Case study: early detection of robot drive failures using RSIMS system

Goals

Implementation of Predictive Maintenance methodology for early detection of robot drive failures

Reduce downtime and repair costs

Results

Monitoring and early detection of changes in signals indicating progressive wear of robot drives

Identification of faults that adversely affect the working conditions of the robot

Challenge

The subject of the project involves automatic monitoring of ten robots on three production lines. The monitoring focuses on early detection of failure symptoms by tracking anomalies in signals characterizing the robots' operation.

The challenge is to implement Predictive Maintenance methodologies that enable early detection of robot drive failures and reduce the cost of equipment downtime and repairs.

Solution

The solution used is an early failure detection system based on anomaly tracking algorithms implemented in RSIMS Apps. The results so far in the project have been achieved based only on robot sensor data provided by the robot controller (including torques, temperatures) and the machine PLC. The application runs online and the data from the client's infrastructure transmitted via https protocol using due security standards.

CASE 1 / Sensor data analysis

Overruns characteristic of the degradation of the axis 5 drive were identified in the application. The propagation of the damage was observed against the parameters of the other drives, which did not deviate from the norm, and the replacement of the robot wrist itself was carried out as planned.

Summary

The solution, based on RSIMS Modules, allowed early identification of the type of failure and replacement of only faulty components on a scheduled basis, reducing both downtime and repair costs. Without monitoring of the robot's parameters in RSIMS Apps, there would have been further propagation of failures and emergency stoppage of the robot. The costs in such a case are definitely higher, and this is related to the potentially larger scope of the overhaul and the different cost of unscheduled downtime and execution of repair work in this mode.

The estimated savings in this one case are in the range of EUR 25-35 thousand.

Benefits

Benefits to date include reduced repair and downtime costs in the event of drive failures - among others, such as those shown in the example above. An additional benefit is that, using the application, it is possible to detect and fix faults in the robot's hardware early on, which, due to the nature of the lines being monitored, have so far only been identified when they caused them to stop. An example would be faults and leaks in the pneumatics system that cause deterioration of the robot's loading conditions - prolonged operation with this type of fault contributes to earlier degradation of the drives of the most heavily loaded robot axes.

Reduction of repair and downtime costs in case of drive failures

Early detection and troubleshooting of defects in the robot's hardware along with understanding the source of the cause of the problems that are occurring

Continuous remote monitoring of equipment and reduction of unplanned downtime

About company

ReliaSol is a company established in response to the growing need to increase the efficiency of machines and installations in industry.

We provide software and services that accelerate the digital transformation process. The applications we create combine real data from machines, sensors, event reports and automate drawing conclusions. The result of their work is data visualization, event prediction and monitoring of the optimal operating range of machines and entire production lines.

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Reliability Solutions Sp. z o. o.
ul. Królewska 57, 30-081 Kraków, Polska