Rapid Prototyping Design Research Articles

Comparing Virtual and Real-Life Rapid Prototyping Methods for User Testing Smart City Interfaces: A Case Study

In the development of complex embedded interactive systems, a tension arises between, on the one hand, ever shorter and highly iterative design processes, and, on the other hand, the need for user testing with early prototypes to validate systems from a user-centred design perspective. This study focuses on the integration of Virtual Reality (VR) into prototyping embedded interactive systems, examining its potential to bridge the gap between rapid prototyping and user-centered design validation. Adopting a comparative research approach, we analyze a case study: the development of a cultural smart city experience. It juxtaposes in situ, low-fidelity prototype testing with VR-based testing, evaluating their realism, interactivity, functionality, presence and task difficulty. This mixed-method research design incorporates both qualitative and quantitative methodologies, engaging 27 design students in a comparative study, conducting participatory research and 8 expert interviews. These findings reveal divergent roles in field testing and VR in the new product development process, highlighting VR’s strengths in visualizing procedures and facilitating discussion. This study identifies the limitations of VR in mimicking realistic interactions and incorporating social context yet underscores its superiority over paper prototypes in its realism and interactivity. Where field testing can hold broader contextual insights, the VR prototype gives more concrete and applied insights. The main advantage of VR testing is its visualisation of procedures and its final materialisation according to the participants interviewed. According to the experts interviewed, VR can be used as a useful tool within the development process especially for visualisation and testing user flows of complex interfaces.

Melting and solution mixing in the production of photocatalytic filaments for 3D printing

3D printing is a fast-growing technology with benefits like rapid prototyping and versatile design capabilities. However, Fused Deposition Modeling (FDM) needs improvement due to limited material options. This study proposes a method for producing photocatalytic prototypes using 3D printing/FDM, focusing on environmental applications like contaminant degradation. Key steps included filament production through melt and solution mixing, defining geometries, 3D printing functional prototypes, and characterizing materials chemically, thermally, microscopically, and mechanically. The photocatalytic capacity was evaluated via tetracycline degradation, showing 45–60% efficiency for ZnO filaments and up to 65% for TiO2 filaments. ZnO-functionalized parts maintained 80% removal capacity after 10 reuse cycles without activation, indicating reduced leaching and photo corrosion. This study advances 3D printing/FDM research for environmental applications, providing a methodology for producing effective photocatalytic prototypes.

Development of a Novel Transonic Fan Casing Making Use of Rapid Prototyping and Additive Manufacturing

Additive manufacturing (AM) presents significant cost savings and lead time reductions because of features inherent to the manufacturing process. The technology lends itself to rapid prototyping due to the streamlined workflow of quickly implementing design changes. Compared to traditional machining, AM techniques are simpler in execution for design engineers because they do not require detailed engineering drawings and they typically make use of the nominal geometry in computer models. A novel transonic fan casing assembly has been developed that makes use of AM inserts surrounding the rotor to provide an opportunity to cost-effectively change the corresponding flowpath. The rapid prototyping design philosophy developed from this work will allow for numerous experimental studies into the effects that different design parameters of casing geometries have on fan aerodynamic performance. A fan stage representative of a small turbofan engine was successfully tested with smooth-walled, additively manufactured inserts as a baseline case for future configurations. Before installing the 3D printed casing assembly, computational thermal stress analysis was performed to reduce the risk in implementation due to the demanding environment associated with the rotor. AM components and materials typically have nonlinear mechanical properties, adding to the complexity of the structural analysis. As part of the research, steady aerodynamic performance was measured over the entire relevant operating range of the fan.

Design and Integration of Information Systems for the Halal Inspection Institute (LPH) UIN Syarif Hidayatullah Jakarta with SiHalal Ministry of Religion of the Republic of Indonesia

In the context of the globalization of the halal industry, the Halal Inspection Institute (LPH) UIN Syarif Hidayatullah Jakarta faces challenges in improving halal certification services. This research develops a web-based information system with the integration of the Indonesian Ministry of Religion's SiHalal using the REST API and Prototype model. The main goal is to increase LPH credibility, integrate the LPH system with SiHalal, and improve LPH operational management performance. The system development method used is the Prototype Model, involving data collection through observation, interviews, and literature study to understand user needs. The first stage focuses on communication to understand needs, followed by rapid planning and prototype design. System implementation using JavaScript, NodeJs, and ReactJs. After a series of tests, the system resulted in effective integration with SiHalal and more efficient operational management. The research results include three prototypes. The first prototype focused on building an LPH profile website to increase credibility and access to information. The second prototype successfully integrated the LPH system with SiHalal, ensuring the efficiency and validity of audit reports. The third prototype adds report management, income/expenditure recording, and information updates, increasing LPH's operational efficiency.

