Add to ORKGWe explore the possibility of replacing a first principles process simulator with a learning system. This is motivated in the presented test case setting by a need to speed up a simulator that is to be used in conjunction with an optimisation algorithm to find near optimal process parameters. Here we will discuss the potential problems and difficulties in this application, how to solve them and present the results from a paper mill test case
Effective management and possession of smoothly running design processes of production, deliveries, ...
Dynamic physics-based models of industrial processes can be computationally heavy which prevents usi...
Artificial neural networks are often proposed as an alternative approach for formalizing various qua...
We explore the possibility of replacing a first principles process simulator with a learning system...
The real-time control of production systems requires complex decisions on resource allocation and th...
Simulation-based optimization models are widely applied to find optimal operating conditions of proc...
Research background: In today’s global world and many major market players, companies are forced to ...
textSimulation is often used in research and industry as a low cost, high efficiency alternative to...
Process simulation and digital twins are of paramount importance to design new processes or optimize...
Process efficiency is definitively a critical factor for manufacturing enterprises and the literatur...
Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introdu...
textLarge-scale processes that are modeled using differential algebraic equations based on mass and ...
Recent advances in machine learning and robotics are automating several processes in the real world....
A full scale process simulator is a type of simulator which is comprehensive in the details of the p...
Computer simulation has become an important tool in modeling systems in the last ten years due to pa...
Effective management and possession of smoothly running design processes of production, deliveries, ...
Dynamic physics-based models of industrial processes can be computationally heavy which prevents usi...
Artificial neural networks are often proposed as an alternative approach for formalizing various qua...
We explore the possibility of replacing a first principles process simulator with a learning system...
The real-time control of production systems requires complex decisions on resource allocation and th...
Simulation-based optimization models are widely applied to find optimal operating conditions of proc...
Research background: In today’s global world and many major market players, companies are forced to ...
textSimulation is often used in research and industry as a low cost, high efficiency alternative to...
Process simulation and digital twins are of paramount importance to design new processes or optimize...
Process efficiency is definitively a critical factor for manufacturing enterprises and the literatur...
Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introdu...
textLarge-scale processes that are modeled using differential algebraic equations based on mass and ...
Recent advances in machine learning and robotics are automating several processes in the real world....
A full scale process simulator is a type of simulator which is comprehensive in the details of the p...
Computer simulation has become an important tool in modeling systems in the last ten years due to pa...
Effective management and possession of smoothly running design processes of production, deliveries, ...
Dynamic physics-based models of industrial processes can be computationally heavy which prevents usi...
Artificial neural networks are often proposed as an alternative approach for formalizing various qua...