You might think comparing music and mechatronics engineering is a stretch, but these two great disciplines have more in common than you might think. Mathematics, abstraction, and connecting the dots (aka combining multiple disciplines) are three common concepts that apply to both creating a great song and designing a smart system.
Whether you like grooving to The Beatles or enjoy Stevie Wonder’s soulful R&B, there’s something mathematically satisfying about music: notes fit together with a beat to provide harmony. There’s a method behind creating a song and it’s all about making connections between the elements of words and sounds. Similarly, mathematics is all about making connections and drawing on abstractions.
Mechatronics is a multi-disciplinary field of science that connects various subfields of mechanical, electronics, controls, systems and computer engineering to generate a simpler, more economical and reliable system. Originally, mechatronics just included the combination of mechanics and electronics, hence the word is a combination of mechanics and electronics. As technical systems have become more and more complex, the definition has been broadened to include more technical areas.
In the early days, mechatronic systems were developed based on the “Build it, Paint it, Add Controls” paradigm. The development process was governed by the mechanical design and controls were added as an afterthought. Design errors, requirement misses, all attributed to longer development times and costs.
Such a sequential approach is simply not possible anymore for a lot of today’s mechatronics products – be it the driving stability of a modern passenger car or the energy consumption of an air conditioning system. Their complexity requires the use of simulation models from early concept design to final validation testing. These simulation models need to cover various disciplines allowing the assessment of the system’s functional behavior and hence optimization with respect to cost, weight, performance and endurance.
While conventional Computer Aided Design (CAD) and Computer Aided Engineering (CAE) technologies are well adopted in the Industry, the application of these technologies are focused mostly on virtually prototyping of Mechanical systems for various Engineering KPI’s such as NVH, durability, crash and so on. When the focus is on the Mechanical system alone, the common approach is to virtually design and improve the system by leveraging a shape-based approach. The geometry of the mechanical system, the material, and boundary conditions are all starting points to virtually design and simulate the system. In other words, the shape and structure are visible – the function of the system you’re trying to simulate is not.
Model-based Development provides a new approach to simulating and improving Mechatronics systems. It provides a framework to model, simulate, and optimize the functional performance of Mechatronics systems (aka multi-disciplinary systems). This approach leverages using abstract mathematical blocks to model, simulate, and improve the functional performance of multi-domain systems.
As shown in the extended V-model from Eigner et al., Model-based Development enables the user to drive the interdisciplinary system design and system integration process.
There are several benefits to Model-based Development when applied during a product development process. Let me illustrate a few:
- Improve system-level performance by running integration & synthesis studies: Simulate and improve the dynamic behavior of any multi-disciplinary system. You can effectively incorporate functions of sensing, actuation and control coming from diverse components such as electrical, mechanical, hydraulics and controls
2. Efficiently Design for Robustness: Model-based Development provides an efficient approach for establishing a common framework for communication throughout the design process. Perform what-if analyses at the system level to quickly test several designs and investigate the interactions of all components in a system
3. Gain Functional Insight Early: Identify system level issues at the concept design stage. Simply drag and drop blocks that specify the functional definition of the system and provide directional insight. And simulate the model within seconds!
The system models that you develop at the concept stage can be reused when you’re at the detailed design stage. Model-based Development provides a common framework across various stages of a product development process. The Functional Mock-Up Interface standard further allows users to leverage a common, tool-independent standard for model-exchange and co-simulation of dynamic models. This approach allows you to combine detailed CAE models of your mechanical system with detailed controls models and understand the combined system behavior. This insight allows you to further improve mechatronics system performance and design superior mechatronics systems.
If you have read to this point, your next question might be: how do I do it? solidThinking has recently released a Model-based Development technology suite that drives innovation through simulation by uniquely combining math, signal-based, physical and 3D modeling technologies for concept studies, control design, system performance optimization and controller implementation & testing. To learn more about the new products, please visit solidThinking.com. There’s also an opportunity to interact with our experts and learn more – Attend our free webinar on Model -based Development on Aug 23rd!
If your interest was merely for music and engineering, you may want to put your headset on and listen to what might happen if chords and notes were tied to OptiStruct iteration parameters of mass and other numbers in this video, “The Music of Topology Optimization”:
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