International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 02 | Feb 2024
p-ISSN: 2395-0072
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Enhanced Diagnostics and Prognostics of Mechatronic Systems using Data Analysis, Visualization and Prediction Technique Prathamesh Shinde, A1*, Tejas Chavan, B2, and Hrushikesh B. Kulkarni 3 1-3School of Mechatronics Engineering, Symbiosis Skills and Professional University, Kiwale, Pune
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performance and minimize operational downtime, thereby maximizing productivity and efficiency. Within the domain of lathe machines, three pivotal parameters emerge as key determinants of operational effectiveness—temperature, vibration, and speed. The meticulous management of these parameters directly influences the machine's operational efficiency and reliability.
Abstract - Mechatronic systems play a crucial role in
modern manufacturing, integrating mechanical, electrical, and computer engineering disciplines. Among these systems, lathe machines are quintessential tools for shaping and machining various materials with precision. This research paper explores the integration of data analysis, visualization, and prediction techniques to enhance diagnostics and prognostics in lathe machines. Three critical parameters— temperature, vibration, and speed—are investigated for their impact on operational efficiency and reliability. A representative lathe machine was chosen, and a Python program was developed for real-time data acquisition from temperature, vibration, and speed sensors. The collected data provided insights into the dynamic interplay of these parameters during machine operation. Results indicate that the developed prognostics framework effectively utilizes integrated sensor data to provide early warnings of potential issues. The amalgamation of comprehensive exploratory data analysis and predictive modeling reveals fundamental principles governing lathe machine behavior. The findings underscore the feasibility of proactive maintenance strategies in ensuring the robustness of mechatronic systems.
Temperature, for instance, intricately impacts the thermal stability of the lathe machine. Even minor deviations in temperature can have profound effects, potentially compromising machining precision and leading to suboptimal outcomes. Vibration, on the other hand, serves as a critical indicator of the mechanical integrity of the lathe machine. Variations in vibration levels can signal potential faults or wear within machine components, necessitating timely intervention to prevent further damage or malfunction. Meanwhile, speed governs not only the efficacy of the machining process but also the overall longevity of machine components. Careful control and optimization of speed parameters are essential to ensure both efficient operation and prolonged service life. In light of these considerations, this research endeavours to delve into the fusion of data analysis, visualization, and prediction methodologies to augment diagnostics and prognostics in lathe machines. By undertaking a comprehensive exploration of the interplay between temperature, vibration, and speed, the aim is to cultivate a nuanced understanding of the operational dynamics inherent within lathe machines. Through this interdisciplinary approach, it is anticipated that insights gleaned from the study will contribute to the development of proactive maintenance strategies, thereby enhancing the reliability, efficiency, and longevity of lathe machines in industrial settings.
Key Words: Mechatronic systems, Lathe machines, Diagnostics, Prognostics, Data analysis, Visualization, Predictive modelling, Maintenance strategies.
1. INTRODUCTION In contemporary manufacturing processes, the integration of mechanical, electrical, and computer engineering disciplines has given rise to mechatronic systems, representing a significant evolution in industrial technology. Mechatronic systems seamlessly combine these diverse disciplines to create versatile and efficient machinery capable of performing complex tasks with precision and reliability. Among the myriad of machines encompassed within mechatronic systems, the lathe machine stands out as a cornerstone, playing a central role in the shaping and machining of diverse materials with unparalleled accuracy. Its versatility and importance in various industries underscore its indispensable status.
2. MATERIALS USED AND METHODOLOGY For this study aimed at enhancing diagnostics and prognostics in lathe machines, a comprehensive array of materials and equipment were meticulously selected and utilized to facilitate data acquisition and analysis. Central to the study was the careful selection of a representative lathe machine, meticulously chosen to exemplify the complexities of a mechatronic system in industrial settings. To enable realtime data acquisition, an Arduino microcontroller board was strategically employed to interface with a variety of sensors
However, as technology continues to advance at a rapid pace, the need for enhanced diagnostics and prognostics within mechatronic systems becomes increasingly apparent. This imperative arises from the critical necessity to optimize
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