Virtual rapid prototyping of materials with deep learning: spatiotemporal stress fields prediction in ceramics employing convolutional neural networks and transfer learning

ABSTRACT Additive manufacturing offers a solution for producing advanced ceramics with complex geometries by enabling precise control over geometry, microstructure, and composition. By leveraging deep learning, rapid prototyping and evaluation of printed ceramic parts become feasible. This study employs convolutional neural networks and transfer learning to predict spatiotemporal fields in ceramics, using synthetic datasets generated from X-ray computed tomography (micro-CT) and finite element analysis. The novel approach integrates spatiotemporal factors into deep learning models, enhancing the prediction of stress and damage evolution, and ultimately providing deeper insights into material behaviour and performance. Additionally, we introduce a target loss training strategy, which focuses on achieving a specific accuracy level, thus reducing training time while maintaining high precision. The proposed deep learning framework achieves accurate predictions of spatiotemporal stress fields, and captures fracture initiation and propagation behaviours. This method facilitates rapid prototyping and advances material design and evaluation processes while significantly reducing experimental efforts.

High-performance convolutional neural network emulation via FPGA-integrated memristive circuitry

Although memristors address the potential data flow and memory access bottlenecks in traditional von Neumann architectures by moving computational operations into the storage elements, thereby improving computational efficiency and reducing energy consumption, the current costs of memristors are relatively high, and they face issues such as low reliability and short lifespan. Therefore, this paper proposes a simulation circuit model based on FPGA, which can provide a low-cost solution for rapid prototyping design and exploration of the design space. The memristor simulation circuit is deployed on the Xilinx ZYNO-7000 FPGA XC7Z020 with a resource utilization rate of less than 1%, and it has been successfully integrated and verified. Furthermore, this paper also constructs a convolutional neural network for MNIST image recognition using a memristor model. With a basis of 512 parameters, it achieves an accuracy of 90.22%.

Custom Implants and Beyond: The Biomedical Potential of Additive Manufacturing

Additive manufacturing, commonly known as 3D printing, is revolutionizing the field of biomedical engineering by enabling the creation of custom implants tailored to individual patient anatomy. This technology uses digital design files to layer-by-layer build structures from various materials, including biocompatible metals, polymers, and ceramics. In medical applications, this precision allows for the creation of implants that closely match the contours and geometries of a patient’s unique anatomical features, offering improved fit, functionality, and comfort compared to traditional, mass-produced implants. The potential benefits extend beyond just enhanced patient outcomes. With additive manufacturing, healthcare providers can reduce surgical times by designing implants that require minimal intraoperative modification. Moreover, the flexibility of this technology facilitates rapid prototyping and iterative design, enabling healthcare professionals to collaborate with engineers in refining implant designs before they are used in surgery. This iterative approach is particularly useful in complex cases, such as craniofacial reconstruction, where conventional implants may not adequately address the intricacies of a patient’s skeletal structure.

Closed-loop control of a 3D printed soft actuator with integrated flex sensors and SMA wires

This article presents a soft SMA-driven actuator capable of achieving desired bending angles. To create the actuator, flex sensors and Shape memory alloy (SMA) wires were embedded into the thermoplastic polyurethane (TPU) matrix of the sample during the 3D printing process. By deactivating and activating the two SMA wires according to sensing signals from the flex sensors, the actuator sample can track the input bending angle. This approach enabled closed-loop control and improved the overall efficiency of the system. Additionally, the proposed manufacturing process provides a simple and cost-effective solution for the rapid prototyping and custom design of smart materials with complex structures and high resolutions.

