The Application of AI for the Modelling and Optimisation of Technological Processes

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F24%3A43973022" target="_blank" >RIV/49777513:23220/24:43973022 - isvavai.cz</a>

Výsledek na webu

<a href="https://index.ieomsociety.org/index.cfm/article/view/ID/17516" target="_blank" >https://index.ieomsociety.org/index.cfm/article/view/ID/17516</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.46254/EU07.20240152" target="_blank" >10.46254/EU07.20240152</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The Application of AI for the Modelling and Optimisation of Technological Processes

Popis výsledku v původním jazyce

This paper reviews the current state of affairs regarding the application of AI for the modelling and optimisation of technological processes. AI is deployed in a plethora of different ways for these purposes. In addition to facilitating modelling, it is also used to determine the optimum procedures and sequences for technological processes and operations. Further to this, it is employed in efforts to eliminate disturbances in processes and can model quality outcomes based on which parameters are set in production processes and establish which parameters should be put in place. AI-based algorithms have been developed that are capable of enhancing models of the optimal controlling of multi-parameter processes and optimising process parameters. They can help to model processes that provide the optimum balance between efficiency and quality. They are also capable of providing machine-generated advice to those involved in facilitating technological processes. Furthermore, AI is used to provide visualisations of processes in order to inform decisions regarding their optimisation. It can inform the tools that are best suited for use in processes and the workpiece-instrumentation selection. It can also be used to inform the best choice of equipment to use in conjunction with specific machinery in processes. A system involving AI has also been devised to describe incomplete data and uncertainties within technological processes so that efforts can be made to mitigate them. It can aid in the selection of the optimum materials for use in manufacturing processes and can also help to align plans for processes with the particular needs of companies. Other uses of AI for process modelling and optimisation include identifying process fingerprints, extending the capabilities of surrogate-based optimisation, and noising monitoring signals that transfer data from technological equipment to computers to enable process optimisation. This paper outlines the use of AI for these purposes and provides information of how it is deployed to achieve these aims when possible. It aims to provide a holistic summary and discussion of various AI-related applications regarding process modelling and optimisation. Furthermore, it discusses some of the underlying mechanisms for the AI algorithms. It is concluded that AI is utilised for a wide variety of different tasks related to these areas and that it is likely to become an increasingly indispensable tool for enhancing processes throughout the years to come. Some predictions for future innovations that are likely to enter usage are also presented.

Název v anglickém jazyce

The Application of AI for the Modelling and Optimisation of Technological Processes

Popis výsledku anglicky

This paper reviews the current state of affairs regarding the application of AI for the modelling and optimisation of technological processes. AI is deployed in a plethora of different ways for these purposes. In addition to facilitating modelling, it is also used to determine the optimum procedures and sequences for technological processes and operations. Further to this, it is employed in efforts to eliminate disturbances in processes and can model quality outcomes based on which parameters are set in production processes and establish which parameters should be put in place. AI-based algorithms have been developed that are capable of enhancing models of the optimal controlling of multi-parameter processes and optimising process parameters. They can help to model processes that provide the optimum balance between efficiency and quality. They are also capable of providing machine-generated advice to those involved in facilitating technological processes. Furthermore, AI is used to provide visualisations of processes in order to inform decisions regarding their optimisation. It can inform the tools that are best suited for use in processes and the workpiece-instrumentation selection. It can also be used to inform the best choice of equipment to use in conjunction with specific machinery in processes. A system involving AI has also been devised to describe incomplete data and uncertainties within technological processes so that efforts can be made to mitigate them. It can aid in the selection of the optimum materials for use in manufacturing processes and can also help to align plans for processes with the particular needs of companies. Other uses of AI for process modelling and optimisation include identifying process fingerprints, extending the capabilities of surrogate-based optimisation, and noising monitoring signals that transfer data from technological equipment to computers to enable process optimisation. This paper outlines the use of AI for these purposes and provides information of how it is deployed to achieve these aims when possible. It aims to provide a holistic summary and discussion of various AI-related applications regarding process modelling and optimisation. Furthermore, it discusses some of the underlying mechanisms for the AI algorithms. It is concluded that AI is utilised for a wide variety of different tasks related to these areas and that it is likely to become an increasingly indispensable tool for enhancing processes throughout the years to come. Some predictions for future innovations that are likely to enter usage are also presented.

Druh

O - Ostatní výsledky

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů