Maintenance has become much more important in recent years, particularly as increasingly dynamic and complex production processes and technological opportunities have emerged. It is also an important but – in many sectors – still underused lever for optimising value creation.
Being able to avoid unplanned production stoppages results directly in increased availability. A whole range of options for doing just that are being discussed in both science and industry.
In future, the information and data captured in drive systems will be visualised in a clear, user-friendly way (e.g. trend charts) and processed by cutting-edge analysis workflows (keyword: machine learning). The concept aims to make it easy for users to keep track of how a system is actually behaving when in use and whether maintenance work needs to be carried out. Operators of these systems will have the opportunity to unlock considerable added value and tap into potential for optimisation. For example, it can provide greater transparency for the operational conditions of a drive, boost the availability of an entire system, make it easier to plan maintenance work, reduce the need to hold spare parts in stock, and create opportunities to optimise processes.
The key benefit of the concept will be significantly higher productivity. Thanks to integrated functions that have been specially customised, users will be able to avoid unplanned downtime and thus increase availability. At the same time, the continuous monitoring of characteristic features will ensure that maintenance work can be accurately planned.