Assessing layer deviations and correction for robotic polymer 3D printing applications

Additive manufacturing (AM), often referred to as 3D printing, is a manufacturing technique that involves the creation of complex objects layer-by-layer while providing design flexibility. The broad spectrum of additive manufacturing applications in aerospace, medicine, automotive industries, etc., using high-value materials necessitates a precise final product with minimal wastage. However, the print's dependence on optimizing parameters such as nozzle diameter, printing speed, extrusion speed, nozzle temperature and other multifaceted factors can contribute to deviations from the intended design. This paper introduces a closed-loop in-situ assessment of layer height deviations using point cloud data to ensure real-time printed part modification. The printing is done using a direct-fed pellet screw extruder mounted on top of 6 degrees of freedom robotic arm. A structured light 3D scanner is used to obtain point cloud data. A Robot Operating System (ROS) based digital toolchain is employed to have seamless communication between all nodes of the AM system. The layer-by-layer printing is observed using an in-house CAM solution, which examines the point cloud data and compares it to the original CAD model. The deviations are analyzed, and the path of the next layer is re-planned to adjust for the digression in the previous layer. This control loop ensures that the final product meets the desired quality standards at minimum cost and efficient time and increases the opportunity for rapid prototyping and iterative design improvements.

Development of a Decision Aid for Family Surrogate Decision Makers of Critically Ill Patients Requiring Renal Replacement Therapy in ICU: A User-Centered Design for Rapid Prototyping

ObjectiveRenal replacement therapy (RRT) is increasingly adopted for critically ill patients diagnosed with acute kidney injury, but the optimal time for initiation remains unclear and prognosis is uncertain, leading to medical complexity, ethical conflicts, and decision dilemmas in intensive care unit (ICU) settings. This study aimed to develop a decision aid (DA) for the family surrogate of critically ill patients to support their engagement in shared decision-making process with clinicians. MethodsDevelopment of DA employed a systematic process with user-centered design (UCD) principle, which included: (i) competitive analysis: searched, screened, and assessed the existing DAs to gather insights for design strategies, developmental techniques, and functionalities; (ii) user needs assessment: interviewed family surrogates in our hospital to explore target user group's decision-making experience and identify their unmet needs; (iii) evidence syntheses: integrate latest clinical evidence and pertinent information to inform the content development of DA. ResultsThe competitive analysis included 16 relevant DAs, from which we derived valuable insights using existing resources. User decision needs were explored among a cohort of 15 family surrogates, revealing four thematic issues in decision-making, including stuck into dilemmas, sense of uncertainty, limited capacity, and delayed decision confirmation. A total of 27 articles were included for evidence syntheses. Relevant decision-making knowledge on disease and treatment, as delineated in the literature sourced from decision support system or clinical guidelines, were formatted as the foundational knowledge base. Twenty-one items of evidence were extracted and integrated into the content panels of benefits and risks of RRT, possible outcomes, and reasons to choose. The DA was drafted into a web-based phototype using the elements of UCD. This platform could guide users in their preparation of decision-making through a sequential four-step process: identifying treatment options, weighing the benefits and risks, clarifying personal preferences and values, and formulating a schedule for formal shared decision-making with clinicians. ConclusionsWe developed a rapid prototype of DA tailored for family surrogate decision makers of critically ill patients in need of RRT in ICU setting. Future studies are needed to evaluate its usability, feasibility, and clinical effects of this intervention.

Using community theater to improve demand for vaccination services in the Niger Delta Region of Nigeria

