Temperature Monitoring System for Rubber Cutter Extrusion Machine Using Mlx90614 Temperature Infrared Sensor with Generative Pre-Trained Transformer (GPT) Prescriptive Analysis
This study aims to enhance the temperature monitoring system in rubber cutter extrusion machines at Sun Yuen Rubber Manufacturing using the MLX90614 infrared temperature sensor. The existing temperature measurement approach suffers from low accuracy and is susceptible to human error, leading to...
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| Format: | Article |
| Language: | English |
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UTP Press
2025-03-01
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| Series: | Platform, a Journal of Engineering |
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| Online Access: | https://mysitasi.mohe.gov.my/uploads/get-media-file?refId=a1ad2710-22d5-401a-83cf-13fc4cc934f4 |
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| _version_ | 1849427040400310272 |
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| author | Nur Atiqah Saaidin Nasraan Shah Mohamed Nasser |
| author_facet | Nur Atiqah Saaidin Nasraan Shah Mohamed Nasser |
| author_sort | Nur Atiqah Saaidin |
| collection | DOAJ |
| description | This study aims to enhance the temperature monitoring system in rubber cutter extrusion machines at Sun Yuen Rubber
Manufacturing using the MLX90614 infrared temperature sensor. The existing temperature measurement approach
suffers from low accuracy and is susceptible to human error, leading to inconsistent product quality and reduced
productivity. The proposed solution leverages the MLX90614 sensor for its high accuracy and non-contact temperature
measurement capabilities. The study involves designing and implementing a new temperature monitoring system
integrating the MLX90614 sensor. This system’s performance will be compared to the current system to demonstrate
improvements. The methodology includes designing the temperature monitoring setup, testing its functionality, and
collecting temperature data. The data will be analysed using statistical methods to evaluate the system’s accuracy,
reliability, and consistency in maintaining the desired temperature range. Additionally, the study incorporates
Generative Pre-Trained Transformer (GPT) models for prescriptive analysis. The GPT model will provide insights and
recommendations for optimising the temperature control process, further enhancing product quality and operational
efficiency by analysing the collected data. Expected outcomes include a significant improvement in the accuracy and
reliability of temperature measurements, leading to better product quality and increased productivity. This study will
also support the company’s progression towards Industry 4.0 and ESG standards by integrating advanced technology
to optimise production. Overall, this study will deliver a robust temperature monitoring system that mitigates human
error and enhances operational efficiency. The integration of GPT-based prescriptive analysis will provide actionable
insights, driving continuous improvements in the rubber manufacturing process. |
| format | Article |
| id | doaj-art-a4d9dfe5561e4b9b91e9bdc0e9fd47a5 |
| institution | Kabale University |
| issn | 2636-9877 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | UTP Press |
| record_format | Article |
| series | Platform, a Journal of Engineering |
| spelling | doaj-art-a4d9dfe5561e4b9b91e9bdc0e9fd47a52025-08-20T03:29:09ZengUTP PressPlatform, a Journal of Engineering2636-98772025-03-01915667Temperature Monitoring System for Rubber Cutter Extrusion Machine Using Mlx90614 Temperature Infrared Sensor with Generative Pre-Trained Transformer (GPT) Prescriptive AnalysisNur Atiqah Saaidin0Nasraan Shah Mohamed Nasser1Department of Mechanical Engineering, Universiti Teknologi PETRONAS, Malaysia Department of Electrical & Electronic Engineering, Universiti Teknologi PETRONAS, Malaysia This study aims to enhance the temperature monitoring system in rubber cutter extrusion machines at Sun Yuen Rubber Manufacturing using the MLX90614 infrared temperature sensor. The existing temperature measurement approach suffers from low accuracy and is susceptible to human error, leading to inconsistent product quality and reduced productivity. The proposed solution leverages the MLX90614 sensor for its high accuracy and non-contact temperature measurement capabilities. The study involves designing and implementing a new temperature monitoring system integrating the MLX90614 sensor. This system’s performance will be compared to the current system to demonstrate improvements. The methodology includes designing the temperature monitoring setup, testing its functionality, and collecting temperature data. The data will be analysed using statistical methods to evaluate the system’s accuracy, reliability, and consistency in maintaining the desired temperature range. Additionally, the study incorporates Generative Pre-Trained Transformer (GPT) models for prescriptive analysis. The GPT model will provide insights and recommendations for optimising the temperature control process, further enhancing product quality and operational efficiency by analysing the collected data. Expected outcomes include a significant improvement in the accuracy and reliability of temperature measurements, leading to better product quality and increased productivity. This study will also support the company’s progression towards Industry 4.0 and ESG standards by integrating advanced technology to optimise production. Overall, this study will deliver a robust temperature monitoring system that mitigates human error and enhances operational efficiency. The integration of GPT-based prescriptive analysis will provide actionable insights, driving continuous improvements in the rubber manufacturing process.https://mysitasi.mohe.gov.my/uploads/get-media-file?refId=a1ad2710-22d5-401a-83cf-13fc4cc934f4data analysis and industrial automationmanufacturing quality controlnon-contact temperature measurementproduction optimisationsensor accuracy |
| spellingShingle | Nur Atiqah Saaidin Nasraan Shah Mohamed Nasser Temperature Monitoring System for Rubber Cutter Extrusion Machine Using Mlx90614 Temperature Infrared Sensor with Generative Pre-Trained Transformer (GPT) Prescriptive Analysis Platform, a Journal of Engineering data analysis and industrial automation manufacturing quality control non-contact temperature measurement production optimisation sensor accuracy |
| title | Temperature Monitoring System for Rubber Cutter Extrusion Machine Using Mlx90614 Temperature Infrared Sensor with Generative Pre-Trained Transformer (GPT) Prescriptive Analysis |
| title_full | Temperature Monitoring System for Rubber Cutter Extrusion Machine Using Mlx90614 Temperature Infrared Sensor with Generative Pre-Trained Transformer (GPT) Prescriptive Analysis |
| title_fullStr | Temperature Monitoring System for Rubber Cutter Extrusion Machine Using Mlx90614 Temperature Infrared Sensor with Generative Pre-Trained Transformer (GPT) Prescriptive Analysis |
| title_full_unstemmed | Temperature Monitoring System for Rubber Cutter Extrusion Machine Using Mlx90614 Temperature Infrared Sensor with Generative Pre-Trained Transformer (GPT) Prescriptive Analysis |
| title_short | Temperature Monitoring System for Rubber Cutter Extrusion Machine Using Mlx90614 Temperature Infrared Sensor with Generative Pre-Trained Transformer (GPT) Prescriptive Analysis |
| title_sort | temperature monitoring system for rubber cutter extrusion machine using mlx90614 temperature infrared sensor with generative pre trained transformer gpt prescriptive analysis |
| topic | data analysis and industrial automation manufacturing quality control non-contact temperature measurement production optimisation sensor accuracy |
| url | https://mysitasi.mohe.gov.my/uploads/get-media-file?refId=a1ad2710-22d5-401a-83cf-13fc4cc934f4 |
| work_keys_str_mv | AT nuratiqahsaaidin temperaturemonitoringsystemforrubbercutterextrusionmachineusingmlx90614temperatureinfraredsensorwithgenerativepretrainedtransformergptprescriptiveanalysis AT nasraanshahmohamednasser temperaturemonitoringsystemforrubbercutterextrusionmachineusingmlx90614temperatureinfraredsensorwithgenerativepretrainedtransformergptprescriptiveanalysis |