Showing papers in "Computer-aided Design and Applications in 2019"

A Semi-Automatic Hybrid Approach for Defective Skulls Reconstruction

Abstract: In cranioplasty surgery, achieving an effective aesthetic shape restoration of the cranial vault is the most important issue to ensure a proper outcome in terms of social and psychological benefits for the patient. To date, the most advanced approach uses CT/MRI data to reconstruct, in a pre-operative stage, the 3D anatomy of the defective skull in order to design a patient-specific prosthesis. In the last years, several techniques have been proposed to improve the applicability of such approach in the clinical practice, but the analysis of the related literature shows still open issues, due to the wide anatomical variability and complexity of the craniofacial anatomy that needs to be retrieved. With the aim to overcome the State-of-the-Art drawbacks, a new semi-automatic hybrid procedure for repairing unilateral or quasi-unilateral (i.e. a single defect slightly passing the sagittal plane) cranial defects is presented. The novel approach is hybrid because a surface interpolation for filling the hole is used together with a template-based reconstruction guided by the healthy counterpart. The procedure, being landmark-independent and avoiding any patch adaptation, represents a valid alternative for the existing approaches also in terms of user's burden, requiring less time consuming and less cumbersome operations. In addition, a new evaluating technique able to measure the symmetry of the reconstruction as well as the continuity between patch and healthy bone is proposed to test the procedure performance. Several test cases have been then addressed to prove the effectiveness and repeatability of the proposed procedure in reconstructing large-size defects of the skull.

Smart Maintenance: A Wearable Augmented Reality Application Integrated with CMMS to Minimize Unscheduled Downtime

Abstract: The ultimate goal of maintenance managers in any industrial firms is to maximize the uptime of the production assets and to keep the downtime to a minimum. These factors affect the capability of an industry to meet the production deadline while still ensuring the good quality product at minimum production cost. To realize this objective, effective maintenance method and innovative tool are required. Previous study has shown that the growing complexity of current manufacturing technologies will necessitate the increasing competent and trained personnel to resolve quickly the interruptions that occur in the shop floor. However, an efficient repair operation is sometimes difficult to achieve especially when the dysfunctional machine involves various possible problems and the assignment of skilled technician and resources to attend to the failed equipment requires more than just the information reported by the operator concerning what was not functioning on site. Augmented Reality (AR) as one of the emerging technologies in the framework of Industry 4.0 provides a way to accelerate the maintenance process and to minimize the recommissioning of maintenance work due to limited maintenance information provided by the operator. This paper presents the application of AR integrated with CMMS on the emerging computing platform Hololens to demonstrate the potential of this integration to optimize the pipeline of maintenance procedure in order to boost the profitability and competitive advantage of an industrial firm.

A Methodological Approach for the Design of Composite Tanks Produced by Filament Winding

Abstract: In this paper, an original approach for the virtual prototyping of composite pressure tanks is proposed. The main tests to be conducted for the homologation of the vehicle tank is the burst pressure, which is a quasi-static test. This method aims to reduce the finite element model development time by the integration between the computational software MATLAB and the FEA tool Abaqus. Since the dome shape has fundamental influence on the mechanical performances of the composite pressure vessel, the presented procedure allows the designer to quickly import the suitable dome geometry into Abaqus, without the need of going through CAD software. The first step of the method here reported is the definition of all the geometric and operational parameters necessary to the construction of the dome meridian profile. The second step is to enter those parameters in a MATLAB script, which is able to integrate the dome profile differential equation, to generate the whole tank profile and to import this profile into Abaqus. Once the geometry has been imported, a FE model of the high-pressure vessel can be built and virtual simulations can be performed. This approach could be implemented in a dome optimization process to find which dome meridian profile gives the best tank performances.

On the Role of Geometric Constraints to Support Design Intent Communication and Model Reusability

Abstract: This work was partially supported by the Spanish grant DPI2017-84526-R (MINECO/AEI/FEDER, UE), project "CAL-MBE, Implementation and validation of a theoretical CAD quality model in a Model-Based Enterprise (MBE) context".

