Additive manufacturing promises an approach for creating complete, functional parts using a single process or machine. While industry is making progress towards this vision with technologies such as hybrid manufacturing and multi-material deposition, many challenges continue to prevent the realization of additive manufacturing’s ultimate potential. For example, different materials, such as nanocomposites and neat polymers, may require different processes that are incompatible on the same machine. In some cases, traditional layer-by-layer printing techniques cannot accommodate constraints due to inherently different properties of multiple materials. For these scenarios, either different processes need to be accessible on a single machine or the work must be split between several machines. The work to be presented here involves approaches taken to permit the printing of carbon nanotube (CNT) yarn and reduced graphene oxide (rGO) strain sensors onto the interior face of a large printed part. The geometry, location, and processing requirements for the sensors prevented them from being printed on the cartesian machine used during the original build. Therefore, a system using a six-axis articulated robot was developed to overcome the geometric restrictions of cartesian machines. Custom designed compliant toolheads helped to mitigate positioning errors common in articulated robots. Translating software converted g-code into a machine readable Python code to allow for toolpath planning using conventional slicing software. Additionally, the large build envelope and open work area enabled in-situ process monitoring via thermal imaging. The approach taken here permitted printing of sensors onto a part larger than typical build volumes available.
- Discuss the limitations of current additive manufacturing techniques for printing nanomaterial sensors.
- Describe a process and system for printing nanomaterial sensors.