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Automatic Closed-loop Adaptive Control of Part Quality in Melt Extrusion

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Conference Abstract: Additive manufacturing (AM) is enabling countless new possibilities in research and manufacturing. Among the many AM processes, material extrusion, specifically melt extrusion (thermally processing polymers), is the most popular method of fabricating parts. Melt extrusion AM involves complex thermodynamic, mechanistic and environmental interactions that often lead to inconsistent part production and poor dependability. In particular, “desktop” melt extrusion (ME) systems (costing less than US$5000) are well-known to be plagued with very high variability in as-printed material properties, low print process reliability, and huge amounts of process waste (time and material cost) that is associated with approximately 20% print failure rate by unskilled users.

In earlier work our lab developed sensors and a method for collecting real-time in-situ data from desktop melt extrusion 3D printers with the goal of improving melt extruded part quality. We validated our method by non-destructively identifying faulty 3D printed parts in actual part builds exclusively from collected in-situ data. In our latest development we successfully “closed the loop” by adjusting print parameters in real-time based on data gathered in-situ. In this session, we present a pilot implementation of automatic closed-loop adaptive control (CLAC) of part quality in melt extrusion. We use collected in-situ process data to adjust 3D printing process parameter(s) in real-time, i.e. as it's printing parts, and demonstrate that our implementation of CLAC can improve print quality and consistency by self-correcting the melt extrusion print process.