RAPID prototyping, DECISION making, ANALYTIC hierarchy process, GREY relational analysis, FUZZY numbers, and STRENGTH of materials
A multitude of rapid prototyping (RP) systems and technologies have come up since the introduction of additive process. Owing to the enlarging number of these systems with distinctive efficacy, the problem of selecting an appropriate system for a particular requirement is a cumbersome task. Henceforth, this work comes up with a strategy based on multi-attribute decision making to select a most suitable RP system. The presence of subjectivity in decision making as well as the existence of imprecision from various sources emphasize the methods which must consider uncertainty and vagueness. A decision advisor based on uncertainty theories, including fuzzy analytical hierarchy process (FAHP) and grey relational analysis (GRA) has been introduced. It provides a comprehensive database comprising thirty nine commercially available RP systems. The evaluation attributes consisting of machine cost, accuracy, layer thickness, machine speed, material cost, net build size volume, machine weight, surface roughness, and material strength were utilized to characterize the different machines. The FAHP based on trapezoidal fuzzy number was implemented to determine the priority weights of various attributes, while the GRA was employed to realize the best RP system and technology. The authors believe that this system has the potential to transform into a fully developed RP selection system. [ABSTRACT FROM AUTHOR]
Usó, Vanessa Ghiraldeli, Sandnes, Frode Eika, and Medola, Fausto Orsi
Usó, V.G., Sandnes, F.E. & Medola, F.O. (2020). Using virtual reality and rapid prototyping to co-create together with hospitalized children. In: M. Di Nicolantonio, E. Rossi & T. Alexander (Eds.). Advances in additive manufacturing, modeling systems and 3D prototyping: Proceedings of the AHFE 2019 International Conference on Additive Manufacturing, Modeling Systems and 3D Prototyping, 2020 (pp. 279-288) Cham: Springer
WIRELESS power transmission, RAPID prototyping, RADIO frequency, GOLD coatings, and STAINLESS steel
This article presents an electromagnetically powered stent designed for hyperthermia treatment of in-stent restenosis. The stent device based on medical-grade stainless steel serves as a radio frequency (RF) inductive receiver to produce mild heating wirelessly through resonant-coupling power transfer, while acting as a mechanical scaffold inside an artery similar to commercial stents. The device and its custom transmitter are prototyped and optimized to show efficient wireless power transfer and stent heating through in vitro tests. The inductive stent with its helical pattern is gold coated to achieve a $3.5\times $ higher quality ($Q$) factor, improving heating performance of the device. The combinational use of independent resonant antennas with the power antenna is found to significantly boost stent temperature by up to 96% with an intermediate tissue layer. Upon matching the frequencies at which the $Q$ factors of the inductive stent, power antenna, and booster antenna are peaked, the stent excited through 10 mm-thick tissue exhibits a temperature increase of 18 °C, well over a necessary level for targeted hyperthermia treatment. The prototype achieves heating efficiencies (HEs) of 15.5–3.2 °C/W with a tissue thickness of 5–15 mm. These results indicate that the proposed resonant-heating stent system with the prototyped transmitter is promising for further development toward its clinical application. [ABSTRACT FROM AUTHOR]
IEEE Transactions on Power Electronics. Sep2019, Vol. 34 Issue 9, p8715-8723. 9p.