Automated Tolerance Analysis of Mechanical Assemblies from a CAD Model with PMI

Abstract: Many tolerance analysis methods, both manual and software-based, are in use today. However, the manual processes are complicated and tedious for complex assemblies as compared to software-based methods. This paper describes three different tolerance analysis methods automated in a software. The procedure starts with translating the geometry of an assembly along with its Product Manufacturing Information (PMI) like GD&T; which serves as the input to the analysis methods: 1D min/max charts, 3D Monte Carlo statistical analysis, and Tmap based worst case and statistical analysis. For an automated system, a full digital thread is required, thus translating the geometry, assembly and tolerance data to an intermediate data structure such as augmented Constraint Tolerance Feature (aCTF) graph is considered. This makes the tolerances analysis modules available for any tolerance problem translated to aCTF format and provides a uniform input to all of automated analysis modules. The analysis software reads the aCTF file and create an output analysis result for each gap of interest, with all the different methods. The results of these analysis methods, on a complex assembly, are compared. The differences can be categorized into these potential sources: variation types, included or omitted, and treatment of assembly constraints in mathematical formulations. In this paper the tolerance problem is defined in Siemens NX and Teamcenter, and the aCTF is translated from the abstract model created in TeamCenter.

An Approach to Improve Technical Drawing using VR and AR Tools

Abstract: In this paper, the authors present the development of 3D interactive AR/VR teaching system from a design-based method to help engineering and product design students improve on critical and complex topics related to TD skills according to an international survey and as part of a broader European funded research project. This work shows that human-centred approaches can improve the understanding of students needs and facilitate the development of AR/VR technology applications for T&L within an international and multidisciplinary team.

A Lightweight Design of Tree-shaped Support Structures for SLM Additive Manufacturing

Abstract: Support structures are used to hold the overhangs of the models and dissipate process heat in the Selective Laser Melting (SLM) processes. However, the support structures are sacrificed afterwards in order to obtain the target 3D models. Therefore, to save both printing time and materials, minimizing the volume of support structures is an effective means. Tree-shaped structure is an effective design for the lightweight design of the support structures. Although existing commercial software such as Autodesk Meshmixer have provided the function of generating tree-supports by manually setting the geometric parameters, the problem of designing a stable tree-support of minimum volume to reduce the material and printing time without sacrificing the printing quality for 3D-printed metal models has not been addressed properly. We propose a combination of an experimental method and a volume minimization framework using a strategy of improved Particle Swarm Optimization (PSO). We carried out a set of experiments to compare our method with traditional “point supports” and the tree-supports module of Autodesk Meshmixer. Simulation and experimental results reveal that our approach is effective in reducing support volume and printing time.

Knowledge Representation Framework Combining Case-Based Reasoning with Knowledge Graphs for Product Design

Abstract: Product design relies on various design knowledge, including explicit design knowledge and tacit design knowledge. This paper aims at issues that the current design knowledge representation methodology lacks scalability and flexibility, and presents a design knowledge representation framework combining CBR with knowledge graphs. Based on the framework, design cases are represented as a set of knowledge graphs. An ontology model for design case representation is proposed. A novel approach to retrieving design cases from knowledge graphs is presented, which uses a design problem query graph instead of keywords to match similar case subgraphs from knowledge graphs. A semantic similarity assessment method based on subgraph similarity is proposed. Finally a case study on knowledge representation for stamping die design is provided.

Comparing Digital Tools for Implementing a Generative System for the Design of Customized Tableware

Abstract: In typical mass customization design processes, designers encode design processes into configurators that are subsequently used by end-users to customize products. Using the case study of ceramic tableware, we explore how to extend the role of designers beyond the deployment of such configurators. In this paper we describe the development of a generative design system for the mass customization of ceramic tableware, focusing on the implementation of generic shape grammar rules encoded into parametric models. The design system enables designers to develop customizable tableware collections, later to be customized using configurators. Two prototypes are presented and compared, each encoding the design system through different programming environments: Grasshopper and Unity.

A Note on Robust Biarc Computation

Abstract: A new robust algorithm for the numerical computation of biarcs, i.e. $G^1$ curves composed of two arcs of circle, is presented. Many algorithms exist but are based on geometric constructions, which must consider many geometrical configurations. The proposed algorithm uses an algebraic construction which is reduced to the solution of a single $2$ by $2$ linear system. Singular angles configurations are treated smoothly by using the pseudoinverse matrix when solving the linear system. The proposed algorithm is compared with the Matlab's routine \texttt{rscvn} that solves geometrically the same problem. Numerical experiments show that Matlab's routine sometimes fails near singular configurations and does not select the correct solution for large angles, whereas the proposed algorithm always returns the correct solution. The proposed solution smoothly depends on the geometrical parameters so that it can be easily included in more complex algorithms like splines of biarcs or least squares data fitting.

