Design processes within the industry are evolving continually. If you look at how engineering and manufacturing have changed within the last 60 years, you will notice a huge difference. In decades past, engineering and design were largely a manual process.
Fast forward to today, however, and we have a vast array of automated technology at our disposal. Systems such as AutoCAD have revolutionized how we design products and improve production efficiency.
But what is the next step? Where can we possibly go from here? If you work in the engineering or manufacturing industries, you may have already heard of a new potential breakthrough – generative design. As you will see in the paragraphs below, generative design could potentially revolutionize how we create and manufacture products. In this article, we look at what generative design is, its limitations, and how it is already being used in industry today:
The Problem – Limitations of Traditional Human/Machine Design
Before we look at generative design, it is imperative to understand the current limitations that industries are facing. Consider this fact below:
One of the main limiting factors to design and innovation is the human mind.
What does this mean? Product design and innovation are largely constrained by what we can imagine. An engineer will formulate a new product based on their own knowledge and research – the product, therefore, has a limited scope. If a designer wanted to create hundreds of different product variants and prototypes, it would take hours of work – the process would be slow and time-consuming.
So we have two main problems – human limitations and time constraints. As you will see below, generative design tools can combat these two limiting factors.
The Solution – Generative Design
In traditional design and engineering, you have the following relationship:
One designer + one computer = a limited number of designs
A designer will create a handful of different designs using a computer as a passive device. The computer is simply used as nothing more than a design tool. For example, an engineer could design an ergonomic plastic chair using CAD and other software. Maybe they could create five different designs from which to choose. This process gives a limited scope and viability to the product.
In generative design, the relationship is as follows:
One designer + artificial intelligence + cloud computing = hundreds and thousands of designs
As you can see, straight away, the end results are superb – generative design allows a designer to create thousands of designs in a fraction of the time they would take using traditional methods. Generative design combines human input together with artificial intelligence and immense computing power to produce hundreds of design variants. The typical process for generative design can be seen below.
Generative Design Process
1. Initial human input – First, the designer will input a myriad of data. This data is the basis from which the artificial intelligence will work. Data to include could be, for example, the design goals, constraints, and limitations. Moreover, the engineer would input specific product information such as material type, weight, cost, and strength. These basic parameters will be used to design the product.
2. AI reasoning – Once the engineer has inputted all the basic parameters, the computer and AI can then start work. You have to remember that we are talking about complex AI algorithms and hugely powerful cloud computing. The computer systems and AI will combine the data provided with its own reasoning and logic to create thousands of potential designs.
During this process, it will run performance analysis trials to determine the viability of each design. It will only create designs that work within the specified parameters.
3. Human modifications – Now we get to the review and re-design stage. Once the computer has formulated its initial designs, the designer will review the results. If necessary, they will make modifications to the goals and constraints. This process will then be repeated – this process of modification and re-design will continue until a satisfactory product is created. The designer will use their own intuition, along with AI reasoning, to decide upon the best product design.
4. Prototype creation – Once the engineer is happy with the design, they will create a prototype. After analysis, the prototype will either be approved, put into full-scale production, or the designer will decide to return to stage 3 for more variants.
This process might look long and complicated, but it is streamlined and efficient, especially if you work with a prototype design service. You are removing a large portion of the human input and replacing it with powerful computer processing and AI technology. As a result, the whole design process time is reduced.
The Main Components of Generative Design
Now that you understand a little more about generative design, we can break down the main components involved in the process. There are three main components – human input, AI intelligence, and cloud computing power.
Human Input
Generative design still includes human input. We are not yet at the stage where computers and AI can design products from scratch. AI evolves and learns – it must have a basis from which to learn – making the human input important.
The designer or engineering design service still plays a vital role in the process. They will set the initial parameters from which the computer will formulate designs. These parameters will be pulled from research, market data, and the company’s own resources. For example, if a designer was creating a new chair, they might look at previous models and identify what materials and weights that customers preferred. Moreover, they may look at ergonomic statistics and input data relating to comfort and safety. Without this initial input, the whole process cannot work.
The engineer is vital for the reviewing phase and final product choice. When reviewing a design, a computer can only review it based on statistics and parameters – there must be a human decision-making element involved. For example, an engineer could potentially notice some factor that the computer wouldn’t evaluate. Human intuition is important to help choose a viable end product.
Artificial Intelligence
AI and computing are hugely important components within the generative design process. The artificial intelligence used removes the human limitations. This AI computing system thinks for itself and uses complex algorithms to formulate viable products.
Let’s say an engineer was creating a bike frame. The AI system could look at the materials and parameters specified by the engineer to formulate what design would provide the lightest frame with the greatest strength. For a human to do this calculation, they would have to try out various styles and test each one. Artificial intelligence can achieve this outcome to find a viable frame within a fraction of the time.