RAPID prototyping, CURRENT-voltage characteristics, and FEEDBACK (Electronics)
Using a photovoltaic (PV) emulator (PVE) simplifies the testing of the PV generation system. However, conventional controllers used for PVEs suffer from oscillating output voltage, requiring a high number of iterations, or being too complex to be implemented. This paper proposes a controller based on a resistance feedback control strategy that produces a stable and fast converging operating point for the PVE. The resistance feedback control strategy requires a new type of PV model, which is the current–resistance (I–R) PV model. This model is computed using a binary search method at a fast convergence rate. It is combined with a closed-loop buck converter using a proportional-integral controller to form the resistance feedback control strategy. The PVE's controller is implemented into dSPACE ds1104 hardware platform for experimental validation. The acquired experimental results show that the proposed PVE is able to follow the current–voltage characteristic of the PV module accurately. In addition, the PVE's efficiency is more than 90% under maximum power point operation. The transient response of the proposed PVE is similar to the PV panel during irradiance changes. [ABSTRACT FROM AUTHOR]
TARGET costing, PROTOTYPES, PRODUCT design, RAPID prototyping, and SUPPLIERS
Prototyping allows firms to evaluate the technical feasibility of alternative product designs and to better estimate their costs. We study a collaborative prototyping scenario in which a manufacturer involves a supplier in the prototyping process by letting the supplier make detailed design choices for critical components and provide prototypes for testing. While the supplier can obtain private information about the costs, the manufacturer uses target costing to gain control over the design choice. We show that involving the supplier in the prototyping process has an important influence on the manufacturer's optimal decisions. The collaboration results in information asymmetry, which makes parallel prototyping less attractive and potentially reverses the optimal testing sequence under sequential prototyping: It may be optimal to test designs in increasing order of attractiveness to avoid that the supplier does not release technically and economically feasible prototypes for strategic reasons. We also find that the classical target costing approaches (cost‐ and market‐based) need to be adjusted in the presence of alternative designs: Due to the strategic behavior of suppliers, it is not always optimal to provide identical target costs for designs with similar cost and performance estimates, nor to provide different target costs for dissimilar designs. Furthermore, the timing is important: While committing upfront to carefully chosen target costs reduces the supplier's strategic behavior, in some circumstances, the manufacturer can take advantage of this behavior by remaining flexible and specifying the second prototype's target costs later. [ABSTRACT FROM AUTHOR]
RAPID prototyping, SEARCH algorithms, DIELECTRIC-loaded antennas, THREE-dimensional printing, and PERMITTIVITY
A prototyping method for dielectrically loaded antennas is presented. Dielectric loading has been used with horn antennas, feeds, and lenses. Dielectrics have also been used for coating antennas submerged in water and biological matter and have led to improvements in bandwidth and efficiency as well as antenna miniaturisation. The authors present a new technique to produce variable dielectrics with permittivity from 6 to 28 using two commonly available powders, titanium dioxide (used in foods) and magnesium silicate (used in talcum powder). An example spherical helical ball antenna is used to demonstrate the process. In this antenna, the mixed powders were encased in a 3D printed shell that achieved a reduction in diameter of the spherical antenna by a factor of 1.85. The technique aids rapid prototyping and optimisation using search algorithms. [ABSTRACT FROM AUTHOR]
Linköpings universitet, Institutionen för klinisk och experimentell medicin, Avdelningen för cellbiologi, Linköpings universitet, Medicinska fakulteten, Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för biokemi och biofysik, Kuruvilla, Jacob, Farinha, Ana Paula, Bayat, Narges, and Cristobal, Susana
Nanoscale Horizons. (1):55-64
Natural Sciences, Biological Sciences, Biochemistry and Molecular Biology, Naturvetenskap, Biologiska vetenskaper, Biokemi och molekylärbiologi, nanoparticle, protein corona, mass spectrometry, surface proteomics, targeting, rapid prototyping, nanomedicine, Engineering and Technology, Nano Technology, Teknik och teknologier, and Nanoteknik
Engineered nanoparticles for biomedical applications requireincreasing effectiveness in targeting specific cells while preservingnon-target cell’s safety. We developed a surface proteomicsmethod for a rapid and systematic analysis of the interphasebetween the nanoparticle protein corona and the targeting cellsthat could implement the rapid prototyping of nanomedicines.Native nanoparticles entering in a protein-rich liquid mediaquickly form a macromolecular structure called protein corona.This protein structure defines the physical interaction betweennanoparticles and target cells. The surface proteins compose thefirst line of interaction between this macromolecular structureand the cell surface of a target cell. We demonstrated that SUSTU(SUrface proteomics, Safety, Targeting, Uptake) provides aqualitative and quantitative analysis from the protein coronasurface. With SUSTU, the spatial dynamics of the protein coronasurface can be studied. Data from SUSTU would ascertain thenanoparticle functionalized groups exposed at destiny that couldcircumvent preliminary in vitro experiments. Therefore thismethod could implement the analysis of nanoparticle targetingand uptake capability and could be integrated into a rapidprototyping strategy which is a major challenge in nanomaterialscience. Data are available via ProteomeXchange with identifierPXD004636.
