Innovations in Smart Manufacturing: An Experimental Assessment of Emerging Technologies
With an emphasis on machine learning and artificial intelligence (AI), the Internet of Things (IoT), robotics, and data analytics, this research offers a methodical empirical evaluation of cutting-edge technologies in the field of smart manufacturing. The findings indicate notable progress in the ab...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
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| Series: | BIO Web of Conferences |
| Subjects: | |
| Online Access: | https://www.bio-conferences.org/articles/bioconf/pdf/2024/05/bioconf_rtbs2024_01064.pdf |
| _version_ | 1797352892454141952 |
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| author | Blinova Tatiana Pant Ruby Nijhawan Ginni Prakash Anshika Sharma Achyut |
| author_facet | Blinova Tatiana Pant Ruby Nijhawan Ginni Prakash Anshika Sharma Achyut |
| author_sort | Blinova Tatiana |
| collection | DOAJ |
| description | With an emphasis on machine learning and artificial intelligence (AI), the Internet of Things (IoT), robotics, and data analytics, this research offers a methodical empirical evaluation of cutting-edge technologies in the field of smart manufacturing. The findings indicate notable progress in the abilities of the employees. Employee 2 had an astounding 30% gain in machine learning competence, while Employee 3 demonstrated a 50% growth in robotics proficiency. Production Line Efficiency showed scope for development; Line B showed a 0.7% gain in efficiency, indicating that there is still opportunity for process improvements. Analyzing sensor data highlights the need of ongoing maintenance and monitoring to guarantee optimum machine functioning. Data from quality control indicated that stricter guidelines were required to lower product faults. With implications for increased productivity and quality, this study advances our knowledge of the revolutionary potential of smart manufacturing technologies, including workforce development, technology adoption, and process optimization. |
| first_indexed | 2024-03-08T13:23:20Z |
| format | Article |
| id | doaj.art-31d84a0cd9af4f488f2aa97460eacfe4 |
| institution | Directory Open Access Journal |
| issn | 2117-4458 |
| language | English |
| last_indexed | 2024-03-08T13:23:20Z |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | BIO Web of Conferences |
| spelling | doaj.art-31d84a0cd9af4f488f2aa97460eacfe42024-01-17T15:02:13ZengEDP SciencesBIO Web of Conferences2117-44582024-01-01860106410.1051/bioconf/20248601064bioconf_rtbs2024_01064Innovations in Smart Manufacturing: An Experimental Assessment of Emerging TechnologiesBlinova Tatiana0Pant Ruby1Nijhawan Ginni2Prakash Anshika3Sharma Achyut4Department of Management and innovation, National Research University Moscow State University of Civil EngineeringUttaranchal Institute of Technology, Uttaranchal UniversityLovely Professional UniversityK R Mangalam UniversityGD Goenka UniversityWith an emphasis on machine learning and artificial intelligence (AI), the Internet of Things (IoT), robotics, and data analytics, this research offers a methodical empirical evaluation of cutting-edge technologies in the field of smart manufacturing. The findings indicate notable progress in the abilities of the employees. Employee 2 had an astounding 30% gain in machine learning competence, while Employee 3 demonstrated a 50% growth in robotics proficiency. Production Line Efficiency showed scope for development; Line B showed a 0.7% gain in efficiency, indicating that there is still opportunity for process improvements. Analyzing sensor data highlights the need of ongoing maintenance and monitoring to guarantee optimum machine functioning. Data from quality control indicated that stricter guidelines were required to lower product faults. With implications for increased productivity and quality, this study advances our knowledge of the revolutionary potential of smart manufacturing technologies, including workforce development, technology adoption, and process optimization.https://www.bio-conferences.org/articles/bioconf/pdf/2024/05/bioconf_rtbs2024_01064.pdfroboticsdata analyticsmachine learningiotsmart manufacturingemerging technologies |
| spellingShingle | Blinova Tatiana Pant Ruby Nijhawan Ginni Prakash Anshika Sharma Achyut Innovations in Smart Manufacturing: An Experimental Assessment of Emerging Technologies BIO Web of Conferences robotics data analytics machine learning iot smart manufacturing emerging technologies |
| title | Innovations in Smart Manufacturing: An Experimental Assessment of Emerging Technologies |
| title_full | Innovations in Smart Manufacturing: An Experimental Assessment of Emerging Technologies |
| title_fullStr | Innovations in Smart Manufacturing: An Experimental Assessment of Emerging Technologies |
| title_full_unstemmed | Innovations in Smart Manufacturing: An Experimental Assessment of Emerging Technologies |
| title_short | Innovations in Smart Manufacturing: An Experimental Assessment of Emerging Technologies |
| title_sort | innovations in smart manufacturing an experimental assessment of emerging technologies |
| topic | robotics data analytics machine learning iot smart manufacturing emerging technologies |
| url | https://www.bio-conferences.org/articles/bioconf/pdf/2024/05/bioconf_rtbs2024_01064.pdf |
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