Abstract
MM Rahman, Karl McCreadie, Girijesh Prasad, M.M. Manjurul Islam, Saugat Bhattacharyya, Cormac McAteer, B. J. Baker, Nuala Parker
Abstract
Authors
Institutions
No local reference links have been materialized yet.
No local citing links have been materialized yet.
Systematic consequence of different splitting indices on the classification performance of random decision forest
2022
Precise and accurate job cycle time forecasting with a fuzzy data mining approach
2013
Manufacturing intelligence to forecast and reduce semiconductor cycle time
10.1007/s10845-011-0572-y · 2012
A fast and elitist multiobjective genetic algorithm: NSGA-II
10.1109/4235.996017 · 2002
Data-driven aggregate modelling of a semiconductor wafer fab
10.1007/s10696-023-09501-1 · 2024
Unresolved referenced work
2017
Integrating AI and machine learning with UVM in semiconductor design
2024
Unresolved referenced work
2025
A predictive control model of Bernoulli production line with rework loop for real-time WIP Optimisation in permutation flowshop
10.3390/machines12010020 · 2023
Intelligent digital twin system in the semiconductors manufacturing industry
10.1007/978-3-030-61045-6_8 · 2021
Provenance
crossref
Confidence 100%
ror
Confidence 99%
ror
Confidence 99%
ror
Confidence 99%
openalex
Confidence 95%
datacite
Confidence 0%
Semiconductor fabrication strategy for cycle time and capacity optimisation: past and present
2016
Maximizing output during ramp by integrating capacity and velocity
10.1109/tsm.2018.2835660 · 2018
A hierarchical structure of key performance indicators for operation management and continuous improvement in production systems
10.1080/00207543.2015.1136082 · 2016
Particle swarm optimisation
1995
Investigation of flow mechanisms in semiconductor wafer fabrication
10.1080/0020754031000065476 · 2003
A method for wafer assignment in semiconductor wafer fabrication considering both quality and productivity perspectives
10.1016/j.jmsy.2019.05.006 · 2019
Manufacturing performance evaluation in wafer semiconductor factories
10.1108/17410400610653246 · 2006
Unresolved referenced work
2006
Soft sensing at scale
2021
Soft sensing model visualization: fine-tuning neural network from what model learned
2021
Survey on data-driven industrial process monitoring and diagnosis
10.1016/j.arcontrol.2012.09.004 · 2012
Revolutionizing semiconductor design and manufacturing with AI
10.60087/jklst.vol3.n3.p.272-277 · 2024
Machine learning with heuristic search-based hybrid framework for cycle time optimisation in semiconductor production
2025
AI in smart manufacturing: driving efficiency and sustainability
2026
A hybrid Monte Carlo–machine learning framework for high-energy neutron shielding using boron-enhanced concrete
2026
Estimating wafer processing cycle time using an improved G/G/M queue
2013
Induced start dynamic sampling for wafer metrology optimisation
10.1109/tase.2019.2929193 · 2020
Cycle time prediction in wafer fabrication line by applying data mining methods
2011
Optimal cyclic scheduling for dual-arm cluster tools using MILP
10.1109/tsm.2023.3239198 · 2023
Efficient approach to cyclic scheduling of single-arm cluster tools with chamber cleaning operations and wafer residency time constraint
10.1109/tsm.2018.2811125 · 2018
Soft sensing transformer: hundreds of sensors are worth a single word
2021
Efficient approach to cyclic scheduling of single-arm cluster tools with chamber cleaning operations and wafer residency time constraint
10.1109/tsm.2018.2811125 · doi-reference
Optimal cyclic scheduling for dual-arm cluster tools using MILP
10.1109/tsm.2023.3239198 · doi-reference
Induced start dynamic sampling for wafer metrology optimisation
10.1109/tase.2019.2929193 · doi-reference
Revolutionizing semiconductor design and manufacturing with AI
10.60087/jklst.vol3.n3.p.272-277 · doi-reference
Survey on data-driven industrial process monitoring and diagnosis
10.1016/j.arcontrol.2012.09.004 · doi-reference
Manufacturing performance evaluation in wafer semiconductor factories
10.1108/17410400610653246 · doi-reference
A method for wafer assignment in semiconductor wafer fabrication considering both quality and productivity perspectives
10.1016/j.jmsy.2019.05.006 · doi-reference
Investigation of flow mechanisms in semiconductor wafer fabrication
10.1080/0020754031000065476 · doi-reference
A hierarchical structure of key performance indicators for operation management and continuous improvement in production systems
10.1080/00207543.2015.1136082 · doi-reference
Maximizing output during ramp by integrating capacity and velocity
10.1109/tsm.2018.2835660 · doi-reference
Intelligent digital twin system in the semiconductors manufacturing industry
10.1007/978-3-030-61045-6_8 · doi-reference
A predictive control model of Bernoulli production line with rework loop for real-time WIP Optimisation in permutation flowshop
10.3390/machines12010020 · doi-reference
Data-driven aggregate modelling of a semiconductor wafer fab
10.1007/s10696-023-09501-1 · doi-reference
A fast and elitist multiobjective genetic algorithm: NSGA-II
10.1109/4235.996017 · doi-reference
Manufacturing intelligence to forecast and reduce semiconductor cycle time
10.1007/s10845-011-0572-y · doi-reference