Predictive maintenance is a preventative maintenance method used to monitor the performance and health of a hydraulic system. This method allows to identify expected malfunctions of the system in advance and prevent potential problems in advance. Here are some common techniques used to provide predictive maintenance on hydraulic systems:
System Monitoring and Analysis: Sensors are used to continuously monitor the performance of hydraulic systems. By monitoring various parameters such as pressure, flow rate and temperature, possible problems in the system can be detected in advance. Analysis of this data provides valuable information about the state of the system.
Oil Analysis: Regularly analyzing the hydraulic oil used in hydraulic systems provides information about wear, pollution or chemical changes in the system. These analyzes evaluate factors such as metal particles, water content and chemical composition in the oil.
Thermal Monitoring: Overheating problems in hydraulic systems often cause malfunctions. Temperature changes in the system can be monitored using thermal cameras or thermometers. Abnormal temperature increases may indicate a potential problem.
Vibration Analysis: Abnormal vibrations in parts such as hydraulic pumps, motors and valves can often indicate malfunction. Vibration analysis can identify problem parts by monitoring and analyzing such vibrations.
Visual Inspection and Inspection: Visual inspection of the system is important to detect obvious problems such as leaks, loose connections, corrosion or other obvious problems. Such checks should be carried out as part of regular maintenance routines.
Scheduled Maintenance and Repair: It is inevitable that certain components in hydraulic systems will wear out over time. Therefore, periodic replacement or maintenance of certain parts is a preventive measure.
Predictive maintenance increases the reliability of hydraulic systems, reduces operating costs and minimizes unexpected downtime. Therefore, it is a widely used maintenance method in industrial applications.
The concept of Industrie 4.0 or Industrial Internet of Things is still new and spreading in major industries with significant investment programs to improve performance, ensure competitiveness and increase value. It is a process that also is revolutionizing traditional maintenance towards smart Predictive Maintenance, allowing to perform services just in time. Real-time machine status information, through remote monitoring and data expertise, significantly increases the availability of equipment, reduces downtime and extends the life of the machine, fluids and components. Predictive Maintenance is thereby a tool to also change business models and offer new after-sales services. It additionally enables manufacturers to offer their machines as a service instead of regular sales.
Figure 1: Critical condition changes
ARGO-HYTOS has developed ground breaking solutions for the online monitoring of fluids. These intelligent measurement systems use smart algorithms to monitor the aging of lubricants and the wear of hydraulic components. ARGO-HYTOS measurement systems detect problems at an early stage, before these cause further damage or downtime.
The smart predictive models developed by ARGO-HYTOS are based on machine-specific learning, allowing to evaluate the time remaining before failure and to plan maintenance accordingly.
Figure 2: Structure of a remote oil condition monitoring system
Smart Predictive Maintenance: allowing to perform services just in time.
Argo-Hytos measurement solutions have proven their benefit in a wide range of applications, from remote monitoring of mobile equipment (e.g. agricultural, construction, material handling), to power generation and distribution (e.g. wind turbines, gas turbines, water power, gearboxes, fuel storage & transport, transformers), machines (e.g. injection molding, presses, welding, grinding) and many more.