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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM41235

Digital Mock-up analysis using Artificial Intelligence of Things

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM41235

Volume:

9 |

1 |

Jan 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM41235

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

AD

Amol Didore

SR

Soutrik Roy

GS

Gaganpreet Singh

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Abstract

Digital Mock-Up units (DMU) are a design or human factor for study and inspection of Computer Aided Designs to help designers identify key design issues and factors which can lead to the functional failure of a product in the early stages of development. Digital Mock-Ups can be used by Computer Aided Design (CAD) & Non- Computer Aided design users to review a product before sending a design to the final stage i.e. Production. Currently, Digital Mock-Ups is used in a wide variety of industries ranging from automobiles to healthcare to aerospace. Additionally, DMU also has some drawbacks such as being time consuming, leading to human errors & repetitive work etc. This paper explores what is the current review process of Digital Mock-Ups in the industry to derive technological & functional information and how latest technologies like Artificial Intelligence (AI) and internet of things (IOT) can be adopted to review Digital Mock-Ups even more effectively using technologies like computer vision and image recognition to reduce human error in the review process.

KEYWORDS

Digital Mock-up Units Artificial Intelligence of Things Sensors Image Recognition Object Detection Machine Vision

Cite This Article

Amol Didore, Soutrik Roy, Gaganpreet Singh, "Digital Mock-up analysis using Artificial Intelligence of Things," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 1, Jan 2025. https://doi.org/10.55041/IJSREM41235

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Publication Date

1/31/2025

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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