Form-Finding and Structural Shape Optimization of the Metal 3D-Printed Multi-Branch Node with Complex Geometry

Abstract: The application of additive manufacturing (AM) technology in architecture and structural engineering has been extended due to recent development of metal 3d printing. In space frame structures, a set of bars is configured in three dimensions, with bars connected by nodes. This article presents two methods to design metal 3d-printed multi-branch nodes to accommodate any number of incident bars at arbitrary angles. Resulting node designs are intended to be smooth and lightweight. A multi-branch node is sketched using the dimensional information of the blank space between the converging bars in a pre-designed space frame and then parameterized by two different approaches to perform structural optimization. The first design method, namely the curve parameter method, which is semi-automated approach, the distances between the control points of the spline curves between node branches and the node branch intersection point are the optimization parameters. For the other method, called fatness parameter method, which is a fast and automated approach, the fatness parameters of the center part of the node and the root radiuses of each branch are chosen as the main parameters of optimization. The optimization procedure is accomplished using a genetic algorithm to minimize the maximum von Mises stress as the objective function subjected to the mass of the node as a constraint function. Finally, functional tests are conducted on 3D printed metal nodes in order to compare the strength and stiffness of the nodes designed by the two form-finding approaches.

Digital Motion Acquisition to Assess Spinal Cord Injured (SCI) Patients

Abstract: The rehabilitation process of patients after spinal cord injury (SCI) is usually based on subjective visual assessment by medical staff of rehabilitation centers. During the process, the medical personnel train patients to manage wheelchair and they learn how to use their sensible body parts in order to have a satisfactory life-style. Furthermore, physiotherapists and physicians have to control patients to prevent wrong postures that could cause further disorders. This paper describes how a low-cost marker-less motion capture system can be exploited to create an objective assessment procedure. Three Microsoft Kinect v2 sensors have been used to track patients using their wheelchairs along a straight path. The three sensors are arranged to optimize the acquisition. Thanks to the collaboration with the medical staff, we identified the set of parameters necessary to monitor patients’ performance. An ad hoc application has been developed to provide the physicians with the right set of data easy readable to assess the patients along the rehabilitation process. The application has been tested involving twenty volunteers. Finally, results reached so far and further developments are summarized and discussed.

Prediction of Motorcycle Seat Styling Based on Grey Modelling (1,1)

Abstract: The process of motorcycle seat styling is a grey system with partially known and partially unknown information and is influenced by various factors. In this study, Grey Modelling (GM)(1,1) is used to predict the style of a motorcycle seat, and the shape features of the seat are extracted via morphological analysis and are parameterized. The process of shape evolution is established, and the modelling characteristics are predicted by GM(1,1). The kansei study is performed using five adjectives describing the seat styles to establish the equation of kansei regression analysis. The regression analysis is employed to modify predictive modelling. A certain brand of motorcycle seats is modelled to analyse and verify the feasibility and scientific applicability of adopting GM(1,1) in predicting motorcycle seat styling, which provided a feasible and effective reference for the motorcycle seat design.

Design for Multi-functional Product by Searching Shareable Functional Components

Abstract: A product with multiple functions can save resources such as material and space compared to single function products. A multi-functional product can be designed through the structural transformation and reorganization of different products. It is a challenge for designers to combine different single-functional products into one to perform multi-functions. This paper proposes a method based on the similarity analysis of flow and function descriptions of different products to form a multi-functional product. A functional element similarity matrix (FESM) is formed first based on the existing products. A component-component similarity matrix (CCSM) is then obtained by combining the functional element-component correlation matrix (FECCM) with FESM. An optimal match of design similarity is searched according to values of CCSM to form the multi-functional product. A product is designed with combined functions of the electric razor and cleanser using the proposed method in a case study.

