INDUSTRY FOCUS Automotive Supply Chain
Keeping car plant robots working
with condition-based maintenance In this article we look at how condition-based maintenance ensures automotive production line robots receive the care they need to remain in good working order
W
ith robots playing a vital role in so many production line processes in automotive
manufacturing, it is vital that each of them is at peak condition, to prevent production disruption and failure. There are many factors that can lead to robot performance problems, including its age, long ‘mean time til repair’ periods, and the way it is programmed and used. Predicting wear and tear on robots and their parts is not an easy process, especially when there may be several hundred robots in use.
The challenge can be successfully met
through condition monitoring, a process that constantly gathers data on the operation and performance of equipment to assess its maintenance needs. Designed for customers with large
fl eets of robots, ABB has launched a new condition-based maintenance service, enabling the creation of a customised preventive maintenance schedule. This can be for either individual robots or a fl eet, as used in a car plant. Based on real-time operational data, it allows automotive robot users to optimise productivity and minimise downtime.
Condition-based maintenance works by gathering motion data on the operation of each robot to help identify any potential issues that could aff ect its performance: duty factor, speed, torque, gearbox wear, and more. The data doesn’t exist in isolation – instead it is compared with a 14-year-old database of other ABB robots across the globe, to calculate when or if a particular robot is likely to develop a fault or fail. Monitoring also minimises the likelihood of premature failure and extends the mean time between failure (MTBF) rate, as well as prolonging the operational life of the robot.
Insights maximise performance Based on this information, robot users gain the insights needed to create a preventive maintenance schedule, to help keep robots in good working order and to maximise its performance. The service can advise
32 October 2021 | Automation
whether any remedial action is required, either a repair or a replacement of any aff ected parts. This allows spare parts to be purchased at the right time, ensuring they are available and not take up space by being held in stock for extended periods. As well as better budget management, this ensures the car plant has the correct resources on hand to plan in advance when the repair needs to be performed, reducing the risk of unplanned downtime. Deciding on exactly which preventive
measures to take is achieved through a report provided for each robot. This includes a colour-coded summary table that clearly indicates the status of each axis and the overall health of the robot indicated by the calculated joint usage score. Also included are data analysis, individual maintenance recommendations, conclusions and ratings of the system. Two levels of analysis are provided: Level 1 gives a factual overview of the customer’s installed base and identifi es the most stressed robots in the plant. This gives the customer a detailed overview of how robots are used in the plant. Level 2 analysis further investigates the robots selected at Level 1, giving the customer a detailed knowledge of the most “stressed” robots in the plant. This prevents the risk of unexpected gearbox breakdown in production and gives recommendations about how to deal with these stressed robots. The report enables the customer to best develop the appropriate maintenance schedule, and ABB can also help in this if needed.
The Level 2 report also helps defi ne the budget for spare parts and supports the plant’s strategy to upgrade its robot fl eet. By making maintenance and repair
more predictable, condition-based maintenance helps automotive plants eliminate unexpected robot downtime caused by failures or delays in obtaining spare parts. Through identifying which robots are over-utilised, compared to others in a production line, users can also better understand exactly which robots may have an increased risk of component failure.
On the road to improvement With drivers demanding ever more bespoke vehicle models and options, ensuring that robots continue to work for the maximum amount of time is key to maintaining the extreme fl exibility of the modern car plant – condition-based maintenance is a vital tool in ensuring that car manufacturers stay competitive in a rapidly-changing industry.
CONTACT:
ABB
www.abb.com
automationmagazine.co.uk
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