Research graph
References from Data-driven cycle time optimisation in semiconductor manufacturing using machine learning and heuristic search algorithms. Local targets link to admitted publications; unresolved targets remain external evidence.
Systematic consequence of different splitting indices on the classification performance of random decision forest
2022 · External reference
Precise and accurate job cycle time forecasting with a fuzzy data mining approach
2013 · External reference
Manufacturing intelligence to forecast and reduce semiconductor cycle time
10.1007/s10845-011-0572-y · 2012 · External reference
A fast and elitist multiobjective genetic algorithm: NSGA-II
10.1109/4235.996017 · 2002 · External reference
Data-driven aggregate modelling of a semiconductor wafer fab
10.1007/s10696-023-09501-1 · 2024 · External reference
Unresolved reference
2017 · External reference
Integrating AI and machine learning with UVM in semiconductor design
2024 · External reference
Unresolved reference
2025 · External reference
A predictive control model of Bernoulli production line with rework loop for real-time WIP Optimisation in permutation flowshop
10.3390/machines12010020 · 2023 · External reference
Intelligent digital twin system in the semiconductors manufacturing industry
10.1007/978-3-030-61045-6_8 · 2021 · External reference
Semiconductor fabrication strategy for cycle time and capacity optimisation: past and present
2016 · External reference
Maximizing output during ramp by integrating capacity and velocity
10.1109/tsm.2018.2835660 · 2018 · External reference
A hierarchical structure of key performance indicators for operation management and continuous improvement in production systems
10.1080/00207543.2015.1136082 · 2016 · External reference
Particle swarm optimisation
1995 · External reference
Investigation of flow mechanisms in semiconductor wafer fabrication
10.1080/0020754031000065476 · 2003 · External reference
A method for wafer assignment in semiconductor wafer fabrication considering both quality and productivity perspectives
10.1016/j.jmsy.2019.05.006 · 2019 · External reference
Manufacturing performance evaluation in wafer semiconductor factories
10.1108/17410400610653246 · 2006 · External reference
Unresolved reference
2006 · External reference
Soft sensing at scale
2021 · External reference
Soft sensing model visualization: fine-tuning neural network from what model learned
2021 · External reference
Survey on data-driven industrial process monitoring and diagnosis
10.1016/j.arcontrol.2012.09.004 · 2012 · External reference
Revolutionizing semiconductor design and manufacturing with AI
10.60087/jklst.vol3.n3.p.272-277 · 2024 · External reference
Machine learning with heuristic search-based hybrid framework for cycle time optimisation in semiconductor production
2025 · External reference
AI in smart manufacturing: driving efficiency and sustainability
2026 · External reference
A hybrid Monte Carlo–machine learning framework for high-energy neutron shielding using boron-enhanced concrete
2026 · External reference
Estimating wafer processing cycle time using an improved G/G/M queue
2013 · External reference
Induced start dynamic sampling for wafer metrology optimisation
10.1109/tase.2019.2929193 · 2020 · External reference
Cycle time prediction in wafer fabrication line by applying data mining methods
2011 · External reference
Optimal cyclic scheduling for dual-arm cluster tools using MILP
10.1109/tsm.2023.3239198 · 2023 · External reference
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 · External reference
Soft sensing transformer: hundreds of sensors are worth a single word
2021 · External reference
Intelligent digital twin system in the semiconductors manufacturing industry
10.1007/978-3-030-61045-6_8 · ExternalCitation · doi-reference
Data-driven aggregate modelling of a semiconductor wafer fab
10.1007/s10696-023-09501-1 · ExternalCitation · doi-reference
Manufacturing intelligence to forecast and reduce semiconductor cycle time
10.1007/s10845-011-0572-y · ExternalCitation · doi-reference
Survey on data-driven industrial process monitoring and diagnosis
10.1016/j.arcontrol.2012.09.004 · ExternalCitation · doi-reference
A method for wafer assignment in semiconductor wafer fabrication considering both quality and productivity perspectives
10.1016/j.jmsy.2019.05.006 · ExternalCitation · doi-reference
Investigation of flow mechanisms in semiconductor wafer fabrication
10.1080/0020754031000065476 · ExternalCitation · doi-reference
A hierarchical structure of key performance indicators for operation management and continuous improvement in production systems
10.1080/00207543.2015.1136082 · ExternalCitation · doi-reference
Manufacturing performance evaluation in wafer semiconductor factories
10.1108/17410400610653246 · ExternalCitation · doi-reference
A fast and elitist multiobjective genetic algorithm: NSGA-II
10.1109/4235.996017 · ExternalCitation · doi-reference
Induced start dynamic sampling for wafer metrology optimisation
10.1109/tase.2019.2929193 · ExternalCitation · doi-reference
Efficient approach to cyclic scheduling of single-arm cluster tools with chamber cleaning operations and wafer residency time constraint
10.1109/tsm.2018.2811125 · ExternalCitation · doi-reference
Maximizing output during ramp by integrating capacity and velocity
10.1109/tsm.2018.2835660 · ExternalCitation · doi-reference
Optimal cyclic scheduling for dual-arm cluster tools using MILP
10.1109/tsm.2023.3239198 · ExternalCitation · doi-reference
A predictive control model of Bernoulli production line with rework loop for real-time WIP Optimisation in permutation flowshop
10.3390/machines12010020 · ExternalCitation · doi-reference
Revolutionizing semiconductor design and manufacturing with AI
10.60087/jklst.vol3.n3.p.272-277 · ExternalCitation · doi-reference
