Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning
In the modern manufacturing landscape, optimizing productivity is a paramount challenge, particularly in dynamic, non-concentrative environments where human activities are diverse and complex. Accurately monitoring and analyzing worker behavior is crucial for enhancing manufacturing processes,...
Saved in:
Main Author: | Goh, Ching Pang |
---|---|
Format: | Article |
Language: | English |
Published: |
INTI International University
2023
|
Subjects: | |
Online Access: | http://eprints.intimal.edu.my/1898/1/joit2023_28.pdf http://eprints.intimal.edu.my/1898/ http://ipublishing.intimal.edu.my/joint.html |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Diminish muscle activity by changing an anthropometry data with appropriate workstation among workers in aerospace manufacturing industry
by: Seri Rahayu , Kamat, et al.
Published: (2014) -
Experimental and numerical analysis of deep drawing process
by: Mohamad Nazrin Kooy, Mohd Daniel Kooy
Published: (2010) -
Musculoskeletal disorders among offshore-structure fabrication yard workers
by: Ch’Ng Emily, Huey Ling
Published: (2010) -
Experimental study of formability of sheet metal in deep drawing process
by: Muhammad Safwan, Ismail
Published: (2011) -
On-line analysis of out-of-control signals in multivariate manufacturing processes using a hybrid learning-based model
by: Salehi, Mojtaba, et al.
Published: (2011)