Computer-aided Design Design Research Articles

EUCLIDIAN DISTANCE TRANSFORMATION, MAIN AXIS ROTATION AND NOISY DILITATION SUPPORTED CROSS-SECTION CLASSIFICATION WITH CONVOLUTIONAL NEURAL NETWORKS

AbstractPolygon meshes and particularly triangulated meshes can be used to describe the shape of different types of geometry such as bicycles, bridges, or runways. In engineering, such polygon meshes can be supplied as finite element meshes, resulting from topology optimization or from laser scanning. Especially from topology optimization, frame-like polygon meshes with slender parts are typical and often have to be converted into a CAD (Computer-Aided Design) format, e.g., for further geometrical detailing or performing additional shape optimization. Especially for such frame-like geometries, CAD designs are constructed as beams with cross-sections and beam-lines, whereby the cross-section is extruded along the beam-lines or beam skeleton. One major task in the recognition of beams is the classification of the cross-section type such as I, U, or T, which is addressed in this article. Therefore, a dataset consisting of different cross-sections represented as binary images is created. Noisy dilatation, the distance transformation, and main axis rotation are applied to these images to increase the robustness and reduce the necessary amount of samples. The resulting images are applied to a convolutional neuronal network.

From CAD design to robot models and simulation tools. Test-case example using the Kassow 810 collaborative robot

PurposeThis paper aims to introduce, in a tutorial form, a collection of procedures, tools and applications that can be used to explore robotics fundamentals and automatically generate kinematic and dynamic models from computer-aided design (CAD) packages, to create representations of the robot manipulator understudy so that a user can generate trajectories and to simulate and visualize the robot motion using several programming, simulation and developing tools. In this paper, the authors are particularly interested in advanced three-dimensional design packages such as Inventor and SolidWorks, interactive mathematical and simulation environments such as Matlab, Simulink, Simscape Multibody and Robot Operating System, and several application development languages such as C# and Python. A few of them will be used throughout the paper in a collection of examples that use the new Kassow 810 collaborative robot as a test-case demonstration. In the process, the authors expect readers to fully understand how to use all these tools to other machines and to their own designs.Design/methodology/approachConsequently, the paper follows a step-by-step practical procedure, fully tested and explained using the already mentioned state-of-the-art collaborative robot, guiding the reader from the design, modeling, simulation and application development phases, which may be applied to other machines and robotic designs.FindingsThe results clearly show that the procedure of starting from a CAD design to generate the kinematic and dynamic models of a robot manipulator create representations of the robot, generate trajectories and simulate/visualize the robot motion is feasible and accessible to a general user (using standard tools).Research limitations/implicationsAlthough the paper uses a few particular software packages, the concepts and kept general, which means that they can be used with other equivalent tools. With that objective in mind, the paper introduces the basic robotics concepts involved, further increasing in this way its tutorial structure.Originality/valueConsequently, the presented procedure has the inherent value of introducing robotics fundamentals in a practical way, but also of demonstrating how readers can build and explore advanced robotic designs using common design, simulation and programming tools.

Integrating deep learning into CAD/CAE system: generative design and evaluation of 3D conceptual wheel

Engineering design research integrating artificial intelligence (AI) into computer-aided design (CAD) and computer-aided engineering (CAE) is actively being conducted. This study proposes a deep learning-based CAD/CAE framework in the conceptual design phase that automatically generates 3D CAD designs and evaluates their engineering performance. The proposed framework comprises seven stages: (1) 2D generative design, (2) dimensionality reduction, (3) design of experiment in latent space, (4) CAD automation, (5) CAE automation, (6) transfer learning, and (7) visualization and analysis. The proposed framework is demonstrated through a road wheel design case study and indicates that AI can be practically incorporated into an end-use product design project. Engineers and industrial designers can jointly review a large number of generated 3D CAD models by using this framework along with the engineering performance results estimated by AI and find conceptual design candidates for the subsequent detailed design stage.