This paper presents a discrete-time neural inverse optimal control for induction motors, which is implemented on a rapid control prototyping (RCP) system using a C2000 Microcontroller-Simulink platform. Such controller addresses the solution of three issues: system identification, trajectory tracking, and state estimation, which are solved independently. The neural controller is based on a recurrent high order neural network (RHONN), which is trained with an extended Kalman filter. The RHONN is an identifier to obtain an accurate motor model, which is robust to external disturbances and parameter variations. The inverse optimal controller is used to force the system to track a desired trajectory and to reject undesired disturbances. Moreover, the controller is based on a neural model and does not need the a-priori knowledge of motor parameters. A supertwisting observer is implemented to estimate the rotor magnetic fluxes. The hub of the RCP system is a TMS320f28069M MCU, which is an embedded combination of a 32-bit C28x DSP core and a real-time control accelerator. This Microcontroller is fully programmable from the Simulink environment. Simulation and experimental results illustrate the performance of the proposed controller and the RCP system, and a comparison with a control algorithm without the neural identifier is also included. [ABSTRACT FROM AUTHOR]
Medlej, Maroun, Stuban, Steven M. F., and Dever, Jason R.
Defense Acquisition Research Journal: A Publication of the Defense Acquisition University. Oct2017, Vol. 24 Issue 4, p626-655. 30p.
SYSTEMS engineering, RAPID prototyping, DEFENSE industries, MANUFACTURING processes, and LIKELIHOOD ratio tests
In 2007, John Young, then-Under Secretary of Defense for Acquisition, Technology and Logistics, mandated the use of "competitive prototyping" strategies in defense acquisition. Further, Department of Defense Instruction 5000.02 includes considerations for prototyping in the acquisition strategy. A 2017 memorandum circulated by Young lists five prototyping benefits, which are expected to "reduce technical risk, validate designs, validate cost estimates, evaluate manufacturing processes, and refine requirements." However, a process to assess whether, and to what extent, a prototype will be or has been successful in achieving these benefits is not currently in use by the Department of Defense. Because cost increases and schedule extension downsides are inherent in prototyping, such an assessment is critical. This research proposes an approach for assessing the likelihood of achieving expected prototyping benefits based on identifying the factors yielding these benefits as well as their relative weights. [ABSTRACT FROM AUTHOR]
Information Services & Use. 2016, Vol. 35 Issue 1/2, p71-75. 5p. 2 Color Photographs, 1 Black and White Photograph.
RAPID prototyping, INFORMATION technology, TECHNOLOGICAL innovations, and BUSINESS partnerships
To build a platform for (high, sustainable) use, we need to know what will thrill users. Finding the right concoction of technology, functionality and design to delight users takes a thousand decisions, pivots and changes. The JSTOR Labs team has been using Flash Builds -- high-intensity, short-burst, user-driven development efforts -- in order to prototype new ideas and get to a user saying "Wow" in as little as a week. In this paper, a distillation of a presentation I gave at NFAIS 2015, I will describe how we have done this, highlighting the partnerships, skills, tools and content that help us innovate. [ABSTRACT FROM AUTHOR]
Hardgrave, Bill C., Wilson, Rick L., and Eastman, Ken
Journal of Management Information Systems. Fall1999, Vol. 16 Issue 2, p113-136. 24p. 1 Diagram, 9 Charts, 4 Graphs.
INFORMATION resources management, RAPID prototyping, INDUSTRIAL surveys, COMPUTER software developers, SYSTEMS design, and ORGANIZATION
Many proposed contingencies regarding the conditions when the use of prototyping will lead to successful system development appear in the literature. Using an industry survey, this exploratory study empirically investigates the effect of certain contingencies on system success. Overall, results indicate that five variables, when combined with prototyping, affect system success (as indicated by user satisfaction): innovativeness of the project, impact of the system on the organization, user participation, number of users, and developer experience with prototyping. These results provide some insight into the proper uses of prototyping to improve system success. The results also indicate that several of the current contingencies, if followed, do not ensure high levels of system success. [ABSTRACT FROM AUTHOR]
de Garrido, Luis, Gómez Sanz, Jorge, and Pavón, Juan
AI Communications. 2019, Vol. 32 Issue 3, p223-233. 11p.