Examples of generative design software include:
- Autodesk Dreamcatcher
- nTopology Element
- SolidWorks
- Rhinoceros 3D
Cloud Computing Power
This type of artificial intelligence requires immense computing power. In the past, this type of technology would require a supercomputer that would, for example, take up a whole office. Today, however, we have the wonderful technology that is cloud computing.
Traditional server-based computing relies on the processing power from a set of physical servers within a server bank. The processing power is finite – it has a limit.
Cloud computing draws processing power from various servers located around the world. This approach means that processing power can be increased or decreased to meet current demands. AI programs used within generative design can draw from practically unlimited cloud computing power. This fact means that the design process can be achieved efficiently in a short time. Without distributed cloud computing, generative design would be slow and inefficient.
Advantages of Generative Design
Now you should have a clearer grasp of generative design and its process. But what advantages does this type of design process provide? The following list is some of the main advantages of generative design:
Reduced Time to Design Products
Let’s say that it would take a designer 20 working hours to create a product. To create five product variations, that equates to 100 working hours. Using generative design, the same product could be designed within, for example, one hour. Therefore, in 100 working hours, the AI system could produce 100 variants as opposed to the 20 variants produced using traditional methods. Generative design can greatly reduce the overall design process time.
Improved Creativity
To coincide with the above point, generative design can also improve creativity. Because generative design can create thousands of different product variants, this approach can open a whole new range of possibilities. SolidWorks design services are typically experts at generative design and can examine hundreds of different variants that they wouldn’t have the time to test and trial. As a result, creativity will bloom. When working with a small sample of product variants, creativity is limited – generative design removes this restriction.
Reduced Design Costs
As we touched upon above, the traditional design process involves extensive testing and evaluation. After each design has been created, it needed to be tested – this testing process is both costly and time-consuming. Generative design includes this testing and simulation process during the AI computation. It will effectively produce only designs that are feasible and effective. This point means that there will be no expensive design changes further along in the manufacturing process.
Enables Creation of the Impossible
Generative design in conjunction with 3D printing can produce the impossible. In traditional CAD design, the machines and programs are limited to conventional geometric shapes. AI inspired generative design can bypass these limitations to create complex geometric shapes that would not be possible otherwise, further helping to increase creativity.
Limitations of Generative Design
As with any new technology, generative design has limitations. This technology has certainly not yet been perfected; it is still in its infancy. In the near future, we should see generative design improve vastly. The processes and computing technology involved should only improve. The following are some of the current limitations of generative design:
Human Error
Because the initial stage of generative design involves human input, the process is still open to human error. What happens if the designer inputs incorrect parameters during the initial input stage?
What happens if they choose the wrong product or make a crucial design error that could compromise the integrity of the overall structure? Whenever there is human involvement, there is scope for errors – this fact must be applied to any form of manufacturing service.
AI Complexity
Artificial intelligence plays an important role in generative design technology. It stands to reason that this process, as a whole, is limited by the complexity and reliability of the AI algorithms. If generative design software uses sub-par AI, the end product will be sub-par too.
Limited Usability
At this moment, generative design only has a limited number of different applications. These applications mainly involve creating complex geometric shapes. As time progresses, we should see the technology being used for a wider array of different products.
How Is Generative Design Currently Being Used?
Finally, we can look at current applications for generative design in manufacturing and retail today. This technology is already being used to push the boundaries of innovation and design. Many high-profile companies are using generative design to improve their products. The following examples are some of the current ways that generative design is being used:
Under Armour – This company creates sportswear and is one of the leading developers of innovative sports technology. In recent months, Under Armour have been testing generative design effectively. They have used Autodesk to generate a comfortable and stable latticework for their ArchiTech trainer.
Airbus – Airbus is one of the premier manufacturers of commercial airplanes. They have used the latest technology to create durable, lightweight, and safe parts for their planes. Recently, Airbus has used generative design to create a new style of cabin partition. Because of its innovative design, the partition is much stronger. Moreover, the planes use less fuel due to lighter overall weight.
MX3D – Would you believe that this company is planning to use generative design to create a bridge? MX3D specializes in robotics but is turning their attention to architecture. They are using generative design to create a canal bridge in Amsterdam.
Black & Decker – This manufacturer of tools, DIY equipment, and machinery has started to include generative design in its process. They have experimented with different designs for tool parts effectively.
We hope you have found this guide enlightening. You should now have a clear understanding of what generative design is. Moreover, you should also see how this type of revolutionary design could transform your business to improve your efficiency. We wholeheartedly advise looking into generative design today, as this type of process is the future. If you act now, you can be part of the design and manufacturing revolution!
