Publications

In recent years, the way that maintenance is carried out has evolved due to the incorporation of digital tools and Industry 4.0 concepts. By connecting to and communicating with their production system, companies can now gather information about the current and future health of the equipment, enabling more efficient control through a process called predictive maintenance (PdM). The goal of PdM is to reduce unplanned downtimes and proactively address maintenance needs before failures occur. However, it can be challenging for industrial practitioners to implement an intelligent maintenance system that effectively manages data. This paper presents a methodology for developing and implementing a PdM system in the automotive industry, using open standards and scalable data management capabilities. The platform is validated through the presentation of two industry use cases.

The challenges commonly associated with conventional high pressure die casting (HPDC) have led to increased interest in semi-solid metal (SSM) forming processes. In the present study, semi-solid slurries of A356 alloy prepared by the Swirled Enthalpy Equilibration Device (SEED) process were used for manufacturing components with complex shape by using a high pressure die casting machine. The segregation phenomenon and the effect of heat treatment on the microstructure evolution and mechanical properties were investigated. The results showed that the alloy consists of primary spherical a-Al grains, secondary solidified a-Al grains, eutectic Si, iron-rich intermetallic phases and low porosities. The microstructural investigations revealed that the eutectic Si particles underwent fragmentation, spheroidization and coarsening with increasing solution temperature. Furthermore, the solution treatment results in the dissolution of the p-Al8FeMg3Si6 phase and the growth of the b-Al5FeSi phase. The hardening peaks at 170 C could be obtained with ageing for 5 h. Due to both solution and precipitation strengthenings, the yield strength, ultimate tensile strength and hardness of A356 alloy after heat treatment increase significantly compared to those in the as-rheocast state: they reach 266 MPa, 343 MPa and 110 HV0.2, respectively. The analysis of fracture surfaces of rheo-HPDC samples in both the as-rheocast and the heat-treated states revealed a mixed mechanism of dimples and quasi-cleavage. The microstructure inside the part was found to be quasihomogeneous while the segregation phenomenon in different zones of the part is affected by die geometry during the filling process. The results imply that the SEED-HPDC

Virtual reality (VR) sketching has many advantages for product design and tends to be more and more used among designers and non-designers (end-users). Nevertheless, few studies have focused on the skills needed to use VR sketching for non-designers especially VR novices in VR software. This study focuses on identifying the cognitive impact of VR sketching compared to traditional sketching on VR expert and VR novice in an experimental setting. Thirty-one participants composed of VR experts (N = 15) and VR novices (N = 16) completed a mental rotation test and then performed one traditional paper and pencil sketching task and two VR sketching tasks. We also measured the participants’ movements when using the VR sketching. Results show that VR experts perform better than VR novices in VR sketching because training is an essential element for the quality of traditional and VR sketching. Nevertheless, VR novices with previous training in traditional drawing and/or high mental rotation skills will be able to produce good-quality sketches. In addition, the results show that users moving more in the immersive environment performed better quality sketches if the drawing requires more complex shapes. Our results suggest that VR sketching can be complex to use for a part of the population that may be end-users, especially for those with little experience in traditional and VR sketching and with poor visuospatial abilities. We, therefore, advise to check the non-designers’ prior skills, otherwise, it will be necessary to train these users in VR sketching.

As distributed generation increases, it is essential to study its impact on the grid dynamics. This paper focuses on understanding the influence of the emergent technology of Grid-Forming converters on the electromechanical oscillations of the power system. Interactions among synchronous generators and gridforming converters are analyzed thanks to simplified models. These highlight the similarities of both sources, and thus, explain the participation of the converter in the oscillation. They also revealed the differences that justify the damping effect of Grid-Forming converter. This conclusion, obtained with simplified models, is validated with a small-signal stability analysis of a detailed model in the dq0-frame.

The performance and unsteady vortical flows of a 2-bladed cycloidal propeller are investigated using the SST γ �� Reθt transition model, under different pitch-pivot-point and blade camber conditions. Firstly, it shows that the results of the present computations match well with the previous numerical data and experiments, in terms of the instantaneous performance and internal flow structures. Then, due to the moderate propulsive force and low power, the cycloidal rotor with a pitch-pivot-point of x/c = 0.25 maximize the efficiency. Moving the pitching location to the leading edge increases the lift and leads to the earlier flow separation on the blade surface. However, as the pitch-pivot-point shifts to the middle chord, the power of the cycloidal rotor increases dramatically because of the massive flow separation, leading to the degradation of the performance. Simultaneously, the symmetrical profiles, involving NACA0012 and 0015, are recommended due to the wide operation condition with high efficiency. The thick symmetrical and asymmetrical airfoils produce the worst performance due to the large power that is consumed. Furthermore, owing to the change of the rotating speed only, the advance coefficient effect is more obvious than the Reynolds number. When analyzing the performance of the rotating system at any position, one should consider the performance, pressure difference, near-wall flows and forces (lift and drag) of each blade.

