Photo Credit: ABB Inc. Robotics
ABB’s (Auburn Hills, Mich.) new condition-based maintenance (CBM) service enables robot users to create a preventive maintenance schedule for individual or robot fleets based on real-time operational data.
CBM uses real-time data to identify potential issues that could affect robot performance. The system compares process variables against other robots in ABB’s worldwide robot database to calculate the likelihood and timeframe of a potential fault or failure.
The tool then advises users about remedial action involving repair or replacement of affected parts. By identifying which parts are likely to fail and when, users can purchase and prepare spare parts without needing to hold them in stock, helping users plan their budgets while minimizing maintenance downtime.
To help customers decide which preventive measures to take, the software provides a report that includes the robot’s serial number as well as a summary table, data analysis, individual maintenance recommendations, conclusions and a rating of the system. Using this data, the customer can design an appropriate maintenance schedule, with help available from ABB if desired.
“By providing greater predictability around maintenance and repair schedules, our condition-based maintenance service allows customers to get the most from their robots,” says Antti Matinlauri, head of Product Management for ABB Robotics. “Customers can optimize their production efficiency by eliminating unexpected downtime caused by failures or delays in obtaining spare parts. Users will also gain a better understanding of exactly which robots may have an increased risk of component failure, for example if they are over-utilized compared to others in a production line, or if heavy payloads are causing the robot to operate outside of its recommended design parameters.”
This process monitoring minimizes the chance of premature failure and extends the mean time between failure (MTBF) rate.
ABB Inc. Robotics | 888-785-3904 | new.abb.com/products/robotics