Engineering, Energy, Transport AIC

Elchyn ALIIEV – Doctor of Technical Sciences, Senior Researcher, Professor of the Department of Technical Systems Engineering of Dnipro State Agrarian and Economic University (St. S. Efremova, 25, Dnipro, Ukraine, 49000, e-mail: aliev@meta.ua, https://orcid.org/0000-0003-4006-8803). 
Yevhenii NOSENKO – Postgraduate Student of Dnipro State Agrarian and Economic University (St. S. Efremova, 25, Dnipro, Ukraine, 49000, e-mail: vsetut13@gmail.com, https://orcid.org/0009-0006-1115-7443).

This study addresses the issue of technical reliability and efficiency of milking equipment, which is a crucial element of modern dairy production. It has been established that the technical condition of milking systems directly affects product quality, animal health, and overall farm productivity. Despite the existence of international standards (ISO 3918, ISO 5707, ISO 6690), the current diagnostic methods are largely outdated, highlighting the relevance of developing modern diagnostic instruments. The research reviews recent scientific advancements in monitoring the technical state of milking equipment, including the application of IoT technologies, machine learning (ML), sensor systems, and augmented reality (AR). The effectiveness of using LSTM and ARIMA models for failure prediction is demonstrated, along with the implementation of RGBD cameras, electrical conductivity, and infrared spectroscopy for improving milking quality and diagnosing animal health issues. The study presents original technical solutions: the Milking Installation Tester v.2.0 based on Arduino Mega 2560, which allows the measurement of key parameters such as pressure, pulsation, temperature, air flow, and rotational frequency; and a testing stand for evaluating the condition of teat liners, enabling assessment of tension and elongation under real operating conditions. The system supports external sensor connectivity, USB data transmission, and further processing in Excel, including hysteresis graph plotting. An adaptive maintenance approach is proposed, based on actual operating hours rather than a fixed schedule, considering the variability in component quality from different manufacturers. The study concludes that the implementation of integrated monitoring systems and technical bulletins can enhance operational efficiency. The deployment of the proposed methods and devices significantly improves the reliability of milking systems, reduces failure risks, enhances animal welfare, and increases the overall economic efficiency of dairy farms.

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