Initiating predictive maintenance for a conveyor motor in a bottling plant using industry 4.0 concepts

Abstract

For the past recent years, Industry 4.0 (I40) also known as smart manufacturing, together with advanced manufacturing techniques, has been introduced in the industrial manufacturing sector to improve and stabilize processes. Nevertheless, practical applications of these advanced technologies are still in their early stages resulting in slow adoption of the I40 concepts, especially for small- to medium-scale enterprises (SMEs). This paper proposes the design of an experimental method to integrate the practical use of Industry 4.0 in a small bottling plant; especially by detecting early faults or threats in conveyor motors and generating accordingly a predictive maintenance schedule. Using advanced programming functions of a Siemens S7-1200 programmable logic controller (PLC) controlling the bottling plant, vibration speed data is monitored through vibration sensors mounted on the motor and an efficient predictive maintenance plan is generated. The running PLC communicates with a supervisory control and data acquisition (SCADA) graphical user interface (GUI) which instantaneously displays maintenance schedules and allows, whenever required, flexible configuration of new maintenance rules. This paper also proposes a decentralized monitoring system from which vibration speed states can be monitored on a cloud-based report accessible via the Internet; the decentralized monitoring system also sends instant email notifications to the intended supervisor for every maintenance schedule generated. By its results, this research shows different possibilities of the practical use of Industry 4.0 basic concepts to better manufacturing operations within SMEs and opens a path for more improvement in this sector.