Anticipation and expectation have always surrounded additive manufacturing (AM) since its inception. This excitement stems from AM’s potential to revolutionize manufacturing, simplify supply chains, and promote a circular economy.
However, to achieve this potential, AM must overcome a number of longstanding operational challenges. These obstacles often include factors such as design printability, the need for manual intervention, repeatability, and producing high-quality output with minimal waste. These factors currently prevent AM from transitioning from R&D experimentation to widespread adoption.
Eliminating these barriers not only allows AM to impact customer P&L and capital usage more effectively, but also has transformative potential. AM’s influence extends to corporate, regional and global well-being. The recent geopolitical landscape, global pandemic, and climate change have exposed the vulnerabilities of our supply chains and highlighted the need for rethink about how and where products are manufactured, stored, and shipped. It has also underscored the necessity to optimize the time and resources used to maintain the current state of affairs.
Thus, the question arises…
What will drive the inflection points in accelerating global AM adoption to full its potential? and;
How can AM users keep pace with complex application evolution and future proof their investment?
Here’s AiBuild’s view on the core essentials:
AI-Driven Simplicity:
Deciding to adopt a new system and its potential benefits are directly impacted by how user-friendly it is, the value it provides through process optimization, and the dependability of its results. From our inception in 2015, we’ve emphasized the importance of AI in our approach and looked into how its integration can collectively improve the Additive Manufacturing (AM) industry.
Undeniably, AI-powered software continues to have a transformative effect on the AM process chain at a fast pace. Embedding AI in product development strategy, user interaction, and system outcome spurs quicker innovation, expands capabilities, and noticeably boosts overall system performance.
We have firsthand experience with this since our platform, AiSync, employs machine learning to oversee quality control and defect detection, spotting real-time print deviations compared to the build simulation. Additionally, AiBuild incorporated natural language processing through GPT-4 integration at Formnext 2023. This allows users to execute complex slicing approaches and preset build parameters using regular language communication or commands via an uncomplicated UI.
As a result, AI-enabled AM translates the expertise into the platform, making optimized AM available to all users (interestingly, it is also unaffected by local language differences). This ranges from design file importing, to advanced slicing strategy guidance, production observation, alerts, and reporting. AI is a primary game changer and a catalyst in AM’s return on investment and readiness to expand.
Ease of Innovation and Distribution:
Cloud-hosted secure software can significantly reduce dependence on tacit knowledge silos and prevent single points of failure. It becomes possible for a business to manage several types of LFAM machines in various locations, across applications and material types using a single user interface or a section view that is secure. This promotes the capture and sharing of knowledge in the workflow and simplifies operations.
Real-time bi-directional flow of machine instructions and print data supports the delivery of various AM manufacturing strategies, such as onsite or remote printing at the point of need and micro-factory production.
From the user’s point of view, cloud deployment (including GovCloud) provides secure and streamlined team collaborations internally. It also speeds up the deployment of software feature requests and enhancements, allowing for customer-driven software innovation and support to be delivered faster and more extensively.
Adopting A User Centric, Holistic View:
Viewing additive manufacturing as a complete process, rather than just individual components like software or hardware, is critical to consumer perception. This view encourages a co-dependency between the different aspects of the system, with collaboration and integration throughout. These elements need to work together as a single, efficient system in order to optimize output.
In our efforts to facilitate this convergence we introduced our collaboration hub, AiLab, in 2015. Insights from this hub influence our software development, provide support for our customers, and inform our approaches with our material and hardware partners. As the capabilities of additive manufacturing systems increase, it’s become clear that combining the efforts of people, processes, and technology is key. Through this collaborative work with our incredible partners, we’re able to help meet client goals via improved system performance.
To Summarize:
Even quite recently AM was described as part of the “Factory of the Future”. In reality it forms part of the “Factory of Today” and as we continue to innovate, AM will continue to secure its place as part of day-to-day operations.
Daghan Cam, Co-Founder & CEO of Ai Build, will be participating at the upcoming Additive Manufacturing Strategies business summit in New York, February 6 to 8, 2024. Cam will be giving a talk on “Automated 3D Printing.”
“Why did the 3D printer go to therapy? Because it had too many layers of unresolved issues!”
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