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In this study, we investigated the fabrication, properties, and sensing applications of TiO2 nanotubes. A pure titanium metal sheet was used to demonstrate how titanium dioxide nanotubes can be used for gas-sensing applications through the electrochemical anodization method. Subsequently, X-ray diffraction indicated the crystallization of the titanium dioxide layer. Scanning electron microscopy and transmission electron microscopy then revealed the average diameter of the TiO2 nanotubes to be approximately 100 nm, with tube lengths ranging between 3 and 9 µm and the thickness of the nanotube walls being about 25 nm. This type of TiO2 nanotube was found to be suitable for NO2 gas sensor applications. With an oxidation time of 15 min, its detection of NO2 gas showed a good result at 250 °C, especially when exposed to a NO2 gas flow of 100 ppm, where a maximum NO2 gas response of 96% was obtained. The NO2 sensors based on the TiO2 nanotube arrays all exhibited a high level of stability, good reproducibility, and high sensitivity. [ABSTRACT FROM AUTHOR]

This paper presents a 3D tolerance analysis approach for linear dimensions applied to planar faces in an assembly. The assembly variations are generated and visualized as an explicit geometrical stack-up of the component variations using the solid modeller Solidworks®. The feature variations are obtained by adapting the geometric solid model of each component, either by offsetting the target planar face or by tilting it within the tolerance zone. A concept of Oriented Minimum Bounding Box (OMBB) is introduced to generate individual component variations with any generalized shape of the target planar face. The analysis of the OMBB extents, the tilting angles and the corresponding pivot points has revealed symmetry in these data. Rigorous mathematical formulations have been implemented in this study to handle the general case of large and small displacements. An approach is suggested to evaluate the functional dimensions, the target face's centroid and normal for each assembly variation. Functional dimensions of the assembly variations obtained by the software '3DCS Variation Analyst' are found to deviate from those obtained by the proposed approach by up to 40% of the assembly tolerance size. 3DCS tool has also failed to detect out-of-specification assembly variations, which were identified by the proposed approach. [ABSTRACT FROM AUTHOR]

The additive manufacturing (AM) field is rapidly expanding, attracting significant scientific attention. This family of processes will be widely used in the evolution of Industry 4.0, particularly in the production of customized components. However, as the complexity and variability of additive manufacturing processes increase, there is an increasing need for advanced techniques to ensure quality control, optimize performance, and reduce production costs. Multiple tests are required to optimize processing variables for specific equipment and processes, to achieve optimum processing conditions. The application of digital twins (DTs) has significantly enhanced the field of additive manufacturing. A digital twin, abbreviated as DT, refers to a computer-generated model that accurately depicts a real-world object, system, or process. A DT comprises the complete additive manufacturing process, from the initial conception phase to the final manufacturing phase. It enables the manufacturing process to be continuously monitored, studied, and optimized in real time. DT has emerged as an important tool in the additive manufacturing industry. They allow manufacturers to enhance the process, improve product quality, decrease costs, and accelerate innovation. However, the development of DT in AM is an iterative and continuous process. It requires collaboration between domain experts, data scientists, engineers, and manufacturing teams to guarantee an accurate representation of the process by the digital twin. This paper aims to provide a comprehensive analysis of the current state of DT for additive manufacturing, examining their applications, benefits, challenges, and future directions. [ABSTRACT FROM AUTHOR]

Computer-aided design (CAD) has become an integral part of engineering education, particularly for those studying mechanical engineering. By providing practical skills that are highly valued in the engineering industry, proficiency in CAD systems enhances students' employability. Generally, CAD systems provide students with the tools and knowledge necessary to excel in their engineering education and future careers. In order to help teachers to give the best training to their students and to make the right evaluations, an automatized tool is needed to support the evaluation of CAD models during training sessions. After an extensive bibliographical search, this paper proposes a CAD Model Automatized Assessment (MAA) Tool for mechanical courses called the CAD MAA Tool. This tool is mainly based on a developed model that takes into account different aspects of modeling, such as geometric, feature-based, and parametric modeling. To correctly evaluate a given part compared to a reference one, the proposed model uses different coefficients fixed by the teacher according to their teaching strategies or course objectives. [ABSTRACT FROM AUTHOR]

