Improving Time Study Methods Using Deep Learning-Based Action Segmentation Models

Improving Time Study Methods Using Deep Learning-Based Action Segmentation Models

In the quest for industrial efficiency, human performance within manufacturing systems remains pivotal. Traditional time study methods, reliant on direct observation and manual video analysis, are increasingly inadequate, given technological advancements. This research explores the automation of tim...

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Bibliographic Details
Main Authors: Mihael Gudlin, Miro Hegedić, Matija Golec, Davor Kolar
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Applied Sciences
Subjects:
action segmentation
deep learning
time study
manufacturing processes
Online Access:https://www.mdpi.com/2076-3417/14/3/1185

Internet

https://www.mdpi.com/2076-3417/14/3/1185

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