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Volume 13 | Issue 4 | Year 2026 | Article Id. IJME-V13I4P102 | DOI : https://doi.org/10.14445/23488360/IJME-V13I4P102

Development and Implementation of Real Time IoT-Enabled Cutting Temperature Monitoring System for Bearing Manufacturing Process


Manan Bhavesh Raval, Hirenkumar Indravadan Joshi

Received Revised Accepted Published
03 Jan 2026 10 Feb 2026 12 Mar 2026 29 Apr 2026

Citation :

Manan Bhavesh Raval, Hirenkumar Indravadan Joshi, "Development and Implementation of Real Time IoT-Enabled Cutting Temperature Monitoring System for Bearing Manufacturing Process," International Journal of Mechanical Engineering, vol. 13, no. 4, pp. 16-27, 2026. Crossref, https://doi.org/10.14445/23488360/IJME-V13I4P102

Abstract

Such excessive cutting temperature in external grinding has a detrimental effect on the surface finish, dimensional accuracy, and overall productivity in the manufacture of bearing components. This manuscript describes the design and industrial application of a real-time Internet of Things-enabled cutting temperature monitoring system developed for the use of cutting SAE 52100 bearing races in an external grinding machine. The system architecture has been integrated with a non-contact infrared temperature sensor, ESP32 microcontroller, wireless communications protocols, cloud-based data storage, and a web-based dashboard with utter threshold alerts to allow for in-process monitoring in a continuous fashion, proximal to the zone of grinding. Industrial additional validation was performed on a series of 259 bearing races at several production shifts. Revealed by empirical data was that there were stable grinding conditions maintained within a temperature band of 21.10°C to 24.95°C, and the highest recorded temperature was obtained at 26.31°C with resulting overall temperature variation of 4.58°C. Sustained presence of cutting temperature in the 20 - 25°C range invariably showed superior surface finish from 0.15 μm to 0.18 μm and dimensional accuracy with ± 0.01mm. To evaluate shift-wise process stability, the Thermal Stability Index (TSI) was introduced. The results validate the idea that the proposed system is a cost-effective, scalable, and industry-ready solution for real-time, quality-oriented monitoring of the grinding process and a basis for future predictive and adaptive control system applications.

Keywords

IoT (Internet of Things), Process monitoring, Temperature measurement, Thermal stability.

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