In this study, CrN/CrAlN multilayer coating with different periods (Ʌ = 1, 2, 3, 4) were deposited on stainless steel (90CrMoV8) and silicon Si (100) samples by DC magnetron sputtering. The results obtained exhibited that the increasing of the number of periods considerably improves the properties of multilayer coatings. All CrN/CrAlN multilayer coatings have a dense columnar microstructure, and the surface morphology showed a pyramidal shape with nanopores. The coating hardness and Young’s modulus of the CrN/CrAlNmultilayer coating increases with the increase of bilayers number and reach 40 and 392 GPa respectively. Friction coefficient in seawater environment was calculated and it show that the increase in bilayer number decreases friction contact and reduce the friction coefficient. Also, wear resistance improves with increasing interfaces and increasing hardness.

When long parts are machined in forged blanks, the variability of bulk residual stress (RS) fields leads to uncontrolled deformation after machining, requiring manual reshaping. An original hybrid digital twin of forged part is thus proposed to manage the bulk RS variability and reduce part distortion in machining. The behavior model of parts relies both on reduced models of thermomechanical simulations of the forging pro-cess variability, on-line measurements and machine learning from the previous parts deformations. Adaptive machining solutions can then be simulated for a rapid decision-making. The approach was validated on a series of aeronautic forged parts.

This paper addresses the problem of timber board positioning within the log where they were sawn from. The method takes as input log and board end cross-section images. It uses a two-step image matching method based on scale invariant feature transform (SIFT) and normalized correlation coefficient (NCC). In the first step, the scale factor and rotation angle of board end images are estimated from the board images that are correctly identified on the log end image by SIFT. Then, the accurate position of each board within the log end image is achieved by the NCC method. The method has been tested on 70 different log images and the 798 corresponding board images of various visual aspects and coming from three different species (Douglas fir, Norway spruce, and oak). The results fully demonstrate that the proposed method is not only rotation and scale invariant, but also has high accuracy properties.

Background: Patient-specific scapular shape in functional posture can be highly relevant to clinical research. Biplanar radiography is a relevant modality for that purpose with already two existing assessment methods. However, they are either time-consuming or lack accuracy. The aim of this study was to propose a new, more user-friendly and accurate method to determine scapular shape. Methods: The proposed method relied on simplified manual inputs and an upgraded version of the first 3D estimate based on statistical inferences and Moving-Least Square (MLS) deformation of a template. Then, manual adjustments, with real-time MLS algorithm and contour matching adjustments with an adapted minimal path method, were added to improve the match between the projected 3D model and the radiographic contours. The accuracy and reproducibility of the method were assessed (with 6 and 12 subjects, respectively). Findings: The shape accuracy was in average under 2 mm (1.3 mm in the glenoid region). The reproducibility study on the clinical parameters found intra-observer 95% confidence intervals under 3 mm or 3° for all parameters, except for glenoid inclination and Critical Shoulder Angle, ranging between 3° and 6°. Interpretation: This method is a first step towards an accurate reconstruction of the scapula to assess clinical parameters in a functional posture. This can already be used in clinical research on non-pathologic bones to investigate the scapulothoracic joint in functional position.

Titanium alloys, largely used for aeronautical applications, are difficult to machine. High cutting forces, chip serration and important tool wear reflect this poor machinability, limiting productivity. One way of improving the machinability of titanium alloys consists of controlling their microstructure. In the present work, the impact of the microstructure of the Ti5553 alloy on chip formation and cutting forces is investigated. For this purpose, a novel experimental approach is proposed. Orthogonal cutting tests are performed on eight different microstructures, which allows studying the impact of the α-phase fraction as well as the size and shape of α particles. Also, an original post processing method based on machine learning provides chip morphological information from images recorded with two high speed cameras. Such information is completed with the cutting forces measured with a dynamometer. In contrast with commonly used approaches, the proposed method is not limited to the formation of a few segments, but uses the full dataset acquired during a test. The results obtained for the different microstructures indicate that no direct link can be established between the cutting forces and their hardness as minimal cutting forces are obtained for microstructures with an intermediate hardness. For microstructures providing low hardness, high cutting forces result from a significantly thick chip. In opposition, for the microstructures leading to high hardness, an important flow stress generates high cutting forces. This study also suggests that chip morphology is primarily affected by the α-phase fraction while the size and morphology of α-phase particles have little influence.