casting create ideas in composition with theoretical process parameters, simulations directly point to possible problems. At this point of development, the casting create and manufacturing process can be changed easily, quickly and inexpensively. With experience, a well-trained die casting engineer using simulation tools can generate a process that yields good capability castings during the first die trials.

In the most cases this success is achieved by designing a mould using one set of possible process parameters only. Given the volume of parameters possible in the casting process, and the range of difference within those parameters, the whole of possible interactions that the engineer could think coming infinity - as would the time needed to research those possibilities.With slight time and resources - and having achieved these good castings straight through singular parameter simulation - the engineer may stop at this point, and turn his attention to other project, leaving shop floor personnel to decree any additional yield variations.

Autonomous Optimization and Uncertainties

Autonomous optimization is mainly used to find a good process set but can also legitimately recognize dependencies and sensitivities between these process parameters; such as casting and cavity designs, fill and cycle times, mould and melt temperatures, and their levels of variations can be defined within the schedule and simulated. The optimization software autonomously selects parameter, simulates the set and evaluates the results. By smart choice based on genetic algorithms one of the best parameter set will be found out of the thousands possible variations.

Autonomous optimization should not simulate all possibilities and define the 'best"; rather, the target is to find an optimum in the shortest time and the least amounts of simulations - and without requiring more than two hours of the engineer's time (one hour for set up, one hour for result analysis.) As the simulations are done on an office computer and do not affect production, the engineer can simultaneously continue to work on other projects.

In addition, as parameter sets are not lost after the simulation has been completed, they can also be additional analyzed at a later time and in greater detail of sensitivities to each other. To start an optimization, parameter values are prime by random or based on designs of experiments. Doing so should furnish sufficient results to imagine sensitivities between the defined parameter even before beginning the optimization. Sensitivity analyses are a by-product of the autonomous optimization; using a small create of experiments, this beginning array can be increased and analyzed by its own.

Producing good castings in a carport process is an achievable goal; it should not, however, forestall developing additional improvements. Admittedly, it is very difficult to hunt for uncertainties under yield conditions, let alone to get consent from administration to stop yield in order to hunt for uncertainties, which may not exist at all. Yet what is almost impossible to perform on the shop floor could be an easy target for simulation tools. For example, controlling a singular variable, such as mould temperature, might be feasible, if difficult, on the shop floor - but experimenting with changes to the mould straight through welding and grinding might be impractical in a working situation. Time and personnel would be required for each alteration, and the cumulative result of the welding and grinding would sell out die life to the extent that this experiment would not make much sense. Using a computer simulation of the changes, however, allows the engineer to analyze the efficacy without threatening the life of the die. Rather than legitimately welding the mould, a Cad file is substituted autonomous and the choice of a climatic characteristic profile is done with the push of a button.

The use of simulation software is also more efficient than 'real world' experiments; rather than shutting down a yield line for 'trial and error' experiments, one set of parameters can be analyzed straight through a simulation even as the yield of other casting continues, resulting in more efficient yield of higher capability castings. Even so, the engineer should think the time frame complicated as well as computer hardware availability, and settle on the most foremost variables. think the task facing an engineer who wants to optimize a casting process by considering the following variables: mould climatic characteristic fluctuating from 250° F and 450° F in 50° F increments gives five levels of variation; three levels for the use of a lubrication nozzle; four levels for pouring temperature; three for pouring volumes and two for distinct casting designs results in 360 iterations to simulate. Depending on the casting create and use of a proper desktop computer one simulation could take up to one hour; to process all 360 permutations could take 15 days - still far faster than attempting to do so on a yield machine, providing that such an test is possible at all. Using more great computer this benefit leans even more towards simulations. Not to stretch the releases of faster machines in the future. Even today by investing in high-end equipment the discussed calculations could be done in less than 3 days.

Summary

Using state of the art computer hardware and the right simulation program, engineers can furnish much more facts about their high-pressure die casting process even before process improvement than during yield ignoring simulation at all.Before implementing fabrication, processes can be optimized, influencing parameter can be found, dependencies can be defined and tolerances can be implemented based on these dependencies and variations in influencing parameter. With this knowledge at hand and the right monitoring systems, yield processes are well understood and able to furnish good castings under carport conditions.

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