Integration of AM process in design cycle of metallic parts: Application to space components

Identified in the European strategy as a key enabling technology, Additive Manufacturing (AM) has a great potential for industries to reshape, improve and optimize product life cycle, with reduced environmental footprint such as material waste in production. Allowing to meet structural and multi-disciplinary requirements with complex freeform design at a much lower weight than high constrained conventional manufacturing, AM can benefit to numerous space applications. Beside manufacturing process development, software and process control are becoming absolutely necessary to support digitalization of industrial workflow. Dedicated tools such as Computer Aided Design (CAD), Computer Aided Engineering (CAE) and Computer Aided Manufacturing (CAM) were introduced in the digital manufacturing chain; however, their development was driven by standard manufacturing processes. Therefore, appropriate design methods for AM must emerge in a fully integrated end-to-end solution to foster and support the growth and competitiveness of AM. In order to support industrialization of AM, the European Space Agency has selected the Design4AM project, based on a strong partnership between Siemens and Sonaca, for “Development of Design Methods for AM including CAD Design, Optimization, FEM Analysis and Manufacturing features”. On one hand, the project aims at combining within a comprehensive end-to-end process, topology optimization, seamless CAD data flows and predictive process simulation in the Siemens’ NX™ and Simcenter™ environments. On the other hand, the integration of dedicated industrial design workflow within the enhanced Siemens Digital Innovation Platform is validated on a relevant ESA space application provided by Sonaca.

CACDA: A knowledge graph for a context-aware cognitive design assistant

The design of complex engineered systems highly relies on a laborious zigzagging between computer-aided design (CAD) software and design rules prescribed by design manuals. Despite the emergence of knowledge management techniques (ontology, expert system, text mining, etc.), companies continue to store design rules in large and unstructured documents. To facilitate the integration of design rules and CAD software, we propose a knowledge graph that structures a large set of design rules in a computable format. The knowledge graph organises entities of design rules (nodes), relationships among design rules (edges), as well as contextual information. The categorisation of entities and relationships in four sub-contexts: semantic, social, engineering, and IT – facilitates the development of the data model, especially the definition of the “design context” concept. The knowledge graph paves the way to a context-aware cognitive design assistant. Indeed, connected to or embedded in a CAD software, a context-aware cognitive design assistant will capture the design context in near real time and run reasoning operations on the knowledge graph to extend traditional CAD capabilities, such as the recommendation of design rules, the verification of design solutions, or the automation of design routines. Our validation experiment shows that the current version of the context-aware cognitive design assistant is more efficient than the traditional document-based design. On average, participants using an unstructured design rules document have a precision of 0.36 whereas participants using our demonstrator obtain a 0.61 precision score. Finally, designers supported by the design assistant spend more time designing than searching for applicable design rules compared to the traditional design approach.

The rise of 3D Printing entangled with smart computer aided design during COVID-19 era

During the current Pandemic, seven and a half million flights worldwide were canceled which disrupted the supply chain of all types of goods such as, personal protective gears, medical health devices, raw materials, food, and other essential equipments. The demand for health and medical related goods increased during this period globally, while the production using classical manufacturing techniques were effected because of the lockdowns and disruption in the transporation system. This created the need of geo scattered, small, and rapid manufacturing units along with a smart computer aided design (CAD) facility. The availability of 3D printing technologies and open source CAD design made it possible to overcome this need. In this article, we present an extensive review on the utilization of 3D printing technology in the days of pandamic. We observe that 3D printing together with smart CAD design show promise to overcome the disruption caused by the lockdown of classical manufacturing units specially for medical and testing equipment, and protective gears. We observe that there are several short communications, commentaries, correspondences, editorials and mini reviews compiled and published; however, a systematic state-of-the-art review is required to identify the significance of 3D printing, design for additive manufacturing (AM), and digital supply chain for handling emergency situations and in the post-COVID era. We present a review of various benefits of 3DP particularly in emergency situations such as a pandemic. Furthermore, some relevant iterative design and 3DP case studies are discussed systematically. Finally, this article highlights the areas that can help to control the emergency situation such as a pandemic, and critically discusses the research gaps that need further research in order to exploit the full potential of 3DP in pandemic and post-pandemic future era.

Development of 3-dimensional Printed Distal Finger Prosthesis With Assembly-free Joint

