Nothing Special   »   [go: up one dir, main page]

Alamri et al., 2022 - Google Patents

Predicting the porosity in selective laser melting parts using hybrid regression convolutional neural network

Alamri et al., 2022

View HTML
Document ID
13976850527634803601
Author
Alamri N
Packianather M
Bigot S
Publication year
Publication venue
Applied Sciences

External Links

Snippet

Assessing the porosity in Selective Laser Melting (SLM) parts is a challenging issue, and the drawback of using the existing gray value analysis method to assess the porosity is the difficulty and subjectivity in selecting a uniform grayscale threshold to convert a single slice …
Continue reading at www.mdpi.com (HTML) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/22—Health care, e.g. hospitals; Social work
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/01—Social networking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20—Handling natural language data

Similar Documents

Publication Publication Date Title
Mahmood et al. Artificial neural network algorithms for 3D printing
Wang et al. Effect of porosity on mechanical properties of 3D printed polymers: Experiments and micromechanical modeling based on X-ray computed tomography analysis
Charles et al. Effect of process parameters on the generated surface roughness of down-facing surfaces in selective laser melting
Kurzynowski et al. Effect of scanning and support strategies on relative density of SLM-ed H13 steel in relation to specimen size
Galati et al. Surface roughness characterisation and analysis of the electron beam melting (EBM) process
Pilipović et al. Influence of processing parameters on tensile properties of SLS polymer product
Vrána et al. Selective laser melting strategy for fabrication of thin struts usable in lattice structures
Du Plessis et al. Mechanical properties and in situ deformation imaging of microlattices manufactured by laser based powder bed fusion
Alamri et al. Predicting the porosity in selective laser melting parts using hybrid regression convolutional neural network
Ulbricht et al. Can potential defects in LPBF be healed from the laser exposure of subsequent layers? A quantitative study
Vrána et al. Deviations of the SLM produced lattice structures and their influence on mechanical properties
Bassoli et al. Design for additive manufacturing and for machining in the automotive field
Hartmann et al. Compensation for geometrical deviations in additive manufacturing
Coranic et al. Utilization of optimization of internal topology in manufacturing of injection moulds by the DMLS technology
Zongo et al. Intra-and inter-repeatability of profile deviations of an AlSi10Mg tooling component manufactured by laser powder bed fusion
Galati et al. Finite element simulation of multilayer electron beam melting for the improvement of build quality
Weber et al. The fracture behavior and mechanical properties of a support structure for additive manufacturing of Ti-6Al-4V
Bakradze et al. On the heuristic procedure to determine processing parameters in additive manufacturing based on materials extrusion
Arnold et al. Electron-optical in situ imaging for the assessment of accuracy in electron beam powder bed fusion
Schlicht et al. Inline quality control through optical deep learning-based porosity determination for powder bed fusion of polymers
Pelzer et al. Acquiring process knowledge in extrusion-based additive manufacturing via interpretable machine learning
Çelik et al. Contact-free support structures for the direct metal laser melting process
Zhang et al. Geometry-based radiation prediction of laser exposure area for laser powder bed fusion using deep learning
Dimopoulos et al. Support structures optimisation for high-quality metal additive manufacturing with laser powder bed fusion: a numerical simulation study
Stavropoulos et al. Developing a framework for using molecular dynamics in additive manufacturing process modelling