Fused Deposition Modelling (FDM) is one of the layer-based technologies that fall under the umbrella term "Additive Manufacturing", where the desired part is created through the successive layer-by-layer addition process with high accuracy using computer-aided design data. Additive manufacturing technology, or as it is commonly known, 3D (three-dimensional) printing, is a rapidly growing sector of manufacturing that is incorporated in automotive, aerospace, biomedical, and many other fields. This work explores the impact of the Additive Manufacturing process on the mechanical proprieties of the fabricated part. To conduct this study, the 3D printed tensile specimens are designed according to the ASTM D638 standards and printed from a digital template file using the FDM 3D printer Raise3D N2. The material chosen for this 3D printing parameter optimization is Polylactic acid (PLA). The FDM process parameters that were studied in this work are the infill pattern, the infill density, and the infill cell orientation. These factors' effects on the tensile behavior of printed parts were analyzed by the design of experiments method, using the statistical software MINITAB2020. [ABSTRACT FROM AUTHOR]

Increasing product diversity, rising performance and reliability demands, and industry competitiveness are some of the many reasons that increase the need of more complex product designs in almost all sectors. The complexity of parts increases with their geometrical features to be designed and manufactured. Researchers agreed that it can be qualitatively evaluated and expressed with terms like low, medium, high, and very high. However, it might be evaluated differently, depending on the designer's considerations, domain and experience. Quantitative evaluation of a design complexity is, therefore, indispensable and expedites the decision-making about the selection of the manufacturing process. However, having a well-defined and unambiguous metric for quantitative evaluation is challenging. Most of existing metrics are not objective and are only valid for their specific applications. This paper presents a novel, unambiguous, and generalized approach for shape complexity evaluation. The developed metric enables determining if the selected part should be produced by conventional methods such as machining, or by non-conventional methods such as additive manufacturing. In order to ensure its objectivity, only geometrical features have been considered. The metric was tested through 25 different part designs of varying complexity. The investigations showed an accordance between the qualitatively evaluated shape and the calculated complexity factor. Also, the comparison of the results with other metrics showed the weakness of the latter and the efficiency and reliability of our metric. The results have been also validated by 50 experts from 23 countries. Based on these results, a threshold between machining and additive manufacturing is fixed allowing an easier decision-making. [ABSTRACT FROM AUTHOR]

Additive Manufacturing (AM) has emerged as an innovative technology that gives designers several advantages, such as geometric freedom of design and less waste. However, the quality of the parts produced is affected by different design and manufacturing parameters, such as the part orientation, the nozzle temperature and speed, the support material, and the layer thickness. In this context, the layer thickness is considered an important AM parameter affecting the part quality and accuracy. Thus, in this paper, a new adaptative slicing method based on the cusp vector and the surface deviation is proposed with the aim of minimizing the dimensional defects of FFF printed parts and investigate the impact on the dimensional part tolerancing. An algorithm is developed to automatically extract data from the STL file, select the build orientation, and detect intersection points between the initial slicing and the STL mesh. The innovation of this algorithm is exhibited via adapting the slicing according to the surface curvature based on two factors: the cusp vector and the surface deviation. The suggested slicing technique guarantees dimensional accuracy, especially for complex feature shapes that are challenging to achieve using a uniform slicing approach. Finally, a preview of the slicing is displayed, and the G-code is generated to be used by the FFF machine. The case study consists of the dimensional tolerance inspection of prototypes manufactured using the conventional and adaptive slicing processes. The proposed method's effectiveness is investigated using RE and CMM processes. The method demonstrates its reliability through the observed potential for accuracy improvements exceeding 0.6% and cost savings of up to 4.3% in specific scenarios. This reliability is substantiated by comparing the resulting dimensional tolerances and manufacturing costs. [ABSTRACT FROM AUTHOR]

Limb disability is a frequent healthcare problem, especially for patients in primary care. Orthotic treatment has become the most common practice for either rehabilitation or permanent assistance, due to the emergence of 3D scanning and 3D printing technologies. A CAD model rebuilt from captured data is a key step in the rapid prototyping process of customized orthoses. An accurate and robust surface reconstruction technique remains a research challenge, aiming for a well-fitting design and the patient's comfort. Thus, this paper presents of a new 3D curve-based reconstruction algorithm to obtain a precise 3D surface of an orthotic device from a scanned body part. Numerical experiments of two orthosis design case studies are shown to evaluate the reliability and accuracy of the proposed approach compared to other reconstruction methods. [ABSTRACT FROM AUTHOR]