RAPID prototyping and MULTIAGENT systems
Many creative methods, such as different types of brainstorming, are based on the collaboration among a set of persons. The collaboration follows some well established workflows, which could be formalized. This would allow the generation of computational models that can be implemented to make some tools that facilitate the enactment of creative processes, or the simulation for the analysis of their characteristics. This work shows how to model this kind of collaborative creative processes as multi-agent systems, by representing the participants as interacting agents in well-defined workflows. This is done with the INGENIAS modeling language and tools, which also support rapid prototyping using the JADE agent platform. A concrete creative method, Symbolic Brainstorming, is used to illustrate and validate the feasibility of the approach. [ABSTRACT FROM AUTHOR]
International Journal of Production Research. Nov2008, Vol. 46 Issue 22, p6431-6460. 30p. 15 Diagrams, 8 Charts, 1 Graph.
PROTOTYPES, RAPID prototyping, COMPUTER integrated manufacturing systems, INDUSTRIAL engineering, MATHEMATICAL models, PRODUCTION planning, and COMPUTER-aided process planning
This paper presents a generative process planning system for parts produced by the rapid prototyping process (i.e. fused deposition modelling-FDM). The proposed process planning involves optimal selection of orientating the model with a proper support structure and then provides an intelligent slicing methodology, such as direct or adaptive, to minimise the built up time, keeping the geometry and cusp height errors in control. Pre- and post-slicing processes have been used to minimise the sliced data error. The Computer Aided Process Planning (CAPP) model has been arranged into five modules: orientation, support structure generation, slicing, path planning and Numerical Control (NC) program generation, and model build up. The CAPP model has been implemented in C language having a unique methodology consisting of 42 simplified steps. The CAPP model has been tested for several examples and shows satisfactory results. [ABSTRACT FROM AUTHOR]
International Journal of Production Research. 1/1/2005, Vol. 43 Issue 1, p169-194. 26p. 7 Black and White Photographs, 5 Diagrams, 10 Charts.
RAPID prototyping, MANAGEMENT information systems, DECISION support systems, PROTOTYPES, and PRODUCTION engineering
A new method is proposed for selecting the most appropriate rapid prototyping process according to user's specific requirements by using the expert system and fuzzy synthetic evaluation. The selection process is divided into two stages. First, it is necessary to generate feasible alternatives, which are executed under the expert system environment. Second, given those feasible alternatives, the fuzzy synthetic evaluation approach is employed to produce a ranking order of the alternatives and to finalize the most suirapid prototyping system. One distinctive characteristic of this method is that quantitative as well as qualitative measures are employed, providing more accurate results. The decision system developed based on the proposed method is composed of four modules: a database to store the specifications of various rapid prototyping processes; a knowledge-based expert system for determining the feasible alternatives; a fuzzy synthetic evaluation model to select the most suitable rapid prototyping process; and a user interface and an expert interface to interact with the system. The fuzzy synthetic evaluation approach used in the system is illustrated in detail by a numerical example. Furthermore, a Java-enabled solution, together with web techniques, is employed for developing such a networked decision support system. Finally, two examples of rapid prototyping process selection are designed to demonstrate the application of the system. The system has been implemented and can run at a rapid prototyping and manufacturing networked service platform that the authors have developed. [ABSTRACT FROM AUTHOR]
A direct-slicing approach might improve the accuracy and quality of small, complex parts produced with rapid prototyping technology. An application software based on direct slicing for rapid prototyping was used on the foundation of PowerSHAPE models. Lines, conic arcs and cubic bezier curves were adopted as the basic elements describing the direct-slicing contours. Moreover, a scheme to carry out subdivided software development was proposed. A picture (PIC) format file was selected as an interface for the slicing data, and a macro-AutoSection software, which collects the direct-slicing contour data of arbitrary complex computer-aided design models and provides power to produce the direct-slicing PIC files, was developed. On the above basis, an application software called PDSlice based on direct-slicing data processing was developed for the commercial selective laser sintering machine HRPS-III, which was made at the Huazhong University of Science and Technology (HUST), P. R. China. The major input and output interfaces as well as the PIC model reconstruction method of the PDSlice are described. Furthermore, a batch of direct-slicing polymer parts were successfully fabricated with the selective laser sintering machine. The application example shows that the accuracy and surface finish of three-dimensional complex curvature surface parts fabricated with the application software system based on a direct-slicing format were better than the application software system based on a stereolithography (STL) format. [ABSTRACT FROM AUTHOR]