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48 results found

Asynchronous AM Bench 2022 Challenge Data: Real-time, simultaneous absorptance and high-speed Xray imaging

Data provided by  National Institute of Standards and Technology

The absolute laser absorption was measured simultaneously with X-ray imaging during laser melting of Ti-6Al-4V solid metal. The data included here are the time-resolved absolute absorbed power and the Xray images acquired at the same time, along with timing data for synchronization. Also included is information about the experimental configuration including applied laser power, laser beam spatial profile, and the experimental setup. A text document is included that describes all files.

Tags: additive manufacturing,Laser Welding,

Modified: 2022-07-29

Views: 0

Simantha: Simulation for Manufacturing

Data provided by  National Institute of Standards and Technology

Simantha is a discrete event simulation package written in Python that is designed to model the behavior of discrete manufacturing systems. Specifically, it focuses on asynchronous production lines with finite buffers. It also provides functionality for modeling the degradation and maintenance of machines in these systems. Classes for five basic manufacturing objects are included: source, machine, buffer, sink, and maintainer. These objects can be defined by the user and configured in different ways to model various real-world manufacturing systems.

Tags: discrete-event simulation,manufacturing,production,maintenance,python,

Modified: 2022-07-29

Views: 0

Linear Axis Testbed at IMS Center - Run-to-Failure Experiment 01

Data provided by  National Institute of Standards and Technology

A linear axis testbed at the Center for Intelligent Maintenance Systems (IMS Center) at the University of Cincinnati was run to failure (the detection of backlash) over one year with periodic data collected from an inertial measurement unit (IMU) on the carriage, two triaxial accelerometers on the ball nut, and the controller.

Tags: manufacturing,Industry 4.0,smart manufacturing,linear axis,machine tool,ball screw,backlash,sensor,accelerometer,inertial measurement unit,IMU,error motion,data analysis,monitoring,diagnostics,

Modified: 2022-07-29

Views: 0

Python tools for measuring filament defects in embedded 3D printing

Data provided by  National Institute of Standards and Technology

In embedded 3D printing, a nozzle is embedded into a support bath and extrudes filaments or droplets into the bath. This repository includes Python code for analyzing and managing images and videos of the printing process during extrusion of single filaments. The zip file contains the state of the code when the associated paper was submitted. The link to the GitHub page goes to version 1.0.0, which is the same as the code attached here. From there, you can also access the current state of the code.Associated with: L. Friedrich, R. Gunther, J.

Tags: python,digital image analysis,computer vision,3D printing,additive manufacturing,openCV,

Modified: 2022-07-29

Views: 0

Suppression of filament defects in embedded 3D printing: images and videos of single filament extrusion

Data provided by  National Institute of Standards and Technology

These images, videos, and tables show experimental data, where single lines of viscoelastic inks were extruded into moving viscoelastic support baths. Lines were printed at varying angles relative to the camera, such that videos and images captured the side of horizontal lines, cross-sections of horizontal lines, and the side of vertical lines. Metadata including pressure graphs, programmed speeds, toolpaths, and rheology data are also included.

Tags: 3D printing,additive manufacturing,polymer,viscoelasticity,Herschel-Bulkley,

Modified: 2022-07-29

Views: 0

AM Bench 2022 challenge problem Subcontinuum Mesoscale Tensile Test (CHAL-AMB2022-04-MeTT)

Data provided by  National Institute of Standards and Technology

One additively manufactured (AM) laser powder bed fusion (PBF-L) Inconel 625 mesoscale tensile specimen (gauge dimensions approximately 0.2mm x 0.2 mm x 1mm) was extracted from build AMB2022-CBM-B1 specimen TH1 and tested at room temperature using a quasistatic strain rate of 0.001/s to failure.  Microstructure was measured using x-ray computed tomography (XRCT) and scanning electron microscopy (SEM) techniques on the specimen gauge section or adjacent material.  Large-area electron backscatter diffraction was used to measure crystallographic texture and grain size/morphology of the entire gau

Tags: AM Bench,benchmark,additive manufacturing,metal,mechanical characterization,microstructure characterization,

Modified: 2022-07-29

Views: 0

AM Bench 2022 challenge Macroscale Tensile Tests at Different Orientations (CHAL-AMB2022-04-MaTTO)

Data provided by  National Institute of Standards and Technology

Additively manufactured (AM) laser powder bed fusion (PBF-L) Inconel 625 blocks were built with two different scan strategies: XY and X-only.  96 tensile specimens were extracted from blocks at different tensile axis orientations with respect to the build direction to yield the following conditions: XY scan strategy (0, 30, 45, 60, and 90 degree orientation w.r.t. build direction) and X-only scan strategy (0, 60, 90 degree orientation w.r.t.

Tags: AM Bench,benchmark,additive manufacturing,metal,mechanical characterization,microstructure characterization,

Modified: 2022-07-29

Views: 0

Python tools for OpenFOAM simulations of filament shapes in embedded 3D printing, Version 1.1.0

Data provided by  National Institute of Standards and Technology

In embedded 3D printing, a nozzle is embedded into a support bath and extrudes filaments or droplets into the bath. Using OpenFOAM, we simulated the extrusion of filaments and droplets into a moving bath. OpenFOAM is an open source computational fluid dynamics solver. This repository contains the following Python tools: - Tools for generating input files for OpenFOAM v1912 or OpenFOAM v8 tailored to a conical or cylindrical nozzle extruding a filament into a static support bath. - Tools for monitoring the status of OpenFOAM simulations and aborting them if they are too slow.

Tags: 3D printing,additive manufacturing,polymer,embedded ink writing,embedded 3D printing,bioprinting,rheology,computational fluid dynamics,OpenFOAM,

Modified: 2022-07-29

Views: 0

Macroscale Compression at Different Temperatures and Orientations (CHAL-AMB2022-04-MaCTO)

Data provided by  National Institute of Standards and Technology

This challenge is to predict the macroscopic stress-strain response of compression samples across a range of temperatures taken from the base leg of the IN625 AMB2018-01 build in both the build direction (Z-axis) and a transverse-build direction (Y-axis). The specific temperatures of interest are 298 K, 523 K, and 773 K. The calibration data provided in this dataset corresponds to the build direction compression tests done at 298 K and 773 K.

Tags: AM Bench,benchmark,additive manufacturing,metal,mechanical characterization,

Modified: 2022-07-29

Views: 0

Smart Investment Tool

Data provided by  National Institute of Standards and Technology

This tool calculates metrics for investment analysis documented in NIST Advanced manufacturing Series 200-5. It calculates net present value, internal rate of return, and payback period along with executing sensitivity analysis using Monte Carlo techniques. The tool helps to identify the most economical projects/investments. For instance, it could be used to identify the most economical heating and cooling system or it might be used to rank a set of potential investments.

Tags: net present value,internal rate of return,payback,investment,monte carlo,manufacturing,cost effective,economics,

Modified: 2022-07-29

Views: 0