To print high-performance polymers, a stable running printer that can reach high temperatures is needed. There is currently a lack of low-cost solutions that allow manipulation of process parameters and expansion of sensors to monitor the printer as well as the process. This paper presents an open-source hardware upgrade for low-cost 3D printers to enable research on new high-temperature polymers as well as manufacturing from all currently available polymers. The hardware cost less than $1700, including the printer. Open-source firmware by Klipper and Fluidd is used for control. The printer is able to reach 500 °C nozzle, 200 °C heated bed, and 135 °C heated chamber with all electronics inside operating within the recommended temperature range. The presented design produced a CF-PEEK 3DBenchy and a spiral vase with excellent surface quality and no signs of delamination. Test specimens according to ISO527 using PA-CF performed similarly to the datasheet provided by the manufacturer for samples produced in the XY-orientation and outperformed the datasheet by 15 % in the ZX direction. Compared to specimens made on an Original Prusa i3 MK3S, the modified printer produced specimens with 22% higher strength in the YX-direction and 25% in ZX. By continuously monitoring and carefully calibrating both hardware and firmware, the presented design can perform as a research tool in material science and produce large-scale components of high-performance polymers.

This paper demonstrates the unpredictability of outcomes that result from compounding variabilities when using generative design (GD) coupled with additive manufacturing (AM). AM technologies offer the greatest design freedom and hence are most able to leverage the full capability of generative design (GD) tools and thus maximize potential improvements, such as weight, waste and cost reduction, strength, and part consolidation. Implicit in all studies reported in the literature is the fundamental assumption that the use of GD, irrespective of user experience or approach followed, yields high-performing and/or comparable design outputs. This work demonstrates the contrary and shows that achieving high performance with GD tools requires careful consideration of study setup and initial conditions. It is further shown that, when coupled with the inherent variability of AM parts, the potential variation in the performance of the design output can be significant, with poorer designs achieving only a fraction of that of higher-performing designs. This investigation shows how AM by Material Extrusion (MEX), which is used to manufacture components with polylactic acid (PLA), varies through different design pathways, bridging MEX and GD. Through a practical study across nine independently generated designs, the breadth of performance—due to initial GD conditions and MEX part strength unpredictability—is shown to reach 592%. This result suggest that current GD tools, including their underlying workflows and algorithms, are not sufficiently understood for users to be able to generate consistent solutions for an input case. Further, the study purports that training and consideration on GD setup are necessary to apply GD toolsets to achieve high-performing designs, particularly when applied in the context of MEX.

The current limitations of design for additive manufacturing (DfAM) are the state of knowledge on materials and the effects of production parameters. As more engineering-grade polymers become available for fused filament fabrication (FFF), the designs and processes must be adapted to fully utilize the structural properties of such materials. By studying and comparing the production parameters of a material test specimen and a component, the effects of layer temperature on the strength, surface roughness, and dimensional accuracy of PA6-CF were found. As the cross-section increases in component manufacturing, maintaining the layer temperature becomes a major challenge. From the findings, the concept of thermal layer design (TLD) was introduced as a way of increasing strength via temperature in selected regions after presenting the effect of layer temperature. TLD proved to have a major effect on layer temperature and heat distribution. Depending on the investigated layer temperature, from 147 °C to 193 °C the UTS of PA6-CF increased from 42 MPa to 73 MPa. Implementing TLD in DfAM represents a big leap for designing high-performance polymer components.

A modular sensor application for measuring athlete performance in skiing sports was developed. Using inertial measurement units (IMUs) and load cells in a modular system, a force orientation measurement system, FOMS, was developed. A functioning prototype capable of measuring ski sports dynamics was created. Data processing using the system, a validation of the prototype in terms of angle measurement IMU accuracy, example data from in-field athlete testing, and visualization by animations are described. The system developed contains four subsystems: a controller, two pole measuring modules, and a terrain-measuring module. The system structure also allows for additional modules, making the system applicable to different sports. The IMUs use orientation-sensing components to measure pole orientations, which are used to calculate decomposed forces relative to the terrain. Data from different modules are synchronized using wireless communication and saved on SD cards with time stamps. A validation experiment was conducted in which the angles from the modules were compared with the Oqus motion capture system from Qualisys. Examples for athlete testing in both cross country and alpine skiing were calculated from the matrix provided by the different modules and are presented in graphs to evaluate the athlete. In addition, the relative pole/terrain coordinates are visualized in 2D and 3D animations for analyzing the movement pattern in connection with the applied forces, opening up a whole new level of sports analysis.

This article introduces a Human-centred Engineering Design (HcED) practice, which values human aspects. This practice engages deeply into (1) human geometry and motion for specific tasks, (2) product and manufacturing complexities through rapid prototyping, and (3) the broader human task context. This cross-disciplinary method combines ergonomics, AM, sensor applications, and multiple design practices. The framework provides concrete tasks to drive innovative designs in engineering. The study, grounded in design research case studies, led to five new Paralympic Rowing world records.