IDEAS home Printed from https://ideas.repec.org/a/epw/ejai00/v4y2025i2id1056.html

Use Artificial Intelligence into Facility Design and Layout Planning Work in Manufacturing Facility

Author

Listed:
  • Sai Dhiresh Kilari

    (University of Texas, Texas)

Abstract

The integration of artificial intelligence (AI) into facility design and layout planning has revolutionized manufacturing by enhancing precision, efficiency, and adaptability. Traditional facility planning methods, reliant on static, rule-based approaches, are increasingly being replaced by AI-driven solutions that optimize spatial arrangements, improve workflow, and balance human-machine interactions. This paper explores the application of AI tools such as Process Planning AI, AutoCAD AI, and Space & Machine Design AI in manufacturing facility design. These technologies leverage predictive modeling, real-time analytics, and generative design to optimize process planning, enhance production layouts, and facilitate adaptive decision-making. Additionally, AI-driven simulations and digital modeling enable manufacturers to anticipate design challenges, reduce bottlenecks, and maximize resource utilization. As AI adoption grows, its role in smart factories and dynamic production environments continues to evolve, fostering a more data-driven, efficient, and automated approach to facility layout and design.

Suggested Citation

Handle: RePEc:epw:ejai00:v:4:y:2025:i:2:id:1056
DOI: 10.24018/ejai.2025.4.2.56
as

Download full text from publisher

File URL: https://eu-opensci.org/index.php/ejai/article/view/1056
File Function: Abstract page
Download Restriction: no

File URL: https://eu-opensci.org/index.php/ejai/article/download/1056/383
File Function: Full text
Download Restriction: no

File URL: https://libkey.io/10.24018/ejai.2025.4.2.56?utm_source=ideas
LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
---><---

More about this item

Keywords

;
;
;
;

Statistics

Access and download statistics

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:epw:ejai00:v:4:y:2025:i:2:id:1056. See general information about how to correct material in RePEc.

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

We have no bibliographic references for this item. You can help adding them by using this form .

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Support Team (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejai .

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.