IntroductionDespite abundant evidence showing immunization as a lifesaving public health measure, a large proportion of Nigerian children are still not or fully vaccinated. Lack of awareness and distrust of the immunization process by caregivers are some of the reasons for poor immunization coverage which need to be addressed. This study aimed at improving vaccination demand, acceptance and uptake in Bayelsa and Rivers State, both in the Niger Delta Region (NDR) of Nigeria through a human-centered process of trust building, education and social support.MethodsA quasi-experimental intervention christened Community Theater for Immunization (CT4I) was deployed in 18 selected communities between November 2019 and May 2021 in the two states. In the intervention localities, relevant stakeholders including the leadership of the health system, community leaders, health workers and community members were engaged and actively involved in the design and performance of the theaters. The content for the theater showcased real stories, using a human-centered design (HCD) of ideation, co-creation, rapid prototyping, feedback collection and iteration. Pre- and post-intervention data on the demand and utilization of vaccination services were collected using a mixed method.ResultsIn the two states, 56 immunization managers and 59 traditional and religious leaders were engaged. Four broad themes implicating user and provider factors emerged from the 18 focus group discussions as responsible for low immunization uptake in the communities. Of the 217 caregivers trained on routine immunization and theater performances, 72% demonstrated a knowledge increase at the post-test. A total of 29 performances attended by 2,258 women were staged with 84.2% of the attendees feeling satisfied. At the performances, 270 children received vaccine shots (23% were zero-dose). There was a 38% increase in the proportion of fully immunized children in the communities and 9% decline in the proportion of zero-dose children from baseline.ConclusionBoth demand- and supply-side factors were identified as responsible for poor vaccination in the intervention communities. Our intervention demonstrates that caregivers will demand immunization services if they are engaged through community theater using a human-centered design (HCD). We recommend a scaling up of HCD to address the challenge of vaccine hesitancy.

Knowledge Driven Synthesis Using Resource-Capability Semantics for Control Software Design

This paper presents a knowledge-driven approach for automated synthesis of controllers in three different use-cases. The approach addresses the engineering challenge posed by Industrie 4.0, which requires fast, reliable, and flexible integration of multiple heterogeneous hardware and software components. Manual design approaches are not scalable for large systems due to their complexity. The proposed approach captures resource-capability knowledge and uses a reasoning-based synthesis mechanism to compose a controller design for a plant goal. The approach uses domain-specific languages (DSLs) to describe the components, their interfaces, and capabilities. The generated control designs are executable codes that implement the control strategy. The proposed approach reduces the average engineering time by 70% and generates on an average 60% of the executable code in each use-case. The approach uses a knowledge repository to store resource-capability knowledge and enables rapid prototyping and iterative design. The proposed approach provides a promising solution to automate the synthesis of controllers in different use-cases with multiple heterogeneous hardware and software components satisfaction.

An experimental study on the role of manufacturing parameters on the dry sliding wear performance of additively manufactured PETG

Abstract Additive manufacturing (AM) is a versatile and promising method for rapid prototyping and advanced design applications. Owing to its unique potential for fast production rates, and capacity of creating complex shapes, the number of researches on AM techniques have increased day by day in the technical literature. In this work, contrary to common literature efforts focused on mechanical properties, friction and wear behaviors of additively manufactured PETG samples were analyzed experimentally. As a methodology, fused filament fabrication (FFF) was selected. In order to explore the influence of manufacturing factors on wear properties, layer thickness (0.1, 0.2, and 0.3 mm), infill rate (40, 60, 80, and 100%), and building direction (vertical and horizontal) were changed. Before the friction tests, dimensional accuracy, hardness, and surface roughness measurements were conducted to interpret better the wear results. In addition, macroscopic and microscopic inspections were performed to determine the correct reason behind the deformation. From the data collected during the tests, there was a positive interaction between volume loss and layer thickness. Besides, there was no direct interaction between infill rate/building direction and coefficient of friction. In comparison with vertically built samples, horizontally built samples were subjected to more plastic deformation, and their worn surfaces were severely damaged.

Model-based on-board post-injection control development for marine diesel engine

Abstract The increasing demands for reducing fuel consumption and emissions in contemporary technology solutions lead to the use of more sensors, actuators, and control applications. With this increasing engine complexity, the feedback design is complex due to the coupling between inputs and combustion parameters. To be able to design the controller systematically, model predictive control (MPC) comes to the scope because of its advantages in the design of multi-input multi-output (MIMO) systems, especially with its constraints handling ability and performance in simultaneously optimizing the engine fuel efficiency and emission reduction. Multi-injection is one of the promising techniques for achieving better engine performance. In this work, post-injection control is implemented utilizing MPC MIMO strategy with the target of exploring the possibility of reducing emissions and improving engine efficiency by controlling post-injection duration and injection timing. The workflow of the MPC controller design from control-oriented model (COM) establishing to MPC problem formation and solution methodology is discussed in this work. Moreover, one contribution from this work is the different implementation angle when compared with the state-of-the-art approaches, where the MPC controller is implemented purely by Matlab Simulink to enable the rapid control prototyping design. The simulation result demonstrated the ability of the controller’s tracking performance and showed a preliminary step towards the nonlinear combustion model-based multi-injection MPC design. The systematic model-based controller framework developed in this work can be applied to other control applications and enables a fast path from design to test.