PURPOSE: Finger and fingertip amputation is common, with tens of thousands of cases occurring yearly in the United States.1 Distal fingertip amputation occurs more frequently than complete finger amputation and often in young and productive populations.2 Apart from loss of sensation, the loss of one or more fingertips often results in drastic functional deficits. Current options for functional finger prostheses are often cost-prohibitive and generally require additional refinement after fabrication. The purpose of this study was to design an option for prosthesis made exclusively via 3-dimensional (3D) printing. In doing so, we hoped to restore an adequate level of function to patients while keeping costs low and requiring minimal postproduction refinement and maintenance. METHODS: Our prototype was made for a patient with amputation at the distal interphalangeal joint (DIJ) of the left ring finger. The patient’s intact ring finger was measured in order to produce a digital model using computer-aided design (CAD) software. Measurements utilized included metacarpophalangeal (MCP) joint to distal tip, and the widths of proximal, middle, and distal phalanx segments. The length of the amputated digit was also measured from MCP joint to amputation stump. This CAD design was finally submitted to an online 3D printing service (Shapeways) to allow for replicas to be ordered by the patient directly while maintaining low production cost. RESULTS: Our final model utilized a single, flexible joint consisting of 2 pins molded directly into the medial and lateral aspects of the prosthesis immediately after 3D printing. High grade nylon material was used during the fabrication process to confer low cost while maintaining comfort and durability. Quality range of motion and improved anatomical grasping of objects was achieved, creating significant return of function. CONCLUSIONS: Our device accomplishes the goal of creating a functional prosthetic fingertip using exclusively 3D printing. In addition, while other 3D printing prosthetics have required significant postproduction customization and maintenance, this device’s intrinsic joint system makes it essentially maintenance free and can be used immediately following printing. The use of high-grade nylon confers stability and durability at a fraction of the cost of previously used materials. Utilizing a third-party 3D-printing company and freely available CAD plans, a patient will be able to upload their measurements and a device can be created and shipped to them for around $20 USD. We see particular utility of our device in pediatric populations as the customizable design and economical production allow for several devices to be used throughout a child’s development. REFERENCES: 1. Reavey PL, Stranix JT, Muresan H, et al. Disappearing digits: analysis of national trends in amputation and replantation in the United States. Plast Reconstr Surg. 2018;141:857e–867e. 2. Østlie K, Skjeldal OH, Garfelt B, et al. Adult acquired major upper limb amputation in Norway: prevalence, demographic features and amputation specific features. A population-based survey. Disabil Rehabil. 2011;33:1636–1649.

Design and Fabrication of Implants for Mandibular and Craniofacial Defects Using Different Medical-Additive Manufacturing Technologies: A Review.

Mandibular and craniofacial bone defects can be caused by trauma, inflammatory disease, and benign or malignant tumors. Patients with bone defects suffer from problems with aesthetics, speech, and mastication, resulting in the need for implants. Conventional methods do not always provide satisfactory results. Most of the techniques proposed by researchers in the field of biomedical engineering use reverse engineering, computer-aided design (CAD), and additive manufacturing (AM), whose implementation can improve the outcomes of reconstructive surgeries. Several literature reviews on this particular topic have been conducted. However, they provide mostly overviews of AM technologies for general biomedical devices. This paper summarizes the use of existing medical AM techniques for the design and fabrication of mandibular and craniofacial implants, and then discusses their advantages and disadvantages in terms of accuracy, costs, energy consumption, and production rate. The aim of this study is to present a comparative review of the most commonly used AM technologies to aid researchers in selecting the best possible AM technologies for medical use. Studies included in this review contain CAD designs of mandibular or cranial implants, as well as their fabrication using AM technologies. Special attention is paid to PolyJet technology, because of its high accuracy, and economical efficiency.

Shape optimization of heterogeneous materials based on isogeometric boundary element method

In this paper, the isogeometric boundary element method (IGABEM) is used to optimize the shape of heterogeneous materials. In contrast to the isogeometric finite element method (IGAFEM), the iterative optimization algorithm based on IGABEM can be implemented directly from Computer-Aided Design (CAD) without returning the optimization results to CAD designers. The discontinuous element method is extended to IGABEM which deals with corner point problems of inhomogeneous materials. After the singularity of sensitivity analysis of boundary integral equations is demonstrated, the power series expansion method (PSEM) is applied to IGABEM to evaluate various degrees of singularity about sensitivity analysis, which shows more accuracy and efficiency than the element sub-division method (ESDM). A set of control points on the geometric boundary are chosen as design variables, which can be passed from the design model to the analysis model, and the objective function is the elastic energy increment. Finally, several numerical examples in 2D and 3D problems are presented to demonstrate the validity and robustness of the present method.

