Global Artificial Intelligence (AI) in 3D Printing Market Research Report: Forecast (2023-2028)

Market Definition

3D Printing (3DP) is an additive technology that involves the creation of 3D objects by forming successive layers of material until the physical object is achieved. It simply stacks & fuses the material layer to build 3D solid objects from a digital file. Combining Artificial Intelligence (AI) with 3DP shall help enhance the efficiency & quality of the printing process and objects created while also enabling faster & low-cost production.

Market Insights & Analysis: Global Artificial Intelligence (AI) in 3D Printing Market (2023-28)

According to MarkNtel Advisors, the Global Artificial Intelligence (AI) in 3D Printing Market is anticipated to grow at a considerable CAGR during the forecast period, i.e., 2023-28. Integration of AI in 3D Printing can help bring out the best of the objects created from the process with reduced need for labor & increased automation. Since 3DP is technical & complicated, the demand for integrating AI into 3D printing processes is surging astronomically worldwide to maximize the quality & efficiency of 3D printing technology.

• AiBuild has developed an AI-based 3D printing technology, “AiMaker,” i.e., the high-precision robotic end-effector used for 3D printing of large objects at high speed & accuracy. It aims to offer complete automated 3D printing that can be controlled & accessed easily from all locations worldwide. AiMaker can help manufacturers minimize production time & expenses to a large extent, decrease the costs of components, and, in turn, significantly benefit end-users.

According to MarkNtel Advisors, the Global Artificial Intelligence (AI) in 3D Printing Market is anticipated to grow at a considerable CAGR during the forecast period, i.e., 2023-28. The growth of the market is likely to be driven by the growing need for optimized 3D printing to attain a consistent & reproducible quality of the prints, the current approach to which involves multiple times manufacturing & extensive testing of the final print, i.e., both expensive and time-consuming.

In search of better approaches, 3D printing experts have found that AI-based algos can help automate the most crucial tasks in the printing process. As a result, the world is witnessing a burgeoning demand for integrating AI into 3D printing to bring out the best of the objects with less human intervention & increased automation.

Some AI-based software packages available in the market allow for the evaluation & optimization of design files for 3D printing through machine learning algorithms. When manufacturers enter the desired design parameters, AI analyzes the design requirements and helps them find the most efficient production pathway. Hence, these perks are aiding in the growing popularity of AI-based additive manufacturing to bring out more automated 3D printing processes, thereby generating lucrative prospects for the Global Artificial Intelligence (AI) in 3D Printing Market.

Market Segmentation

By End-User:

• Healthcare
• Automotive
• Consumer Electronics
• Others (Aerospace & Defense, Marine, etc.)

Here, 3D printing is gaining immense popularity in the Healthcare sector. Integrating AI into 3D printing helps improve the speed & customization of the printing process, which played a crucial role amidst the pandemic to ease the shortage of essential medical equipment like ventilators & PPE kits. Hence, the preference for AI in 3D printing over traditional manufacturing methods is expected to increase significantly in the years to come.

Moreover, 3DP also offers the freedom to manufacture customized healthcare equipment & tools, which have several positive effects in terms of the duration of the surgery, patient recovery time, etc. The technology is also beneficial to the design process of human organs or tissues since the cells used in this process are taken from the patient’s body. Hence, the probability of the body rejecting the organ gets significantly reduced.

Further, it is used extensively for manufacturing surgical equipment like medical clamps, forceps, needle drivers, retractors, etc. Here, the most prominent benefit of integrating AI in 3D printing is that specific modifications can be made to the designs, and the design speed can also be greatly enhanced. 

By Technology:

• Machine Learning
• Natural Language Processing (NLP)
• Others (Context Aware Computing, Computer Vision, etc.)

The integration of machine learning algorithms in 3D printing directly impacts the quality of 3D printed objects. It is beneficial in process optimization and in-situ monitoring for quality control. In addition to this, it helps in enhancing the efficiency of the design & manufacturing process. 

Further, the machine learning technique in 3D printing offers feature recommendations to existing models, thereby assisting manufacturers in speeding up the decision-making process. Moreover, it helps make composite designs, tune material properties, and produce new designs that outclass the existing ones.

Regional Landscape:

• North America
• South America
• Europe
• Middle East & Africa
• Asia-Pacific

Amongst all regions. North America acquires the largest share of the Artificial Intelligence (AI) in the 3D Printing Market, mainly due to the strong technological ecosystem present across the region. Additionally, increasing expenditure on manufacturing technologies and surging R&D activities in space applications is also fueling the need for integrating AI in the 3D printing technology. Massive investments in 3D printing start-ups & rapid technological innovations are other crucial factors contributing to the overall market growth in North America.

Market Dynamics:

Key Drivers

• Burgeoning demand for increased 3D printing performance and less errors.
• Growing requirements for automated 3D printing workflow and highly optimized entire process.

Growth Challenges

• High computational costs associated with the integration of AI into 3D printing
• Lack of unified frameworks to facilitate sharing of ML models
• No reliable data acquisition technique to ensure that the data gathered can offer informative insights into the printing process

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