Why Combine Artificial Intelligence with Additive Manufacturing?24 November 2023
Report by Danny Weller
In an ever-progressing world, many companies are leveraging digitization and automation for additive manufacturing advancement. More and more manufacturers are turning to cloud-based solutions and integrated algorithms in 3D printing maximize its potential in Industry 4.0. As part of this digital realm, 3D printing aligns with AI, like machine learning, in optimizing the value chain. AI’s rapid data processing capacity makes it a crucial decision-making tool. Machine learning, as a form of Artificial Intelligence, is forging the future of additive manufacturing.
Both of these technologies have been increasingly adopted in the manufacturing industry over the past several years, and their synergy is yielding rewards. AI’s role in additive manufacturing extends to elevating product quality, fostering innovation, driving productivity, and ultimately, amplifying companies’ profitability.
What is Machine Learning?
Machine Learning, a subset of AI, involves systems or software using algorithms to analyze data and identify patterns or solutions. Despite misconceptions, machine learning isn’t a recent development. Its roots date back to the 1940s when researchers began simulating brain neurons with electrical circuits.
In 1957, the Mark I Perceptron marked a significant breakthrough—it autonomously classified input data. Learning from past errors, it progressively refined its classifications. This pivotal moment sparked researchers’ fascination with the technology’s potential. Today, artificial intelligence permeates various aspects of daily life, from speech recognition and smart chatbots to tailored treatment plans, showcasing the widespread applications of Machine Learning.
In 1957, the Mark I Perceptron was the first major success in this field: the machine was able to classify input data independently. In doing so, the device learned from mistakes made in previous attempts, which improved the classification over time. Since then, the foundation was laid and researchers became fascinated by the possibilities and potential of the technology. In the meantime, we encounter artificial intelligence every day in all areas of life. From speech recognition to intelligent chatbots to personalized treatment plans, Machine Learning is being used in a variety of applications.
How is AI used in Additive Manufacturing?
Artificial intelligence has had a profound impact on additive manufacturing; from revolutionizing design, quality control, and production efficiency to enhancing facility operations and maintenance. These are some of its main uses:
AI plays a multifaceted role in the design phase of additive manufacturing, offering diverse contributions. From the initial stages, AI assesses the viability of additive manufacturing for specific designs, ensuring optimal efficiency.
In later stages, AI drives generative design, sparking innovation and streamlining the design process by swiftly generating designs based on predefined parameters. With regards to 3D printing design, AI proves instrumental in topology optimization, utilizing machine learning to craft designs that prioritize maximum production efficiency.
Quality Assurance & Defect Detection
Artificial intelligence revolutionizes quality control in additive manufacturing by integrating with vision systems for real-time production monitoring. It excels in identifying even the minutest defects invisible to the naked eye. AI ensures precise and proactive quality monitoring, minimizing the chance of potentially defective products. Moreover, AI has a similar impact on post-production quality assurance, swiftly detecting and addressing issues as products are finalized.
Proactive Defect Management
AI goes beyond detection by empowering a proactive approach to addressing potential defects during additive manufacturing. By facilitating real-time material usage control, AI significantly minimizes material wastage.
Leveraging machine learning capabilities, 3D printing AI detects defects and assists operators or technicians in prompt issue resolution. Additionally, AI enables autonomous decision-making within the manufacturing process itself. This proactive, real-time control mechanism reduces the discard rate of defective pieces, optimizing production efficiency.
Predictive maintenance, the process of using data analysis and technology as an early warning system for production issues, is already changing the game in the manufacturing industry. This approach revolutionizes maintenance practices, productivity, inventory management, and troubleshooting methodologies.
The deployment of additive manufacturing and AI bolsters these advancements, offering on-demand production of 3D-printed industrial parts. This enables heightened maintenance and inventory efficiency through just-in-time delivery strategies. AI complements these efforts by triggering production upon issue detection and by analyzing equipment lifecycles and predicting maintenance requirements based on historical data.
Benefits of AI in Additive Manufacturing
Given the broad array of mentioned applications, with more besides, it is clear that AI can offer a wide range of benefits for manufacturers across the industry. Chief among these benefits are:
Improved Quality Assurance
Proactivity drives efficiency and cost savings in manufacturing, and AI could prove to be a pivotal tool in achieving these goals. Through prefabrication quality assurance, AI verifies design suitability for additive manufacturing, curtailing wasted time, effort, and materials in design testing and iterations. Essentially, AI mimics the QA process of a ‘finished’ part before production commences, delivering significant time and cost advantages.
Streamlining and Simplifying Processes
Leveraging AI during the design and ideation phase proves invaluable in streamlining designs and simplifying complex processes. This approach yields several advantages: simplifying production, cutting manufacturing costs, optimizing material usage, easing the QA burden, and accelerating the overall process and time to market.
Efficient, High-Quality Production
AI integration in additive manufacturing delivers comprehensive benefits, offering tangible cost savings, actionable operational enhancements, and a positive impact on the bottom line. When deployed in additive manufacturing and other organizational processes, AI excels in problem detection, optimizing design, production, and post-production workflows, aiding decision-making, and accelerating facility-wide processes. The synergy between additive manufacturing and artificial intelligence enhances the multiple advantages offered by this innovative technology.
At Formnext 2023, 1000 Kelvin, a pioneering startup unveiled its groundbreaking AI software, AMAIZE. AMAIZE harnesses physics-informed AI to craft precise Additive Manufacturing recipes. By analyzing uploaded build files, it autonomously corrects potential thermo-mechanical issues, eliminating the need for costly simulations and multiple physical iterations. This seamless integration with machine manufacturers paves the way for a more accessible, sustainable, and technologically advanced approach to 3D printing, appealing to industries spanning energy, aerospace, and manufacturing.
In a compelling case study, a California rocket launch provider overcame significant AM challenges using AMAIZE’s AI solutions. This led to a superior-quality part with an 80% reduction in support structures, resulting in over 30% overall cost savings.
AI in Space
LEAP 71 and The Exploration Company have teamed up to revolutionize space exploration by integrating artificial intelligence and additive manufacturing. Their joint aim is to refine calculation and manufacturing models for spacecraft design, focusing on LEAP 71’s computational engineering model. This model enables the design and 3D printing of intricate, high-performance rocket engines. By combining AI and additive manufacturing, their goal is to drastically cut production costs and drive innovation in aerospace at an accelerated pace.
This partnership builds upon additive manufacturing’s established success in aerospace, particularly in crafting finished components for rockets and satellites. LEAP 71 and The Exploration Company aim to build lighter, faster-to-produce components, enhancing the business model and performance of spacecraft. LEAP 71’s computational model facilitates the design of diverse rocket engines, to be 3D printed for testing and refinement. Their vision is to continuously improve these engines exponentially through real-world feedback, marking a pivotal step toward advancing space exploration.
The debate is still raging as to whether Artificial Intelligence will prove helpful or harmful to humanity in the long run. However, in the world of manufacturing, AI and machine learning are offering consistent benefits.
We work with hundreds of businesses to enhance and accelerate their quoting process. Take control of your quoting procedure and streamline your pre-production workflow: our real-time inventory management empowers you to efficiently oversee your resources, leading to a smoother and more productive operation.
Whether you’re an SME machine shop or a multinational OEM, AMFG offers a comprehensive end-to-end MRP system to enhance your inquiries, quoting, and pre-production processes.
Find out how AMFG can supercharge your Additive Manufacturing and CNC Machining processes today.
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