3D Printing in Fractures: A Game Changer?

Background: 3D printing (3DP) or additive manufacturing has become an established technique in many industries for its fast production of objects with a large range of shapes and designs. Whereas it was initially used for rapid prototyping and product design evaluation, it has been applied more and more in small batch production as well. In the medical field 3DP has demonstrated its potential for various purposes, ranging from mere display of anatomy to printing of implants in tissue, although the latter application still needs to be translated to the clinical field and demonstrate usefulness. Applications of 3D printing: We will present an overview of the different clinical uses of 3DP in the process of fracture treatment and where these uses may prove to be beneficial. This will encompass the use for patient interaction, in which a physical model of the anatomy is used to explain the complexity of the fracture to the patient. We will also consider the preparation of the intervention in which the 3D model is used: i) to understand and appreciate the fractures lines, ii) to come up with a suitable classification, and iii) realize a surgical plan (Figure 1). A third use is the surgical simulation of the intervention, in which the surgeon conducts a trial surgery on a 3D printed model. Finally, 3DP can be employed in the design of surgical templates or guides that enable the surgeon to accurately transfer a digital preoperative plan to the surgical environment. Practical implications:Realizing a 3DP solution within a clinical environment can be challenging and often requires a multi-disciplinary approach. Hence, it is important to know the pitfalls of such an endeavor. We will present the different practical steps involved in the realization of a 3DP solution in clinical practice. This involves image acquisition, image segmentation for anatomical model generation, surgical preparation and/or modeling, and the actual 3DP the anatomical part or surgical guide. Finally, we will highlight important considerations that may be prohibitive for deploying a 3D-printed solution in the hospital. More specifically we will touch upon the legal boundaries that are set by the recent introduction of the Medical Device Regulation (MDR) but also on aspects of cost-efficiency of 3DP solutions. In this respect, some applications may find that 3D visualization of the anatomy is a valid alternative to 3DP and (future) developments in the field of artificial intelligence may reduce the cost of patient-tailored solutions.

Rapid prototyping and customizable microneedle design: Ultra-sharp microneedle fabrication using two-photon polymerization and low-cost micromolding techniques

In recent years, interest in microneedle devices for drug and vaccine delivery and point-of-care diagnostics has grown due to low cost, convenience and minimal invasiveness. A cluster of miniature needles on a small patch could enhance the quality of human health care, revolutionizing test and drug and vaccine delivery systems. However, current fabrication methods are not viable for cost-effective large-scale manufacture. This study reports fabrication of ultra-sharp microneedles with microfluidic channels using two-photon polymerization (2PP) which enables flexible designs with resolution down to 100 nm. The technique is ideally suited to prototyping and the fabrication of master molds from which elastomeric negative-molds have been used in a rapid micromolding technique to make batches of ultra-sharp microneedles. This micromolding process has mass manufacturing potential.

Current and future trends of additive manufacturing for chemistry applications: a review.

Three-dimensional (3-D) printing, also known as additive manufacturing, refers to a method used to generate a physical object by joining materials in a layer-by-layer process from a three-dimensional virtual model. 3-D printing technology has been traditionally employed in rapid prototyping, engineering, and industrial design. More recently, new applications continue to emerge; this is because of its exceptional advantage and flexibility over the traditional manufacturing process. Unlike other conventional manufacturing methods, which are fundamentally subtractive, 3-D printing is additive and, therefore, produces less waste. This review comprehensively summarises the application of additive manufacturing technologies in chemistry, chemical synthesis, and catalysis with particular attention to the production of general laboratory hardware, analytical facilities, reaction devices, and catalytically active substances. It also focuses on new and upcoming applications such as digital chemical synthesis, automation, and robotics in a synthetic environment. While discussing the contribution of this research area in the last decade, the current, future, and economic opportunities of additive manufacturing in chemical research and material development were fully covered.Graphical abstract

Decision Support for Tactical Combat Casualty Care Using Machine Learning to Detect Shock.

