The direct ink writing (DIW) method of 3D-printing liquid resins has shown promising results in various applications such as flexible electronics, medical devices, and soft robots. A cost-effective extrusion system for a two-part high-viscous resin is developed in this article to fabricate soft and immensely stretchable structures. A static mixer capable of evenly mixing two viscous resins in an extremely low flow regime is designed based on the required mixing performance through a series of biphasic computational fluid dynamics analyses. The printing parameters of the extrusion system are determined empirically, and the mechanical properties of the printed samples are compared to their molded counterparts. Furthermore, some potential applications of the system in soft robotics and medical training are demonstrated. This research provides a clear guide for utilizing DIW to 3D print highly stretchable structures.

Robotics and automation have been a growing area within K–12 educational institutions for the past decade. Across secondary educational institutions, students are introduced to robotics in classes, after-school clubs, and competition leagues through various educational platforms, vendors, and kits. Robotics was initially implemented in schools to help drive more interest in STEM through hands-on application of mechanical, electrical, structural, and computer engineering concepts. Recently, the trend of K–12 robotics has become very niche, focusing more on mobile robotics or robotics competitions. Because of this trend, students have limited exposure to emerging technological advances, such as those found in Industry 4.0. Exciting technological areas, such as digital twins, are not covered in curricula, and this lack of exposure negatively influences the direction of student interest in the “T” and “E” of STEM, with many students never pursuing computer science, technology, or robotics in higher education. The primary goal of this research is to provide a methodology to expose secondary students to Industry 4.0 technologies by leveraging accessible technologies, such as Unity and the Robot Operating System (ROS), to develop a low-cost, high-fidelity digital twin of a pick-and-place robot in a smart warehouse operation. This digital twin prototype will help students to learn about Industry 4.0 trends, such as next-generation automation systems, digital twins, digital manufacturing, intelligent automation, and additive manufacturing, using ROS–Unity integration and hardware accessible to secondary schools to simulate a pick-and-place robotic application. By harnessing the accessibility of Unity and ROS to create a low-cost digital twin prototype for a secondary school, this research has a secondary goal of improving the pipeline of students interested in pursuing STEM-related learning in higher education, thereby ensuring a future STEM workforce that can research, design, develop, operate, and maintain the systems and technologies of Industry 4.0.

This paper describes the methodology for rapid prototyping of nitinol structures by heat setting. Nitinol is a shape memory alloy commonly used in implantable medical devices. The proposed technique, based on 3D printing, can be used to effectively iterate multiple nitinol designs for different types of medical devices. We describe a rapid and low-cost process of ceramic replica molding of standard 3D printed parts to create high-temperature resistant fixtures, suitable for heat setting of nitinol. The technique represents a low cost (<$20 materials per fixture) and rapid (as quickly as 16 h for a volume less than 1.25 × 10⁵ mm³) method for shaping nitinol, a technique that typically is costly, labor intensive, and requires specialized equipment. Our method satisfies a need for cost-effective, rapid prototyping of nitinol for implantable medical devices, and we show an example set of shaped nitinol wires, clips, and stents. This method is straightforward and can be easily applied by researchers to rapidly iterate medical device designs.

This paper presents the computational design, fabrication, and control of a novel 3-degrees-of-freedom (DOF) soft parallel robot. The design is inspired by a delta robot structure. It is engineered to overcome the limitations of traditional soft serial robot arms, which are typically low in structural stiffness and blocking force. Soft robotic systems are becoming increasingly popular due to their inherent compliance match to that of human body, making them an efficient solution for applications requiring direct contact with humans. The proposed soft robot consists of three soft closed-loop kinematic chains, each of which includes a soft actuator and a compliant four-bar arm. The complex nonlinear dynamics of the soft robot are numerically modeled, and the model is validated experimentally using a 6-DOF electromagnetic position sensor. This research contributes to the growing body of literature in the field of soft robotics, providing insights into the computational design, fabrication, and control of soft parallel robots for use in a variety of complex applications.