Artificial Intelligence in Mechanical Engineering – A Tool for 2020s Design Solutions

October 8, 2024

Artificial intelligence (AI) has quickly become one of the most essential technologies capable of enhancing many industrial sectors, including mechanical engineering and design. While AI may still sound like a distant, even futuristic concept, it is likely to play a significant role over time in improving the efficiency and innovation in the field.

In this blog post, we will explore the current and potential applications of AI in mechanical engineering, with a particular focus on mechanical design: How does AI manifest itself, and how can it be utilised as part of mechanical engineering?

AI as Part of the Design Process

Traditionally, mechanical engineering and design processes have required extensive expertise, manual work, and complex calculations — that is, human labor.

Top-tier design at Metecno still requires this expertise, particularly in using software like SolidWorks, and AI won’t replace the role of the designer at Metecno. However, AI has brought tools that can automate some stages of special purpose machine design, making the overall process more efficient.

One of the most significant advantages of AI is its ability to analyse large amounts of data and draw conclusions quickly. This, in turn, enables designers to make faster and more accurate decisions.

For instance, optimisation algorithms can evaluate different design options and offer the best possible solution for the assembly of a special purpose machine in terms of its performance and durability. In general, language models can already provide a credible sparring partner for comparing different design ideas.

AI in Mechanical Design – Case SolidWorks

AI is becoming increasingly visible in new software features.

SolidWorks’ new AI features, such as Design Assistant, utilise AI and machine learning to streamline design. Design Assistant learns from the user’s design style and automatically provides suggestions, reducing repetitive and time-consuming tasks.

New AI features in SolidWorks include Mate Helper, which automatically detects and suggests the placement of parts in assemblies, reducing the need for manual adjustments. For example, if you place a bearing near a shaft, Mate Helper recognises the relationship between the parts and suggests a concentric mate connection between the centers of the shaft and bearing. This saves time as the designer doesn’t have to manually select the surfaces or define the geometric relationships of each part.

Another new feature is Selection Helper, which predicts which parts of the model the user should select next, speeding up the selection process. For example, when you select a screw, it might suggest that you select matching nuts or washers, as you did before. By simply reducing unnecessary clicks, AI makes the design process more intuitive and smoother.

Predictive Analytics and Simulation

One significant application of AI in mechanical engineering is predictive analytics.

In mechanical design, AI can be used to evaluate the performance of machines and their components before they are even built. AI-based simulation tools can analyse how different components and materials behave under various loads and conditions, helping designers identify potential issues before the prototype stage.

AI also enables fault prediction based on data collected from machine operations. For example, sensors continuously gather data about the state of machines. AI can analyse this data and predict when a component is likely to fail or require maintenance. This predictive maintenance can reduce costly downtimes and extend the lifespan of machines.

Generative Design

AI allows for a new approach to mechanical design through generative design. This technique combines AI and computational methods to produce alternative designs based on set conditions and objectives.

In generative design, the designer defines specific parameters, such as weight, strength, or material. Based on these parameters, AI can generate various design options that meet these requirements. AI might also propose entirely new, creative solutions.

Generative design not only speeds up the design process but also produces lighter and more optimised structures with lower production costs. In this way even complex part 3D printing, which is already a common practice in special machine design at Metecno, becomes easier and more cost-effective.

AI in Mechanical Engineering – Benefits and Challenges

The main goal of utilising AI in mechanical engineering is to achieve cost efficiency, but it may also lead to better quality.

AI can reduce the amount of manual work, improve the accuracy and speed of the design process, and enable the development of new innovations. Examples include predictive maintenance methods and better simulation tools that reduce the risk of machine failure and shorten downtime.

However, using AI also comes with its own challenges; first and foremost, its implementation often requires the collection and analysis of large datasets. This can be challenging for smaller companies that lack the resources or infrastructure to handle big data. Additionally, developing and integrating AI into existing processes requires expertise and training, which can take time away from billable work.

Implementing AI requires addressing a central question — how much design work can a company transfer from human intelligence to AI without compromising the reliability and safety aspects of the machines being produced?

Future Outlook

The message across various industries is strong; the role of AI is likely to grow even more in the future.

New AI innovations are continuously being developed, and interest in AI as part of design processes is only set to increase. As 5G technology and the Internet of Things (IoT) evolve, AI will gain more real-time data from processes, improving the accuracy and productivity of designs.

Although AI adoption at Metecno and in mechanical engineering is still in its early stages, the predicted potential of AI is significant. Companies that invest in AI and its applications are likely to see substantial improvements in their business efficiency, innovation, and profitability within the 2020s.

AI is no longer just a theoretical concept or a distant future innovation; it is already a tool that has the potential to enhance mechanical engineering and design. It is important for professionals in mechanical engineering to start considering AI’s possibilities as an opportunity to deepen their understanding of the field.

AI was also utilised in the production of this blog.

For more details

René Silander
Marketing Manager
+358 20 741 6212
rene.silander@metecno.fi