The optimum structural characteristics of lamination materials used in the fabrication of prosthetic and orthotic parts were investigated in this work. Optimization was chosen based on high yields, ultimate stresses, and bending stress properties. The ideal materials were determined through the use of an RSM (response surface methodology) which considers three factors: Perlon reinforcement, a layer of glass fiber, and the percentage of titanium nanoparticles combined with the matrix laminating resin. The RSM approach suggests thirteen samples by manipulating two variables: the Ti nano percentage and the number of Perlon layers. Laminating materials, defined by RSM methods and treated with a vacuum system, were submitted to a series of tests. The ideal lamination material was compared with the laminations from the initial study through the use of tensile, flexural, and fatigue testing according to ASTM standards. Tests carried out using version 10.0.2 of Design Expert software showed that, compared with the 12 other laminations, the one with 10 Perlon layers and 0.75 percent Ti nano had the highest overall yield and ultimate and bending loads. Fatigue eventually showed that stamina tension constraints were applied for optimal lamination, compared to ten Perlon lamination layers. We additionally tested the fatigue life of the best material and compared it with the available materials used at prosthetics and orthotics centers. [ABSTRACT FROM AUTHOR]

Orthoses and prostheses were Chosen and laminated based on their high Yield, ultimate stresses, bending stresses, and fatigue limit. Response Surface Methodology (RSM) was utilized to find the best values for two parameters reinforcement perlon fiber and percent of Titanium Nanoparticle coupled with the matrix resin during optimization. The response surface methodology combined the expertise of mathematicians and statisticians to construct and analyze experimental models. Using this method, we identified 13 different lamination samples comprising a wide range of perlon number and Ti nano Wt% in their Perlon layer composition. All lamination materials defined by RSM methods and produced by a vacuum system were subjected to a battery of tests, with fatigue tests performed on the ideal laminating material in contrast to laminations created in the first study (Tensile test, Bending test, and Fatigue tests according to the ASTM D638 and D790 respectively). In comparison to the other 12 laminations tested using Design Expert version 10.0.2, the lamination with ten perlon layers and 0.75 percent Ti nano proved to be the strongest overall in terms of Yield, ultimate, and bending loads. This study used composite materials and titanium nanoparticles to characterize and fabricate ankle foot orthoses. Strength in bending should amount to about 70 MPa, around 85 MPa in tensile tension. Two empirical quadratic equations for the models of peak bending strength and maximum tensile stress with 95% confidence were created using the response surface approach and analysis of variance within the design of experiments software. [ABSTRACT FROM AUTHOR]

Basically, augmented reality (AR) technology grants innovative ways so as to manipulate and visualize a three-dimensional (3D) model of an object through superimposing computer-generated images onto another object interactively. Being able to interact in real-time with digital and spatial information offers further chances in order to manipulate medical data efficiently and easily. In fact, surgeons encounter multiple challenges handling digital patient data during surgical interventions. Multiple techniques are invested in order to visualize the operative areas, as for example fluoroscopy and ultrasound methods. The latter display certain deficiencies. Therefore, the AR technique can stand for a good candidate in order to project a 3D model of a target organ into the surgeon's perspective and view field so as to enhance the efficiency and accuracy of the medical intervention intraoperatively. The basic target of this paper is to simulate a generated biomechanical model of the liver organ and visualize its deformations through the use of an AR headset during the open surgery. The proposed approach is validated by the use of acquired CT scans of a human liver organ. [ABSTRACT FROM AUTHOR]

Over the last decades, facing the blooming growth of technological progress, interest in digital devices such as computed tomography (CT) as well as magnetic resource imaging which emerged in the 1970s has continued to grow. Such medical data can be invested in numerous visual recognition applications. In this context, these data may be segmented to generate a precise 3D representation of an organ that may be visualized and manipulated to aid surgeons during surgical interventions. Notably, the segmentation process is performed manually through the use of image processing software. Within this framework, multiple outstanding approaches were elaborated. However, the latter proved to be inefficient and required human intervention to opt for the segmentation area appropriately. Over the last few years, automatic methods which are based on deep learning approaches have outperformed the state-of-the-art segmentation approaches due to the use of the relying on Convolutional Neural Networks. In this paper, a segmentation of preoperative patients CT scans based on deep learning architecture was carried out to determine the target organ's shape. As a result, the segmented 2D CT images are used to generate the patient-specific biomechanical 3D model. To assess the efficiency and reliability of the proposed approach, the 3DIRCADb dataset was invested. The segmentation results were obtained through the implementation of a U-net architecture with good accuracy. [ABSTRACT FROM AUTHOR]

