An Automation Designed for Industry 4.0 Using Robotics and Sensors that Based on IoT & Machine Learning
Even though there has been significant research conducted on the topic, the idea of the fourth industrial revolution is still not widely acknowledged. The adoption of Industry 4.0 is anticipated to enhance multiple facets of human existence. The integration of Industry 4.0 will influence various sta...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2023-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/42/e3sconf_icstce2023_02014.pdf |
| _version_ | 1797756264752611328 |
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| author | Soumyashree S. Gupta Anuj Biswas Balaka |
| author_facet | Soumyashree S. Gupta Anuj Biswas Balaka |
| author_sort | Soumyashree S. |
| collection | DOAJ |
| description | Even though there has been significant research conducted on the topic, the idea of the fourth industrial revolution is still not widely acknowledged. The adoption of Industry 4.0 is anticipated to enhance multiple facets of human existence. The integration of Industry 4.0 will influence various stages of production processes, distribution networks, consumers, supervisors, creators of digital systems, and all staff members engaged in the process. This will lead to changes in manufacturing models and business paradigms. This technology enables self-identification, self-configuration, self-diagnosis, and self-optimization in various industries. This study employs the decision tree algorithm to monitor the energy usage of machines and appliances, predict their future behaviour. Upon assessment of the effectiveness of the proposed system and juxtaposing it against current methodologies, it was determined that the system had a 79% efficiency rate. The integration of this technology presents a number of obstacles, such as standardization dilemmas, security risks, difficulties with resource planning, legal considerations, and the necessity of adjusting to evolving business models. The success or failure of Industry 4.0 and its implementation relies entirely on the involvement and cooperation of all participants in the production chain, from manufacturers to end-users. |
| first_indexed | 2024-03-12T17:58:55Z |
| format | Article |
| id | doaj.art-eaab383cf2794055a6bfcf25d670657a |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-03-12T17:58:55Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-eaab383cf2794055a6bfcf25d670657a2023-08-02T13:18:12ZengEDP SciencesE3S Web of Conferences2267-12422023-01-014050201410.1051/e3sconf/202340502014e3sconf_icstce2023_02014An Automation Designed for Industry 4.0 Using Robotics and Sensors that Based on IoT & Machine LearningSoumyashree S.0Gupta Anuj1Biswas Balaka2Department of Mechatronics Engineering, Chandigarh UniversityDepartment of Electronics and Communication Engineering, Chandigarh UniversityDepartment of Electronics and Communication Engineering, Chandigarh UniversityEven though there has been significant research conducted on the topic, the idea of the fourth industrial revolution is still not widely acknowledged. The adoption of Industry 4.0 is anticipated to enhance multiple facets of human existence. The integration of Industry 4.0 will influence various stages of production processes, distribution networks, consumers, supervisors, creators of digital systems, and all staff members engaged in the process. This will lead to changes in manufacturing models and business paradigms. This technology enables self-identification, self-configuration, self-diagnosis, and self-optimization in various industries. This study employs the decision tree algorithm to monitor the energy usage of machines and appliances, predict their future behaviour. Upon assessment of the effectiveness of the proposed system and juxtaposing it against current methodologies, it was determined that the system had a 79% efficiency rate. The integration of this technology presents a number of obstacles, such as standardization dilemmas, security risks, difficulties with resource planning, legal considerations, and the necessity of adjusting to evolving business models. The success or failure of Industry 4.0 and its implementation relies entirely on the involvement and cooperation of all participants in the production chain, from manufacturers to end-users.https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/42/e3sconf_icstce2023_02014.pdf |
| spellingShingle | Soumyashree S. Gupta Anuj Biswas Balaka An Automation Designed for Industry 4.0 Using Robotics and Sensors that Based on IoT & Machine Learning E3S Web of Conferences |
| title | An Automation Designed for Industry 4.0 Using Robotics and Sensors that Based on IoT & Machine Learning |
| title_full | An Automation Designed for Industry 4.0 Using Robotics and Sensors that Based on IoT & Machine Learning |
| title_fullStr | An Automation Designed for Industry 4.0 Using Robotics and Sensors that Based on IoT & Machine Learning |
| title_full_unstemmed | An Automation Designed for Industry 4.0 Using Robotics and Sensors that Based on IoT & Machine Learning |
| title_short | An Automation Designed for Industry 4.0 Using Robotics and Sensors that Based on IoT & Machine Learning |
| title_sort | automation designed for industry 4 0 using robotics and sensors that based on iot machine learning |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/42/e3sconf_icstce2023_02014.pdf |
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