Custom-made 3D-printed face masks in case of pandemic crisis situations with a lack of commercially available FFP2/3 masks

In the case of pandemic crisis situations, a crucial lack of protective material such as protective face masks for healthcare professionals can occur. A proof of concept (PoC) and prototype are presented, demonstrating a reusable custom-made three-dimensionally (3D) printed face mask based on materials and techniques (3D imaging and 3D printing) with global availability. The individualized 3D protective face mask consists of two 3D-printed reusable polyamide composite components (a face mask and a filter membrane support) and two disposable components (a head fixation band and a filter membrane). Computer-aided design (CAD) was used to produce the reusable components of the 3D face mask based on individual facial scans, which were acquired using a new-generation smartphone with two cameras and a face scanning application. 3D modelling can easily be done by CAD designers worldwide with free download software. The disposable non-woven melt-blown filter membrane is globally available from industrial manufacturers producing FFP2/3 protective masks for painting, construction, agriculture, and the textile industry. Easily available Velcro fasteners were used as a disposable head fixation band. A cleaning and disinfection protocol is proposed. Leakage and virological testing of the reusable components of the 3D face mask, following one or several disinfection cycles, has not yet been performed and is essential prior to its use in real-life situations. This PoC should allow the reader to consider making and/or virologically testing the described custom-made 3D-printed face masks worldwide. The surface tessellation language (STL) format of the original virtual templates of the two reusable components described in this paper can be downloaded free of charge using the hyperlink (Supplementary Material online).

Artificial intelligence in fixed implant prosthodontics: a retrospective study of 106 implant-supported monolithic zirconia crowns inserted in the posterior jaws of 90 patients

BackgroundArtificial intelligence (AI) is a branch of computer science concerned with building smart software or machines capable of performing tasks that typically require human intelligence. We present a protocol for the use of AI to fabricate implant-supported monolithic zirconia crowns (MZCs) cemented on customized hybrid abutments.MethodsThe study protocol consisted of: (1) intraoral scan of the implant position; (2) design of the individual abutment and temporary crown using computer-aided design (CAD) software; (3) milling of the zirconia abutment and the temporary polymethyl-methacrylate (PMMA) crown, with extraoral cementation of the zirconia abutment on the relative titanium bonding base, to generate an individual hybrid abutment; (4) clinical application of the hybrid abutment and the temporary PMMA crown; (5) intraoral scan of the hybrid abutment; (6) CAD of the final crown with automated margin line design using AI; (7) milling, sintering and characterisation of the final MZC; and (8) clinical application of the MZC. The outcome variables were mathematical (quality of the fabrication of the individual zirconia abutment) and clinical, such as (1) quality of the marginal adaptation, (2) of interproximal contact points and (3) of occlusal contacts, (4) chromatic integration, (5) survival and (6) success of MZCs. A careful statistical analysis was performed.Results90 patients (35 males, 55 females; mean age 53.3 ± 13.7 years) restored with 106 implant-supported MZCs were included in the study. The follow-up varied from 6 months to 3 years. The quality of the fabrication of individual hybrid abutments revealed a mean deviation of 44 μm (± 6.3) between the original CAD design of the zirconia abutment, and the mesh of the zirconia abutment captured intraorally at the end of the provisionalization. At the delivery of the MZCs, the marginal adaptation, quality of interproximal and occlusal contacts, and aesthetic integration were excellent. The three-year cumulative survival and success of the MZCs were 99.0% and 91.3%, respectively.ConclusionsAI seems to represent a reliable tool for the restoration of single implants with MZCs cemented on customised hybrid abutments via a full digital workflow. Further studies are needed to confirm these positive results.

Peak Your Frequency: Advanced Search of 3D CAD Files in the Fourier Domain

An ever-increasing number of industries are adopting additive manufacturing (AM), also known as 3D printing , to their production lifecycles for manufacturing parts. A computer aided design (CAD) model is used to manufacture the part. The capability for efficient search and retrieval of the CAD models from the database has become an essential need for designers and users. However, traditional search techniques perform poorly in the context of searching CAD designs. In this paper, we propose Fourier Fingerprint Search (FFS), a retrieval framework for 3D models that deduces and leverages critical shape characteristics for search. FFS introduces a novel search methodology that incorporates these characteristics and uses two advanced matching techniques that operate at different granularities and take into account unique patterns associated with each design. In addition, FFS supports both exact and partial matching in order to provide helpful and robust search results for any scenario. We investigate a diverse set of features and enhancements for search that allows for high adaptability in all situations, such as dividing shapes into smaller parts, surface interpolation, and two different types of rotation. We evaluate FFS using the FabWave CAD dataset with approximately 3000 manufacturing models with different configurations. Our experimental results demonstrate the efficiency and high accuracy of our approach for both exact and partial matching, rendering FFS a powerful framework for CAD model search.

