The Future of CAD: How AI is Transforming the Design Industry

Artificial Intelligence is the science of making machines do things that would require intelligence if done by humans—says Marvin Minsky, Pioneer of intelligence-based Mechanical Robotics and Telepresence.

The Global Artificial Intelligence in Construction Market was valued at USD 0.4 Bn in 2020 and is expected to reach USD 3.5 Bn by 2027, with a growing CAGR of 36.5% during the forecast period (2021-2027). According to the Association of Equipment Manufacturers (AEM), AI has the potential to boost productivity, safety, and other aspects of business success in the construction industry.

This blog describes how Artificial intelligence (AI) will transform the design/modeling industry and the paths through which AI will be applied to Computer-aided design (CAD).

How soon will AI be the Engineering Consultant?

Computer-aided design (CAD) is the software technology of designing, drafting, modeling, and drawing concepts that used to be done manually on drawing boards. The inclusion of embedded Artificial Intelligence into CAD software has somewhat and will surely in the near future take this technology to a new paradigm of human-machine symbiosis. CAD has come a long way over the recent decades, streamlining and accelerating a wide array of repetitive and tedious steps associated with the planning, testing, and implementing of designs.

CAD is an intelligent design and drafting tool that combines computer and software capabilities to deliver virtual design models and drafting products across AEC, manufacturing, automotive, industrial, and visualization platforms. During the last 20 years, various tools have emerged with applications across the above range of platforms. In the best interests of growth and development, engineers and related professionals must use and enhance their capabilities in these intelligent tools. The creativity aspect of these intelligent tools is enormous and growing by the day. The complex challenges of emerging markets and the requirements of a fast-paced developmental environment make it essential to be abreast with these tools and proficient in their application. The proficiency will ensure that the professional will be able to face and deliver Complex Designs/ Concepts in record times which was unimaginable in the near past.

Deep Learning AI is an embedded neural algorithm in the CAD tool. It has the capabilities of advanced and automated decision-making (ADM). ADM thus develops into a process where the Deep Learning algorithm collects historical data and processes it for modeling and iterations with a support logic for automated decisions based on criteria from the historical data. The feedback loop reviews, evaluates, and improves the design decision. This leads to and records the improvements for immediate future reference.

The apprehensions of CAD resource personnel that the need for Human Resources is dwindling fast due to this automation will not be necessarily valid even after the AI automation is entirely on. We will still need CAD persons until ADM (AI) replaces most of the design process. We will need them to set up, run, modify settings, modify applications, check and cross-check, present, discuss and finalize other associated tasks involved in the random options developed by Design through AI. The specialized CAD personnel, Engineers, and Managers will be the Supervisors of this AI Setup. Along with moving the software setup to the next level, the human resources will be moving to the next higher level.

Paths through which AI will be applied to CAD

The application of AI to CAD includes two distinct paths of applying algorithms to the Design/Drafting process:

1. Machine Learning Algorithms are exposed to Substantial Data sets, examples, past designs, past experiences, etc., and learn to read patterns and recurrences. Thus, these algorithms will refine themselves to repeat the logic (commands) based on these learned patterns and hence fast-track the execution of tasks, progressively reducing the requirement of manual inputs. The following is an example explanation of the basic CAD tasks, which can be executed using simple applications of AI Algorithms applied to Drafting/Design using CAD software. The ADM (AI) will transform non-digital data into digital data for processing into an intelligent design. For example, designs/concepts on paper can be primarily scanned, and then the ADM (AI) algorithm will generate the 3D CAD models based on historical data/ deep learning. Another example is that in the absence of any design data in any format, 3D scanners will be used to scan manufactured products or architectural buildings to create point data cloud files. On the availability of design data in a digital format, the ADM (A.I.) algorithms will process this to understand the data and develop solutions and create 3D CAD models containing all information inside it. The information in 3D CAD models is more valuable than other format design data, as it is rich in features and interconnectivity between the components.
   Based on the above concept/challenges of Applying AI in CAD, the stepwise process stepwise as follows:
   • Problem Definition
   • Existing Experimentation
   • Application to Geometric Data
   • Data Set Preparation
   • Data Set Collection
   • Feature Generation
   • Data Analysis and Visualization
2.  Neural Network Algorithms are the advanced type of deep learning algorithms that simulate the human brain’s neural networks. These advanced deep-learning algorithms have been used in image recognition, processing, and self-driving automobiles. These techniques are being introduced into CAD/CAM software for the next level of Drafting, Engineering, Design, Review, Manufacturing, and Life Cycle Management. The elements of Neural Network Algorithms are:

• Generative Design: What if you could come up with thousands of options for a single Design without drawing? You wouldn’t have to draft through all these thousands of options. Generative design is one of the easiest ways to start collaborating with AI. It’s available in a range of Drafting tools from various Software suppliers, enabling collaboration for projects across industries. Using Generative Design scripts for designs can provide limitless options. With generative design, it is possible to explore different scenarios and find the best solutions to the problem, all while balancing multiple objectives. E.g. when applied to road networks, this means automating the creation of complex models like corridors with Generative Design.
• AI assistants: Generative design is just one kind of AI—there are many others. The incredible increase in computing power has given rise to AI assistants, for example—the kind of AI that helps you navigate traffic or compose an email. They also have a key role to play in product design. AI-enabled add-ons to CAD software enable outcome-driven design in the early stages of AEC projects. Using physical data, site constraints, regulations, and local preferences, planning, and design teams can create an optimal proposal from a 3D model that serves as a single source of truth for all parties. To explore the future of human-machine collaboration, Japanese manufacturer OMRON built a robot that can play table tennis. The robot, named FORPHEUS, was created with generative design and other automation technologies. While ping pong is fun, the ultimate goal is to advance research into AI and how this developing area of collaboration could impact homes and factories.
• BIM 360 for collaborating with people: When working on a project involving multiple disciplines with different companies, BIM modeling is here to help. Using BIM collaborative platforms for Design Collaboration, Review, and Issues Management, a CAD resource will discover the various workflows for design collaboration, review, and issues management that enable cross-party connectedness.
  And that’s just the beginning of exploring generative design and artificial intelligence.

The Sharp Cutting Edge of CAD Technology will be fully Automated Decision Making (ADM) which will have a fully developed capacity for interpreting, analyzing, and implementing the extended CAD capabilities beyond imagination. The complex, laborious tasks of drafting and analyzing in CAD about 30 years ago have now been reduced by 50%. This will be further reduced by fully embedded AI through Neural Network Algorithms. Soon, full ADM capabilities will emerge in CAD technologies, and further innovations will be possible in Engineering Design.

Basic CAD Drafting work by the run of mill Drafting resources takes a lot more time than if Engineering and Proficient resources are working using Intelligent tools of Design and Drafting, e.g., Revit on a Collaborative Platform, BIM 360/ Pro, etc., in the AEC, Transportation and Utility sectors.

Also Read: CAD and Cloud: 11 Reasons Why Cloud-based CAD is the Way to Go

Sterling Engineering Support Services, a unit of iQuasar LLC , is a Northern Virginia company delivering Computer-Aided Design (CAD), Engineering Support, and Recruitment Services to businesses of all sizes, from small growing companies to large established organizations in Architectural, Civil, and Structural Engineering verticals. Our professionals assist you with a full array of quality CAD services, including 2D/3D, Modelling, Drawing, Rendering, Conversion, and Animation, to ensure that your projects have their engineering deliverables on time and within budget.

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