Feature Recognition for Structural Aerospace Sheet Metal Parts

Abstract: With the advances in the aerospace industry, specialized tools, e.g. specialized modelling tools for aerospace sheet metal, have been developed to help at various stages of the product lifecycle. Although structural sheet metal parts form a significant portion of airplanes, there is no specialized automated feature recognition (AFR) method dedicated to them. AFR provides unparalleled contributions to various tasks in product lifecycle management, e.g. computer aided process planning, data retrieval and model difference identification. Despite the presence of a number of AFR methods for sheet metal parts, none of them are tuned to recognize the design semantics of the aerospace industry. This work proposes the first AFR method to recognize aerospace sheet metal features and design semantics to elevate the level of abstraction of the information from 3D STEP models. The proposed approach is to first preprocess the 3D STEP model in order to classify the topological elements of the boundary model (B rep model) and create relevant novel face sets and subtypes of faces, face boundaries and edges. Then, rule-based steps are used to recognize aerospace sheet metal features. The extracted features are described by their geometry, their relationship with other features and their pertinent parameters. As a result, the engineering semantics of 3D B-rep models of aerospace sheet metal parts are extracted and could be used for many applications like design reuse and model comparison.

A Survey of Immersive Systems for Shape Manipulation

Abstract: Immersive modelling systems have predominantly used non-natural interfaces and devices for shape modification. The new technologies for gesture and speech interaction can provide more familiar interface and reduce the cognitive complexity of current user interfaces of traditional visualization and modelling systems, making it possible manipulating and modifying the shape in a simple and effective manner even by non-expert users. In this paper, we present a survey of existing approaches for immersive shape modelling and manipulation. Current approaches are analyzed according to three characterizing key aspects: input method, supported operations and type of representation of the shape. Finally, the paper briefly introduces our current approach to verify the existence of consistency in hand motions/gestures among different users for 3D modelling tasks in virtual environment, as a first step for the creation of natural interfaces in immersive shape manipulation.

A Framework for Concept Formation in CAD Systems: a Case Study of Japanese Rock Garden Design

Abstract: Designers often identify desirable design typologies and utilize them as building blocks of high-level conceptual frameworks for designing spatial configurations. Each building block can be seen a concept connoting with lower level meanings, which are in turn grounded in sets of spatial relations associated with those meanings. Formalizing this practice will enable to further inform CAD systems regarding the potential meanings of certain spatial configurations for their user. In this research we propose an implementable framework for assigning spatial configurations with meanings in CAD systems, by integrating a CAD environment with an inference engine. The framework is constructed and tested in the context of Japanese rock garden design. Automatic matchings of spatial configurations with conceptual abstractions are presented and interpreted, and generalization as well as future research directions are discussed.

Meshfree CAD-CAE Integration through Immersed B-rep model and Enriched Iso-geometric Analysis

Abstract: The goal of the present study is to develop techniques to enable CAE-CAE integration by immersing B-rep CAD models within a spatial analysis grid. The developed method relies on point classi cation and enforcing boundary conditions using signed algebraic level sets and Enriched Isogeometric Analysis (EIGA) respectively. In EIGA, the boundaries as well interfaces are explicitly represented by lower-dimensional spline entities with degrees of freedom corresponding to the enrichment directly speci ed on the control points of the boundary. The eld approximations of the underlying domain are enriched with the boundary conditions and blended with domain eld using distance from the boundary. Signed algebraic distance eld is used as a measure of distance and the point classi cation problem is solved as a by-product. The analysis is carried out directly on the B-rep surfaces created by the CAD software without further generating volumetric discretization. We demonstrate good convergence behavior of the proposed method through a patch test. Several numerical examples are included as a demonstration of the method.

An Approach of Rapid Tooling for Scalp Cooling Cap Design

Abstract: This Innovate UK funded research studies the design, development and integration of a replicable mass-manufacturable process for scalp cooling caps using 3D anthropometric human head data assisted by Selective Laser Sintered tooling (SLS), and implementation of Additive Manufacturing (AM) in silicone manufacturing for chemotherapy-induced hair loss prevention. This research also consists of how 3D digital technologies including 3D scanning, 3D modelling & virtual analysis, AM and Rapid Tooling (RT) can be effectively used in prototyping and low volume manufacturing of sheet silicone forming for creating complex geometry with channels where traditional tool making process cannot be applied.

Systematic Support of Learning from Errors and Negative Knowledge Development in MCAD Education: Empirical Analysis of Student Feedback

Abstract: To address some of the shortcomings of the traditional approach to CAD education in relation to the increasingly complex and highly competitive global labor markets, while also taking advantage of recent developments in educational research and cognitive science related to how students learn, a novel approach to improving CAD education has been developed and implemented. The approach integrates negative knowledge and learning from errors as crucial elements in combination with traditional teaching methods (positive knowledge) and formative assessment/feedback. To examine different facets of teaching/learning-related phenomena aimed at providing grounds for improving learning outcomes achieved within a recently restructured MCAD course, empirical research was conducted. In this paper, the results of that empirical research are presented and discussed in regard to learning experience and self-evaluated competency development. The results and insight gained herein are based on student feedback from a set of over 700 questionnaires collected and analyzed using a multi-method approach.