Proposal of new eco-manufacturing feature interaction-based methodology in CAD phase

Following the environmental crises of recent decades, a turning point in the awareness of the fragility of ecosystems has been marked, i.e., environmental awareness. This has contributed to the development of various environmental laws and regulations such as the “Waste Electrical and Electronic Equipment,” the “Restriction of Hazardous Substances,” and the “Registration, Evaluation, Authorization and Restriction of Chemicals” regulations and the “Energy Using Products” Directives. Our work contributes to the development of eco-friendly product manufacturing processes. In order to estimate and optimize the environmental impacts of a product, most of the methodologies, concepts, and tools that integrate computer-aided design (CAD) and life cycle assessment systems generally exploit the feature technology at the level of each feature independently of the others, i.e., “microplanning.” The feature interaction technology (FIT) is treated only in few studies, but it is pivotal in the eco-manufacturing process. In this paper, we propose a new manufacturing-scenarios-based methodology by using FIT and a Multi-criteria Decision Support Method (MCDSM), which helps manufacturers maintain their marketplaces by producing goods in an eco-friendly way. In fact, this methodology helps designers choose from the CAD design phase the most ecological manufacturing process from possible existent scenarios in real time.

A Multi-Objective-Driven Placement Technique for Digital Microfluidic Biochips

Microfluidic biochips are extensively utilized in biochemistry procedures due to their low cost, high precision and efficiency when compared to traditional laboratory procedures. Recent, computer-aided design (CAD) techniques enable a high performance in digital microfluidic biochip design. A key part in digital microfluidic biochip CAD design is the biochip placement procedure which determines the physical location for biological reactions during the physical design. For the biochip physical design, multiple objects need to be considered, such as the size of the chip and the total operation time. In this paper, a multi-objective optimization is proposed based on Markov decision processes (MDPs). The proposed method is evaluated on a set of standard biochip benchmarks. Compared to existing works, experimental results show that the total operation time, the capacity for routing and the chip size can be optimized simultaneously.

Customized CAD Modeling and Design of Production Process for One-Person One-Clothing Mass Production System

Following the development of the Industrial Revolution 4.0, many new types of systems are being designed, introduced, or attempted, even in almost every traditional industry. The clothing industry is no exception. The use of continuously developing production equipment and Information and Communication Technology (ICT) has a single objective, providing a customized service to all customers. Thus, in this study, the primary research task was to identify ill-balanced aspects or disadvantages of the services previously analyzed to construct a more complete online customized service. This was accomplished by analyzing an automated Computer-Aided Design (CAD) output file containing customer requirements regarding individual clothing items. The secondary research task was to plan and design a clothing manufacturing process to which a one-person one-item mass production system has been applied to achieve a customized service. As a result, for the primary research task, the customers’ requirements for each dress were reflected in attributes, such as color, pattern, or size, and it was possible to obtain an automated CAD output file for each element. Such CAD output files can be used in the production process directly. To find the possibility of upgrading the existing dressmaking process and implement the one-person one-item system, the entire manufacturing process was simulated for the test.

Systematic Analysis of Production Errors and Accuracy when using Pin-Bed Mold of Free-form Concrete Panels

Although various mold design and techniques have been introduced for free-form building production, successes so far have been only minor owing to lack of adaptability, machine errors, and high production cost. Herein, this presents a new reusable mold technique called a Pin-bed Mold (PBM), an inexpensive rubber mold based mechanical method and validates its applicability using the shape implementation method. This paper also describes a Failure Mode Effects Analysis (FMEA) for development of the PBM considering risk. A prototype free-form shape was designed using Computer-aided Design (CAD), and an experiment was conducted to produce smooth Free-form Concrete Panels (FCPs) rapidly and easily using a Computerized Numerical Control (CNC) machine and PBM. The rubber mold produced was measured using an optical sensor and compared with the designed FCP shape. The experimental showed significant errors in FCP shape between the CAD design and the measured CNC, and PBM shapes. The failure modes of the PBM and their causes were identified, while examining the PBM production capability. According to the FMEA method, weaknesses in the operation of PBM that could potentially lead to shape errors were identified.

