AIMC Topic: Manufacturing Industry
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Recognition of industrial machine parts based on transfer learning with convolutional neural network.
PloS one
Jan 28, 2021
As the industry gradually enters the stage of unmanned and intelligent, factories in the future need to realize intelligent monitoring and diagnosis and maintenance of parts and components. In order to achieve this goal, it is first necessary to accu...
Industry 4.0 Lean Shopfloor Management Characterization Using EEG Sensors and Deep Learning.
Sensors (Basel, Switzerland)
May 18, 2020
Achieving the shift towards Industry 4.0 is only feasible through the active integration of the shopfloor into the transformation process. Several shopfloor management (SM) systems can aid this conversion. They form two major factions. The first incl...
Prediction of formation force during single-point incremental sheet metal forming using artificial intelligence techniques.
PloS one
Aug 22, 2019
Single-point incremental forming (SPIF) is a technology that allows incremental manufacturing of complex parts from a flat sheet using simple tools; further, this technology is flexible and economical. Measuring the forming force using this technolog...
Automatic detection and classification of manufacturing defects in metal boxes using deep neural networks.
PloS one
Nov 9, 2018
This paper develops a new machine vision framework for efficient detection and classification of manufacturing defects in metal boxes. Previous techniques, which are based on either visual inspection or on hand-crafted features, are both inaccurate a...
Ubiquitous Robotic Technology for Smart Manufacturing System.
Computational intelligence and neuroscience
Jun 30, 2016
As the manufacturing tasks become more individualized and more flexible, the machines in smart factory are required to do variable tasks collaboratively without reprogramming. This paper for the first time discusses the similarity between smart manuf...
An Integrated MCDM Model for Conveyor Equipment Evaluation and Selection in an FMC Based on a Fuzzy AHP and Fuzzy ARAS in the Presence of Vagueness.
PloS one
Apr 12, 2016
The conveyor system plays a vital role in improving the performance of flexible manufacturing cells (FMCs). The conveyor selection problem involves the evaluation of a set of potential alternatives based on qualitative and quantitative criteria. This...
Hand-Eye Calibration in Visually-Guided Robot Grinding.
IEEE transactions on cybernetics
Oct 26, 2015
Visually-guided robot grinding is a novel and promising automation technique for blade manufacturing. One common problem encountered in robot grinding is hand-eye calibration, which establishes the pose relationship between the end effector (hand) an...
Ergonomic intervention on a packing workstation with robotic aid -case study at a furniture manufacturing industry.
Work (Reading, Mass.)
Jan 1, 2020
BACKGROUND: Several risk factors among packing lines workers can lead to Work-related Musculoskeletal Disorders (WRMSD) occurrence. Foreseeing WRMSD prevention and productivity increase, some furniture manufacturing industries have been investing in ...
Development of an automatic classifier for the prediction of hearing impairment from industrial noise exposure.
The Journal of the Acoustical Society of America
Apr 1, 2019
The ISO-1999 [(2013). International Organization for Standardization, Geneva, Switzerland] standard is the most commonly used approach for estimating noise-induced hearing trauma. However, its insensitivity to noise characteristics limits its practic...
Phytoremediation of palm oil mill secondary effluent (POMSE) by Chrysopogon zizanioides (L.) using artificial neural networks.
International journal of phytoremediation
May 4, 2017
Artificial neural networks (ANNs) have been widely used to solve the problems because of their reliable, robust, and salient characteristics in capturing the nonlinear relationships between variables in complex systems. In this study, ANN was applied...
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