Prediction of Hotspots in Injection Moulding by Using Simulation, In-Mould Sensors, and Machine Learning

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Original language	Undefined/Unknown
Title of host publication	2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)
DOIs	https://doi.org/10.1109/codit58514.2023.10284132
Publication status	Published - 3 Jul 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

@inproceedings{8e4b10e324c341ddb761ad199a177578,

title = "Prediction of Hotspots in Injection Moulding by Using Simulation, In-Mould Sensors, and Machine Learning",

author = "Mandana Kariminejad and David Tormey and Christopher O'Hara and Marion McAfee",

year = "2023",

month = jul,

day = "3",

doi = "10.1109/codit58514.2023.10284132",

language = "Undefined/Unknown",

booktitle = "2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)",

}

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Prediction of Hotspots in Injection Moulding by Using Simulation, In-Mould Sensors, and Machine Learning

AU - Kariminejad, Mandana

AU - Tormey, David

AU - O'Hara, Christopher

AU - McAfee, Marion

PY - 2023/7/3

Y1 - 2023/7/3

UR - http://dx.doi.org/10.1109/codit58514.2023.10284132

U2 - 10.1109/codit58514.2023.10284132

DO - 10.1109/codit58514.2023.10284132

M3 - Conference contribution

BT - 2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)

ER -