Microstructure and fracture properties of open-cell porous Ti-6Al-4V with high porosity fabricated by electron beam melting

The open-cell porous Ti-6Al-4V structure with high porosity, intended to be applied as replacement for human cancellous bone, were fabricated by electron beam melting (EBM). Computer aided design (CAD) was applied to design porous structures using the same unit cell with different unit cell sizes from 2.5 to 4 mm, different ligament widths from 600 to 900 μm, and different pore sizes from 1200 to 1800 μm, in order to achieve high porosity of 80% in avoiding the stress shielding effect. In comparison with the CAD designs and the EBM samples, there were minor discrepancies in terms of pore size and ligament width, mainly a result of melting pool. The measured data on the Young's modulus and yield strength of the EBM porous samples can be predicted by the Gibson and Ashby model. All samples with high porosity were found to match well with cancellous bone, with Young's modulus of 2 GPa and yield stress of 31 MPa, effective to diminish the risk of stress shielding effect. For porous EBM sample with high 80% porosity, the work of fracture can increase from 15.9 to 47.6 kJ/m2 with increasing ligament width from 600 to 900 μm.

Validating a prediction modeling tool for left ventricular outflow tract (LVOT) obstruction after transcatheter mitral valve replacement (TMVR).

Demonstrate proof-of-concept validation of a computed tomography (CT) computer-aided design prediction modeling tool to identify patients at risk for left ventricular outflow tract (LVOT) obstruction in transcatheter mitral valve replacement (TMVR). LVOT obstruction is a significant and even fatal consequence of TMVR. From August 2013 to August 2017, 38 patients in 5 centers underwent TMVR with compassionate use of balloon-expandable valves for severe mitral valve dysfunction because of degenerative surgical mitral ring, bioprosthesis, or severe native mitral stenosis from to severe mitral annular calcification. All patients had preprocedural CT scans performed for anatomic screening, intraprocedural TEE and invasive hemodynamics performed. Preprocedural prediction modeling was performed utilizing computer-aided design (CAD) of the neo-LVOT post-TMVR. Post-TMVR CT scans were obtained and compared to pre-TMVR LVOT modeling datasets for validation. All patients underwent successful TMVR without device embolization. Seven of the 38 patients experienced LVOT obstruction, defined as an increase of ≥10 mmHg LVOT peak gradient post-TMVR. Anatomic screening using CT was validated in 20/38 patients as preprocedural predicted neo-LVOT surface area correlated well with post-TMVR measurements (R2 = 0.8169, P < 0.0001). A receiver operating curve curve found a predicted neo-LVOT surface area of ≤ 189.4 mm2 to have 100% sensitivity and 96.8% specificity for predicting TMVR-induced LVOT obstruction. CAD design and CT postprocessing are indispensable tools in predicting LVOT obstruction and necessary for anatomic screening in percutaneous TMVR.

A tool to convert CAD models for importation into Geant4

The engineering design of a particle detector is usually performed in a Computer Aided Design (CAD) program, and simulation of the detector’s performance can be done with a Geant4-based program. However, transferring the detector design from the CAD program to Geant4 can be laborious and error-prone.SW2GDML is a tool that reads a design in the popular SOLIDWORKS CAD program and outputs Geometry Description Markup Language (GDML), used by Geant4 for importing and exporting detector geometries. Other methods for outputting CAD designs are available, such as the STEP format, and tools exist to convert these formats into GDML. However, these conversion methods produce very large and unwieldy designs composed of tessellated solids that can reduce Geant4 performance. In contrast, SW2GDML produces compact, human-readable GDML that employs standard geometric shapes rather than tessellated solids.This paper will describe the development and current capabilities of SW2GDML and plans for its enhancement. The aim of this tool is to automate importation of detector engineering models into Geant4-based simulation programs to support rapid, iterative cycles of detector design, simulation, and optimization.

Living in the Material World

This article explores ways and solutions that could make computer-aided design (CAD) systems help engineers make a better choice of their design. CES Selector is a stand-alone library of material property data that helps engineers screen materials based on design objectives and constraints. The tool is useful for identifying potential materials during the conceptual design phase and when searching for a replacement for a material that is not working out. The MultiFab printer developed by MIT’s Science and Artificial Intelligence Lab enables engineers to print multiple materials at once and build objects whose segments have different properties. Research teams are looking for ways to enable engineers to design a part and the materials that comprise it at the same time, within a single software application. The approach will give engineers tools to customize those materials at the microscale and give them just the right properties for the design. By integrating this into CAD design systems, engineers could alter materials at the microscale to achieve specific physical properties needed for the shapes and structures they design at the macroscale.