MCADCafe Industry Predictions for 2024 – AlphaStar

By AlphaStar Team

The year 2023 has passed and we are in the New Year. Before we make predictions, it may be helpful to make requests. Let us hope 2024 is a time of peace.  Let us remember how much we need each other and how much we can accomplish together.  Peace may be difficult; but it is also necessary for the progress we all desire.

Let us remain positive.  Thankfully that means getting down to business and engineering.  Fortunately, technology, like people, marches on and 2024 should be a banner year.

New Roles and Applications for Polymer Additive Manufacturing (AM),

Polymer AM has always been the little engine that could.  From rapid prototyping to hobbyist to complex geometry, it has pioneered growth in AM.  Yet it always seems it is in a relay race with AM metal.  Thank you polymer, now pass the baton to AM metal for the real breakthroughs. Fortunately, what we have are two heavy stems of a strong and robust tree.  Explorations in new fibers, continuous fibers, chopped fibers, inclusions, particulates, resins, multi-materials, curing and fabrication technologies have amplified the capabilities of this venerable science.  Improvements in strength, stiffness, performance in elevated temperatures mean polymer AM can take on challenges that seemed impossible ten years ago.  Light weighting, selective critical components, and massive scaled fabrication are all within the crosshairs.  Polymer AM is ripe for reasserting its place as a major contributor to AM expansion and development. It should be noted that AlphaSTAR’s ICME based GENOA 3DP toolset provides virtual process simulation and build optimization for polymer AM parts.  The tool can also assess the durability and damage tolerance of the virtual as build part in response to service loads.

Repurposing Available Feedstocks for Metal AM Production

The United States faces challenges at every corner.  Concerns regarding costs, skilled labor, and reliable technology are only the start. America manufacturing is learning, once again, that reliance on foreign supplies at times of war may not be the healthiest choice for national security.  To date AM metal fabrication has moved forward with powder and filament sourced domestically and from around the world.  However, costs associated with mining, extraction, processing and delivery continue to increase.  Sustainability is also concerned with long term costs as well as during times of need.  Surprsingly, the DOD has an enormous supply forgotten parts and material stock that go back as far as World Wars I and 2. These stocks are located in open air fields, warehouses and subterranean caverns throughout the United States.  Conditions range from pristine to unusable.  In the near future, the US government will recover these parts, process the materials, isolate, purify and atomize to create viable powder feedstock for AM production.  The overall impact is yet to be determined but it will simultaneously address a short term need and an existing environmental hazard.  More importantly, it will provide a ready reserve of material for new alloy development, new part fabrication and the continued expansion of Metal AM.

Artificial Intelligence/Machine Learning

Additive Manufacturing is finally positioned to take advantage of Artificial Intelligence and its old sidekick Machine Learning.  This has happened because AM fabrication has become more complex, i.e., multiple printer heads, complex build challenges, complex geometries, nano-am. Large-scale AM, integrated sensor suites for in-situ monitoring, integrated robotics for multi-degree of freedom movement fabrication, and new exotic material combinations.  This complexity has demanded additional automation and computer oversight to make the next build decision based on an analysis of data history or learning derived from neural networks and intelligent choices for improved outcomes.  The shock will be related to how quickly these technologies are incorporated into existing processes and how quickly they will accelerate evolution and innovation related to those processes. Continued sophistication of software and hardware will lead to greater automation and the potential for significant scaling in terms of physical size of production as well as volume of production.  Data is king and AI/ML will ensure it is exploited to its maximum potential.

AM in the DOD

It is often stated that an army is prepared to fight the last war.  Translated, this means the best laid plans of mice and men frequently go awry. Cost structurers, attrition and technological advances have once again dramatically changed the battlefield.  Complex multipurpose platforms with high ticket prices are being challenged by one time use or attritable low cost weapon systems manufactured in their thousands (drones, missiles, etc,). Whether facing local threats or long distance deployments, our military must address supply chain challenges related to availability, shipment, storage, accessibility and readiness. Accordingly, the DOD is turning to AM in a big way to address (1) cost concerns; (2) accelerated product delivery, and (3) deployed/remote fabrication.  The DOD believes America’s technological lead in AM will translate into dramatic improvements in the readiness, sustainability and reliability of critical weapons platforms, while still supporting innovations to address new threats and adversaries.  With its multiple benefits, AM will deliver more affordable systems, accelerate development and ultimatelly deliver technology at the point of need.

AM Microstructure Control

Did you ever take a selfie and were immediately not satisfied with the result and appearance.  So you without hesitation snapped 500 pictures to finally select the image that captured the real you. Metal AM tends to involve melting and recrystallization.  When aiming for quality and maximum performance, is it sufficient to simply eliminate voids and other anomalies? Microstructural control implies establishing a protocol to achieve a desired grain architecture that ensure maximum part quality and desired part performance.  Further microstructure control suggests desired grain size and architecture as a function of location within a part, which would lead to maximum optimization of the design for increased efficiency, productivity and overall reduction in materials and costs. For the last two years, AlphaSTAR has led a team consisting of Quadrus Corporation, the University of Michigan and General Electric in a research program for the US Defense Logistic Agency to develop validated models to predict gain architecture as a function of the build plan.

There are probably a dozen more areas worthy of consideration.  These include AM exploration of metal alloys, AM of biological materials, embedded sensors in the finished AM part for lifetime performance feedback, AM in space and AM innovations in medical procedures.  While the above list represents a subset, it is poised to have an effect on the greater community in the shortest time possible.

Have a safe 2024 and see you next year.

Category: Predictions

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