Implementation of Low-end Disruptive Innovation based on OTSM-TRIZ

Abstract: Abstract. Low-end disruptive innovation has its own unique characteristics to develop product for simplicity, less cost and ease of use with maintained reliability and efficiency of the existing product. Disadvantaged enterprises can use it to attract a large number of low-end users with small investment to explore the new market. At present, the process of the low-end disruptive innovation based on classical TRIZ lacks quantitative solutions of multiple contradictions. In this research, combined with the analytic hierarchy process and Floyd-Warshall algorithm, a quantitative model of the low-end disruptive innovation is proposed based on the OTSM-TRIZ model. The proposed method is verified by an innovative case of tire breaker.

Multi-objective Aesthetic Design Optimization for Minimizing the Effect of Variation in Customer Kansei

Abstract: Due to maturation of science and technology, companies are required to differentiate their products in terms of subjective qualities such as aesthetics whose evaluation depends on customer kansei instead of objective qualities such as performance, function and cost. In the field of kansei engineering, various methods that design products aesthetics fitted to customer kansei have been researched, but diversity of customers’ kansei is becoming a big issue in those researchs. Industrial products are in general designed and sold for a huge number of customers, not a single customer. Due to diversity of their kansei, that they may receive completely different impressions or have different preferences from the same product. As a result, it becomes quite difficult to design products that satisfy all customers. To overcome such difficulty, this paper proposes a new method for designing product aesthetics that give the same / similar impressions to all customers even if their kansei is diverse. To achieve this, the proposed method is based on the concept of robust design. In particular, customers evaluate existing products in questionnaire investigation. Response surfaces that approximately represent the relationships between customer’s impressions received from existing products and their aesthetic elements are then calculated for each customer. Sum of squares of the difference between target impression scores and estimated ones of a design candidate is calculated for each customer as a utility. Optimal design parameters that minimize both mean and variance of all customers’ utility are finally explored by using multiobjective genetic algorithm. In the case study, the proposed method was applied to artificially generated questionnaire results in which the variation in customer kansei is quantitatively controlled. The results revealed that the proposed method can design products that keep low the effect of the variation in customer kansei while achieving a design goal.

A boolean method to model knit geometries with conditional logic for additive manufacturing

Abstract: As additive manufacturing (3D printing) technology becomes increasingly mainstream, new tools are required to enhance creative endeavors in disciplines such as fashion design, which have been slow to embrace digital technologies and computer-aided design software. Additionally, new techniques are required based on an understanding of the limitations of common desktop extrusion-based 3D printers, with 2.5D printing presenting new opportunities to rapidly produce complex forms, such as fashion, which can be assembled by hand as a hybrid approach to digital manufacturing. This paper presents a parametric system through which a new type of digitally fabricated, hand-assembled knit can be customized using a constrained selection of interactive controls. Novice users may rapidly iterate a pattern of loops and floats at a scale matching their Fused Deposition Modeling (FDM) 3D printer, creating a series of knit courses which can be assembled into a textile of expandable dimensions. More advanced users may modify the geometry or logic of the system, building new forms of knits that could not be manufactured through traditional means. This paper will guide designers through the process of developing a new typology of textile appropriate for production on ubiquitous FDM machines, following a workflow from 2D to 2.5D to 3D. Examples were printed at various scales and contribute to discourse on customization, parametric design and visual programming languages for additive manufacturing.

Developing Narrative Diagrams for Algorithmic Modeling of Architectural Parametric Design

Abstract: From diagrams of buildings to diagrams of algorithms, architects rely on diagrams to bridge abstract intentions to generating of building forms. This paper proposes an approach for generating narrative diagrams which can visually describe what design intentions are reached, and how the diagrams are generated. In order to communicate with a broader public than just AEC professionals, this paper proposes a visual strategy for manipulating and generating narrative diagrams that tell the design stories in parametric architectural design. By providing editable clusters of topological algorithms for recognizing and reasoning spatial relationships among geometric entities, this paper aims to help architects to represent design intentions within the algorithmic process of parametric design.