The main objective of this experimental investigation is to examine favourable machining conditions by utilising fewer resources of machining industries for the techno-economical and ecological benefits. The machining operations are performed in turning SS 304 using coated carbide tool inserts under dry, water-soluble cutting fluid solution in the form of flood cooling and small-quantity lubrication (SQL) conditions by employing a newly formed micro-jet for a comparative classical chips study and analysis. The machining experiments are conducted in turning by a 25 kW precision CNC lathe with a special arrangement of micro-jets into the machining zone. Machining speeds and feed rates are varied under dry, micro-jet, and flood cooling conditions and their effects are studied on the type of chips and their morphology, chip reduction coefficient (ξ), and chip shear plane distance (d). The effect of machining environments on tool health conditions (such as BUEs, tool-edge chipping, and edge breaking) is examined for the inferences. In the range of low-speed machining (less than 600 m/min), metal cutting seems easier in flood cooling conditions, but it imposes more unfavourable effects (such as edge chipping and edge breaking) on the ceramic cutting tool's health. On the other hand, the dry machining condition shows a favourable performance for a ceramic cutting tool. The optimum machining condition is found in the micro-jet SQL by the analysis of experimental data and observation results for the tool and work combination. The analysis of the results is carried out by the response surface methodology (RSM) and artificial neural network (ANN). The ANN model is found to be more accurate than RSM. The aspects of effective green machining are emphasised. [ABSTRACT FROM AUTHOR]

During the design stage, the ideal simulation and visualization of the mechanical assemblies behavior require the modeling of parts with dimensional and geometrical defects. However, the deviations caused by parts deformations can generate an important difference between the ideal assembly and the real product. In this regard, this paper proposes a tolerance analysis method of CAD assemblies considering non-rigid joints between parts with defects. The determination of realistic rigid components with dimensional and geometrical defects is based on the worst case tolerancing approach and the Small Displacement Torsor (SDT) parameters. The Finite Element (FE) computation is executed to determine deformations of realistic non-rigid part models under external loads. Sub-algorithms to define non-rigid joints between realistic parts are developed. The tolerance analysis is established using the realistic CAD assembly. A case study is presented to evaluate the proposed model. [ABSTRACT FROM AUTHOR]

Nowadays, 3D CAD systems (Computer Aided Design) are extremely important in many sectors related to the modern industry. The wide range of modelling software and their increasingly advanced functionalities have considerably extended the uses of CAD models. Indexing and searching in huge databases for the purpose of reusing a 3D CAD model is still a big challenge for both the industrial and for scientific research fields. This highlights the need for an effective approach that provides accurate results within an acceptable time-frame and that takes into account the re-usability of the model regardless of its modelling software. From this perspective, this paper proposes a new data-intensive approach for the detection of reusable CAD models, similar to a reference one. The proposed method is based on the probabilistic graphical model Bayesian network. The suggested approach is mainly based on two phases: (1) first, the construction of a Bayesian network of models (MBN). The developed network is based on an index of association calculated according to the common reusable sub-parts between the candidate models. (2) Then, the detection of reusable models (through the indirect similarity extracted from the built MBN) based on the graph structure and the probabilistic inference. [ABSTRACT FROM AUTHOR]

The manufacturing industries must correctly and quickly predict the production cost of a new product to face increasingly stiff competition. The proper reuse of the company's know-how guarantees the correct estimation of the manufacturing cost while respecting the required quality. The use of the Digital Mock-Up (DMU) leads to the rapid determination of the manufacturing cost from the CAD data. Thus, this paper describes an approach to estimate manufacturing cost and to produce the machining strategy of a new model by the reuse of the manufacturing expertise, acquired during old projects. The new product closely related and similar to a previous design must be found. Thus, a comparison tool is developed, in manufacturing semantics. This tool quantifies the similarity between the query CAD model and company database. The tolerance values as well as geometrical and topological parameters are considered in the similarity calculation. Feature data modelling under a standard structure is used. Two cost computation methods are proposed. Consequently, the estimated cost and machining strategy, of the studied model, are deduced. A case study is presented to show the feasibility of the proposed approach to estimate the cost and to suggest a machining strategy during the design phase. [ABSTRACT FROM AUTHOR]

Engineering changes management has become a crucial task in product lifecycle management. Indeed, the good management of the modifications enables saving both money and time concerning the important competition existing in the market where the majority of mechanical products are complex systems and generally composed of sub-systems. Computer-aided design (CAD) is the use of computer systems to aid in the creation, the modification, the analysis, and/or the optimisation of a design. Actually, CAD softwares are used to increase the productivity of the designer and improve the quality of design. Therefore, researchers aim to improve those CAD systems in order to increase their efficiency and facilitate the designer task. Consequently, the objective of the authors is to develop a model to help the user to manage modifications affecting a simple part of an assembly CAD model, before propagating it to the whole assembly model. Thus, as a first step, the initial and the modified version of a considered part have to be compared in order to detect the affected features, pick up the topologic and geometric modifications, and then calculate the ratio of modification. This ratio measures the importance of changes that affect the initial part, and it will be useful later on while propagating this change. [ABSTRACT FROM AUTHOR]

