Improving uptime in industrial robotic systems: Page 2 of 6

October 05, 2018 // By Clemens Müller
Machine maintenance can sometimes seem like a black arts. A seemingly reliable machine suddenly stops working and, despite everyone’s best efforts, cannot be brought back to life. Along comes a member of the maintenance team and, after some beard scratching, tinkering inside the machine and a few words of encouragement, the machine springs back to life.

The Goldilocks zone of maintenance

With the continued roll-out of Industry 4.0, plant managers are being offered an ever-increasing amount of data about their manufacturing locations. Internetworked systems and the data sharing it enables provide continual feedback on manufacturing or process status. Sensors are primarily focused upon either monitoring the process, such as temperature, pressure or volume, or safety, whether a valve is operational or a safety door is locked.

Stored data from these sensors can also be used for a hindsight analysis of what went wrong. If the time taken to empty a tank gradually took more time over a period of weeks, this knowledge could be used to determine an improved planned maintenance schedule for the tank’s outlet valve.


Fig. 2: The aim of the maintenance team is to sit in
the Goldilocks zone – the optimal balance between
too much scheduled maintenance downtime and
the impact of too little.

One of the advantages of our maintenance team members is their uncanny ability to sense when something is about to go wrong. Humans draw upon all their senses and, when a machine doesn’t quite sound right, or seems to visibly judder a little too much, their gut instinct kicks in. Invariably they are correct in their instinct, sometimes managing to avoid significant downtime and the financial losses that would otherwise result from unplanned maintenance.

It is not inconceivable that affixing additional sensors to manufacturing equipment could help improve predictive maintenance. The aim here is to ensure that there is not too much preventative maintenance downtime, neither too much unexpected downtime – rather the balance should be just right.

 

The goal of these sensors is to monitor the machinery itself during operation to detect the changes that are signs of a pending failure. For example, by simultaneously monitoring current consumption, temperature, noise and motion, wear-related damage could be pre-empted in robotic joints.

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