The emergence of more complex Prolonged Field Care in austere settings and the need to assist inexperienced providers' ability to treat patients create an urgent need for effective tools to support care. We report on a project to develop a phone-/tablet-based decision support system for prehospital tactical combat casualty care that collects physiologic and other clinical data and uses machine learning to detect and differentiate shock manifestation. Software interface development methods included literature review, rapid prototyping, and subject matter expert design requirements reviews. Machine learning algorithm methods included development of a model trained on publicly available Medical Information Mart for Intensive Care data, then on de-identified data from Mayo Clinic Intensive Care Unit. The project team interviewed 17 Army, Air Force, and Navy medical subject matter experts during design requirements review sessions. They had an average of 17 years of service in military medicine and an average of 4 deployments apiece and all had performed tactical combat casualty care on live patients during deployment. Comments provided requirements for shock identification and management in prehospital settings, including support for indication of shock probability and shock differentiation. The machine learning algorithm based on logistic regression performed best among other algorithms we tested and was able to predict shock onset 90 minutes before it occurred with better than 75% accuracy in the test dataset. We expect the Trauma Triage, Treatment, and Training Decision Support system will augment a medic's ability to make informed decisions based on salient patient data and to diagnose multiple types of shock through remotely trained, field deployed ML models.

Thermal and Manufacturing Design Considerations for Silicon-Based Embedded Microchannel Three-Dimensional-Manifold Coolers (EMMC)—Part 3: Addressing Challenges in Laser Micromachining-Based Manufacturing of Three-Dimensional-Manifolded Microcooler Devices

Abstract Laser machining is an inexpensive and fast alternative to conventional microfabrication techniques and has the capability to produce complicated three-dimensional (3D), hierarchical structures. It is especially important while performing rapid prototyping and quick design studies of extreme heat flux cooling devices. One of the major issues plaguing the use of laser micromachining to manufacture commercially usable devices, is the formation of debris during cutting and the difficulty in removing these debris efficiently after the machining process. For silicon substrates, this debris can interfere with surrounding components and cause problems during bonding with other substrates by preventing uniform conformal contact. This study delves deep into the challenges faced and methods to overcome them during laser micromachining-based manufacturing of such complicated 3D-manifolded microcooler structures. Specifically, this work summarizes several postprocess techniques that can be employed for complete debris removal during etching of silicon samples using an Nd/YVO4 ultraviolet (UV) laser, detailing the advantages and drawbacks of each approach. A method that was found to be particularly promising to achieve very smooth surfaces with almost complete debris removal was the use of polydimethylsiloxane (PDMS) as a high-rigidity protective coating. In the process, a novel technique to strip PDMS from silicon surface was also developed. The result of this study is valuable to the microfabrication industry where smooth and clean substrate surfaces are highly desirable and it will significantly improve the process of using UV lasers to create microstructures for commercial applications as well as in a research environment.

Immersive visual scripting based on VR software design patterns for experiential training

Virtual reality (VR) has re-emerged as a low-cost, highly accessible consumer product, and training on simulators is rapidly becoming standard in many industrial sectors. However, the available systems are either focusing on gaming context, featuring limited capabilities or they support only content creation of virtual environments without any rapid prototyping and modification. In this project, we propose a code-free, visual scripting platform to replicate gamified training scenarios through rapid prototyping and VR software design patterns. We implemented and compared two authoring tools: a) visual scripting and b) VR editor for the rapid reconstruction of VR training scenarios. Our visual scripting module is capable to generate training applications utilizing a node-based scripting system whereas the VR editor gives user/developer the ability to customize and populate new VR training scenarios directly from the virtual environment. We also introduce action prototypes, a new software design pattern suitable to replicate behavioral tasks for VR experiences. In addition, we present the training scenegraph architecture as the main model to represent training scenarios on a modular, dynamic and highly adaptive acyclic graph based on a structured educational curriculum. Finally, a user-based evaluation of the proposed solution indicated that users - regardless of their programming expertise - can effectively use the tools to create and modify training scenarios in VR.