For several years, researchers have focused on Reverse Engineering techniques, which generate the geometric model of an object from a point set, a mesh, a triangulation, etc. These data are provided by 3D scanners, three-dimensional Coordinate Measuring Machines, finite elements results, deformed meshes, etc. In this field, the reconstruction of the Computer Aided Design (CAD) model from a deformed mesh remains a challenge. This CAD model can be used in order to visualize 3D objects that were scanned and approximate their shapes by mathematical formulations. It can represent the geometric support for many other activities (analysis, manufacturing, assembly, etc.). In this paper, we propose a method to rebuild the CAD geometry model from a deformed mesh. This approach is based on the B-Spline formulation for rebuilding the CAD model entities (faces, edges and vertices) from those extracted from the deformed mesh (triangulations, arcs, nodes). The reconstruction is based on the Levenberg Marquardt algorithm as a method for the interpolation/approximation. An illustration of the developed method is proposed discussed at the end of this paper. [ABSTRACT FROM AUTHOR]

The dimensional and geometric inspection of non-rigid mechanical parts still presents a real challenge to the automotive and aerospace industry. Much research has been devoted to automating the inspection of these parts in order to eliminate the cost of specialized fixtures that cause productivity problems for manufacturers. A registration step between the part'31s nominal CAD model and its corresponding scan is required for an automatic inspection. The coherent point drift (CPD) is one of the existing algorithms for registration and is widely used in imaging applications. It has been recently adapted with regard to the mechanical field for the fixtureless dimensional inspection problems of deformable bodies, notably the IDB-ACPD algorithm. In this paper, an improvement of the optimization phase by reformulating the objective function of the algorithm is put forward. A correction matrix associated with the importance of each measurement point, and therefore with the local rigidity of the part during the registration operation, was introduced and incorporated. In addition, the measurement points representing the same rigidity have been clustered based on mechanical metrics using a fuzzy c-mean algorithm. The effectiveness of the proposed approach is demonstrated on different case studies from the transport industry and the results provide an improved registration of non-rigid parts leading to better dimensional and geometric errors detection. [ABSTRACT FROM AUTHOR]

The improvement of the simulation process requires an integration of the design and analysis models. There are two essential tasks in the design analysis process: (i) computer-aided design (CAD) which provides the geometric description of the model and (ii) the finite element method (FEM) used for mechanical behaviour simulations. The interoperability between these two tasks reduces costs and improves product quality through the acceleration of design analysis loops. Our activity fits into this research orientation by providing a method to link the FE analysis and the CAD model. This is done by reconstructing the CAD model from the FE analysis results (deformed mesh). This paper proposes a method to update the CAD geometry from the deformed mesh. This approach allows for rebuilding the CAD model after analysis by extracting geometric information from the deformed mesh. An illustration of the developed method is discussed at the end of this paper. [ABSTRACT FROM AUTHOR]

In order to improve digital mock-up, a tolerancing phase should be integrated in the geometric models. However, in CAD software, tolerances are represented by annotations, which are neglected as well as the tolerance impact. Thus, the system malfunction is generated. For these reasons, in this paper a tolerancing phase is integrated in the numerical model to form a realistic model, where worst case configurations of assemblies are determined from the tolerances assigned to the nominal model. The proposed model incorporates tolerances on CAD models in the case of planar face, cylindrical face and planar face with non quadratic loop. In addition, the model ability to respect the maximum material condition (MMC) and the requirement of datum priority order in the CAD models is shown. Finally, functional requirement of a linear guide mechanism is inspected by using the proposed model. [ABSTRACT FROM AUTHOR]

Current researches aim at the best control and integration of activities related to the product life cycle. That's why integrating the simulation of assembly/disassembly operations in development process of mechanical product is an increasing aspect of CAD (computer aid design) and VR (virtual reality) research. In order to help designer in early stages in analyzing accessibility and disassembly aptitude of components this paper develops an automatic disassembly methodology of CAD models. This methodology allows identifying of geometric entities of parts connection. Deduced from connection entities parameters, authorized movement directions of components are verified by interference tests. If tested directions are valid, disassembly sequences are generated and assembly state is updated. Then target, time and disassembled pieces number are saved to be used for computing optimal sequences. Using the application programming interfaces (API) of SolidWorks and Opencascade development platform, the developed methodology was applied to an example illustrated in this paper to show its efficiency. [ABSTRACT FROM AUTHOR]