The use of Generative AI in Manufacturing
Sahradyan, Babken (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025051210932
https://urn.fi/URN:NBN:fi:amk-2025051210932
Tiivistelmä
Artificial Intelligence and Generative AI, in particular, have gained significant attention. The growing interest of companies from different industries in leveraging Generative AI to improve efficiency and increase profitability raised the need to study the Generative AI usage in manufacturing. The objective was to study the practices and benefits of Generative AI in different phases of manufacturing and the possible risks and challenges companies might encounter during its implementation. The selected manufacturing areas included supply chain visibility and distribution, production planning and predictive maintenance.
To achieve this objective, traditional literature review was conducted. The literature was searched using Google Scholar, Research Gate and JAMK University of Applied Sciences’ online library databases. The selected literature was synthesised, and thematic data analysis was conducted, based on which the review was made.
The results demonstrated that current practices of Generative AI in manufacturing are numerous. Generative AI could be applied independently or integrated with other systems to support the selected manufacturing areas. The results also presented a variety of benefits that Generative AI brings which were both application-specific and shared across different manufacturing areas. The identified main risks were classified into ethical and legal, data-related, operational and technical categories. Moreover, a model was developed to serve as a guide for companies or individuals when making decisions regarding practical applications, benefits and risks of Generative AI.
In conclusion, Generative AI was found to be a beneficial tool for improving the selected manufacturing areas. Similar to any other topic, the matter of risks was found to be critical for consideration.
To achieve this objective, traditional literature review was conducted. The literature was searched using Google Scholar, Research Gate and JAMK University of Applied Sciences’ online library databases. The selected literature was synthesised, and thematic data analysis was conducted, based on which the review was made.
The results demonstrated that current practices of Generative AI in manufacturing are numerous. Generative AI could be applied independently or integrated with other systems to support the selected manufacturing areas. The results also presented a variety of benefits that Generative AI brings which were both application-specific and shared across different manufacturing areas. The identified main risks were classified into ethical and legal, data-related, operational and technical categories. Moreover, a model was developed to serve as a guide for companies or individuals when making decisions regarding practical applications, benefits and risks of Generative AI.
In conclusion, Generative AI was found to be a beneficial tool for improving the selected manufacturing areas. Similar to any other topic, the matter of risks was found to be critical for consideration.