Home > Article > Technology peripherals > How does generative AI help automate architectural design?
The construction industry has begun to dabble in the use of artificial intelligence (AI) to complete daily tasks such as scheduling and document analysis. But generative AI is a game changer, says Augmenta CEO Francesco Iorio, and has the potential to change the way buildings are designed — lowering costs, increasing productivity and reducing waste.
Tools like ChatGPT and DALL-E use large-scale machine learning (ML) models and access large amounts of labeled and meaningful data to provide insightful responses to queries in text and images. However, some industries have limited access to the datasets used to train ML models, making the benefits of using generative AI to solve real-world problems difficult to reap.
The construction industry is a good example. No single repository contains markup data for building engineering drawings. This is because engineering companies keep their data secret and don't tend to share their intellectual property. One consequence is that outdated design methods hinder the growth of the construction industry. Existing legacy tools for designing buildings and their systems are little better than an electronic pencil on paper, resulting in unbuildable designs, a lack of coordination between industries, and a waste of time and materials when they inevitably need to be redone.
That said, even state-of-the-art generative AI models like ChatGPT, which utilize very large, diverse, and detailed data sets to train complex models, can produce erroneous results while also affecting the output. Show complete confidence. In the case of ChatGPT, the consequences of making a mistake are relatively low. But the stakes are so high in engineering that the safe and effective adoption of generative AI will require more than large black-box mathematical models.
Thankfully, there is a novel hybrid approach to rule-based AI systems that can generate new valid data in the form of generative design that can be used to train ML Model. The most valuable application of this approach is in automated building design. Not only does it shorten the end-to-end design process from months to days, it also provides developers, architects, and engineers with unprecedented insights to help them make more informed decisions related to cost, schedule, and efficiency.
Let’s take a closer look at what the construction industry can achieve by automating the building design process.
Today, architects and consulting engineers who create advanced building designs do not have the time or sufficient information to develop Buildable systems. For example, the design process for mechanical, electrical, piping, and structural systems (MEP/S) is extremely complex, time-consuming, and error-prone. It is also one of the main causes of errors, delays, risks and uncertainty.
By automating design, the speed of the design and construction process can be greatly accelerated, shaving months off the construction schedule, thereby creating functional buildings for residential and commercial uses faster. By reducing risk and uncertainty and eliminating rework (which adds an average of 6% to costs), developers can better plan and budget projects, while contractors can bid for work more accurately.
The construction industry is a major consumer of energy and materials. According to Energy Research Frontier’s Digital Transformation and Waste Management in the Architecture, Engineering, Construction and Operations Industry report, up to 30% of new construction materials are wasted due to design errors and rework. Using an automated design system can virtually eliminate these errors.
Generative AI can also create multiple design alternatives in parallel, helping to find ways to develop better-performing buildings using less material. It also helps improve energy efficiency – a vital capability considering that buildings consume approximately 40% of the world’s energy and resources, according to the United Nations Environment Programme. Now developers can understand their options: optimize for cost and schedule alone, or design for more sustainable material use and operations simultaneously. Automatically generating highly detailed designs ensures they only order what they need, reducing material waste.
By leveraging generative AI to optimize the design and performance of buildings, the industry can not only reduce its carbon footprint, but also do so more efficiently and cost-effectively. Target. A few years ago, it was estimated that architects, engineers, and construction (AEC) professionals spent approximately 20% of their time resolving errors and conflicts caused by design and coordination errors. Globally, this equates to $280 billion in rework. No doubt these numbers are rising as talent is scarce and demand for new construction intensifies.
Generative artificial intelligence brings a level of automation to the design and construction process, enabling AEC professionals to create optimal designs in hours instead of weeks and dramatically reducing construction errors. Because designs are designed with a high degree of certainty, design professionals can be more efficient and spend less time on rework and errors.
The construction industry is facing a serious shortage of well-trained and experienced talents, which cannot meet the needs of current projects under construction. In fact, some of the industry's largest unions predict there will be a shortage of skilled tradespeople in the United States.
Automated design means making it easy for individuals in construction firms, engineering firms, and contractors to gain experienced management experience, allowing even junior designers and engineers to create buildable and code-compliant designs. It also frees these people from traditional and boring methods of designing work. Instead, they can take the time to truly understand the client's needs and explore design options and trade-offs to achieve the best design.
According to a 2023 Engineering and Construction Industry Outlook report by Deloitte, there is no shortage of investment in new construction projects. In the United States, new housing units are expected to reach 1.55 million units per year, compared with 583,000 units in 2009. Given the shortage of skilled workers coupled with high turnover rates, the industry must learn how to do more with less.
Generative AI promises to scale across the entire construction ecosystem. Contractors can expand their design capabilities without being limited by talent or retention. Parts suppliers can automate and expand their prefabrication services to include selling complete, purpose-designed assemblies rather than just parts. The construction industry can finally catch up by embracing this emerging technology.
There is no doubt that the construction industry is ripe for disruption. Generative AI has the potential to fundamentally change the course of architectural history—fundamentally changing the way we design buildings and the design of those buildings themselves. Although AI has already achieved some results in this field, it is clear that the best is yet to come.
The above is the detailed content of How does generative AI help automate architectural design?. For more information, please follow other related articles on the PHP Chinese website!