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Hierarchical aggregation/disaggregation for adaptive abstraction-level conversion in digital twin-based smart semiconductor manufacturing
In smart manufacturing, engineers typically analyze unexpected real-time problems using
digitally cloned discrete-event (DE) models for wafer fabrication. To achieve a faster …
digitally cloned discrete-event (DE) models for wafer fabrication. To achieve a faster …
Automatic Model Generation and Data Assimilation Framework for Cyber-Physical Production Systems
The recent development of new technologies within the Industry 4.0 revolution drives the
increased digitization of manufacturing plants. To effectively utilize the digital twins, it is …
increased digitization of manufacturing plants. To effectively utilize the digital twins, it is …
Transforming discrete event models to machine learning models
Discrete event simulation, formalized as deductive modeling, has been shown to be effective
for studying dynamical systems. Development of models, however, is challenging when …
for studying dynamical systems. Development of models, however, is challenging when …
Generating TCN Models From Parallel Devs Models: Semiconductor Manufacturing Systems
Machine learning models have the potential to augment the simulation of discrete-event
dynamical systems, which is of considerable interest. Such models should serve the central …
dynamical systems, which is of considerable interest. Such models should serve the central …
Hyperparameter Tuning with Gaussian Processes for Optimal Abstraction Control in Simulation-based Optimization of Smart Semiconductor Manufacturing Systems
Smart manufacturing utilizes digital twins that are virtual forms of their production plants for
analyzing and optimizing decisions. Digital twins have been mainly developed as discrete …
analyzing and optimizing decisions. Digital twins have been mainly developed as discrete …
Hyperparameter tunning in simulation-based optimization for adaptive digital-twin abstraction control of smart manufacturing system
Smart manufacturing utilizes digital twins (DTs) that are virtual forms of their production
plants for optimizing decisions. Discrete-event models (DEMs) are frequently used to model …
plants for optimizing decisions. Discrete-event models (DEMs) are frequently used to model …
Adaptive abstraction-level conversion framework for accelerated discrete-event simulation in smart semiconductor manufacturing
Speeding up the simulation of discrete-event wafer-fabrication models is essential for fast
decision-making to handle unexpected events in smart semiconductor manufacturing …
decision-making to handle unexpected events in smart semiconductor manufacturing …
Metamorphic Edge Processor Simulation Framework Using Flexible Runtime Partial Replacement of Software-Embedded Verilog RTL Models
Iterative register-transfer level (RTL) simulation is essential for the edge processor design,
but the RTL simulation speed is significantly slower in a system where various RTL models …
but the RTL simulation speed is significantly slower in a system where various RTL models …
Petri Net-Based Multi-Module Optimization Scheduling Strategy for Combinatorial Equipment
Combinatorial equipment plays a crucial role in semiconductor wafer manufacturing, and
optimizing its scheduling and control poses significant challenges in the semiconductor …
optimizing its scheduling and control poses significant challenges in the semiconductor …
[PDF][PDF] TRANSFORMING DISCRETE EVENT MODELS TO MACHINE LEARNING MODELS
CG Corlu, SR Hunter, H Lam, BS Onggo, J Shortle… - sce.carleton.ca
Discrete event simulation, formalized as deductive modeling, has been shown to be effective
for studying dynamical systems. Development of models, however, is challenging when …
for studying dynamical systems. Development of models, however, is challenging when …