Advancing predictive maintenance: a comprehensive case study through industry 4.0

Year 2024, , 133 - 142, 30.09.2024

Ülge Taş

https://doi.org/10.18245/ijaet.1543509

Abstract

The paper is focused on predictive maintenance in the automotive industry with a specialization in technologies related to Industry 4.0. The emergence of predictive maintenance with Industry 4.0 technologies is also called Maintenance 4.0. The article describes specific Industry 4.0 technologies, such as supervisory control and data acquisition (SCADA) and Predictive Maintenance (PdM), that are being implemented in manufacturing companies. The sample for the case study consisted of a paint shop from the automotive sector that operates in Turkey. In the data collection step, SCADA collected data from pressure sensors to create a historical database for PdM. The purpose of this article is to illustrate, through a case study, the importance of PdM using SCADA using Industry 4.0 instruments such as the Internet of Things and big data. 18 filters, which were replaced every 6 months during preventive maintenance, are now replaced at different intervals through PDM after this study. Based on SCADA data, a total of 2 filters experience blockage in both the primer and topcoat paint processes every 6 months. Over a 12-month period, an extra 9 filters are blocked across all processes. Furthermore, within a 24-month timeframe, a total of 7 more filters become blocked in the entirety of the operational processes. The results showed that the PdM combination increased the effectiveness of care by 45.83%.

Keywords

Automotive Sector, Industry 4.0, Maintenance 4.0, PdM (Predictive Maintenance), SCADA Smart Systems.

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