Simulation has become a vital factor in product designing if we wish to create a fault-free product with greater efficiency. Not only does it help in eliminating faults and errors in our model before implementing it on hardware, but it can also help you save expenses in the long run.
Let's take a closer look at simulation-driven product development and how it can improve efficiency.
In DOE, let us assume that in a particular rib, you have width, thickness, and angle, and you wish to see how your system varies by tweaking specific parameters, such as altering the width from -w to +w or thickness from -t to +t.
These parameters can change your design target factors, such as stiffness or stress. DOE helps you deduce the most suitable variables for your system design without compromising structural integrity.
For instance, you can calculate the best configurations and figures for various dimensions while designing your system out of 50 Permutations and Combinations.
DOE lets you strategically eliminate values that might not work for your system, even before actual simulation. After DOE, you can move on to optimization to scale your results.
After landing on the correct values of thickness, width, or other parameters, you must see how your system gets processed.
Consider that you have selected 2mm as the final thickness for the pump valve of your system, which you have depicted using the straight line.
We set the Upper Spec Limit at 2.1 while the Lower Spec Limit is at 1.9. As we test the system, the thickness value deviates from the intended figure; however, it remains between the USL and the LSL, implying that the system would not encounter any deterrents in its operation.
To understand this from the perspective of processing, we consider the following figure.
Here, the graph has a normal distribution to depict the variation of thickness for various components.
For most of the components, the thickness remains at 2; however, some sections exhibit a thickness value that exceeds the USL or falls under the LSL benchmark, which is not acceptable.
We measure the values of various parameters using a quantity called 'Cp.' We define it as the ratio of the difference between the USL and the LSL by six times sigma, where sigma is the standard deviation.
The first figure denotes Cp<1, which is not acceptable. Thus, the process, as mentioned in the first distribution figure, is not practical for implementation.
The second figure denotes Cp=1, which might be considered as the values almost touch the USL or the LSL but remain within the desired limits.
However, practical implementation of the second system is still not viable as the value of a parameter hitting extremities would significantly reduce the confidence level in the machine as it would have a higher chance of breaking down.
With Cp>1, the extremities of the parameters are well within the limits of USL and LSL. This representation is ideal for how a system must exhibit its characteristics.
This figure describes how simulation can help in product designing. As you propagate ahead in product designing, cost skyrockets exponentially.
You can make alterations in the lower stages of development; however, in later stages, you cannot afford to include any changes as it would not be economical.
Here are some reasons to involve simulations in your product designing pathway and how simulation-driven product development can proliferate profits and boost efficiency -
Here are some statistics to prove that simulation has benefitted various organizations in boosting efficiency, product authenticity, and reduce malfunctions.
According to this table, the companies using simulation have been able to decrease physical prototypes by 44%. Even the companies that have not harnessed the power of simulation tools have reduced prototypes by 32%.
The number of iterations has increased by 56% for companies fully harnessing simulation and 27% for the ones still in the development phase of implementing simulation.
We define simulation-driven design as a design process where decisions related to the behavior and performance of the system in all major phases of the process get supported by computer-based product modeling and simulation.
We use simulation in every stage, including verifying your concept by simulation, optimizing it, and ultimately improving the model before actual implementation.
Below are the various stages involved in product design where simulation significantly helps in squashing bugs, faults, and improving performance -
Simulation has proven to be a cost and time-saving addition to the product development process over the years. As such, understanding the fundamentals of simulation is a must for those who want to pursue a career in product design.
Learn more about simulation-driven product development by visiting Skill-Lync and upgrade your skills for substantial job opportunities.
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