Requirements for the skilled workers of tomorrow

In times of increasing customer demands and global competitive pressure, automation is indispensable. But as promising as the added value provided by automation is for entrepreneurs, many skilled workers are having to rethink.

They no longer spend years working on one or more machines that they know inside out and whose quality they are completely responsible for. Employees no longer grow with the experience on a machine, but rather they are responsible for processes in the machine park. In doing so, they do not actively intervene: they look after the machines, which independently ensure quality, and are supported by assistance systems.

The systems help to optimize production processes, diagnose faults or carry out maintenance. Thanks to robotics and digital assistants, the skilled workers can concentrate on activities with high added value and simple tasks are completely taken over. The robots thus play a key role in relieving the burden on skilled workers.

Significance of “classic” robotics: With the investment costs of state-of-the-art machine tools, small and medium-sized companies can no longer afford to work in two shifts as they used to. Robots enable unmanned night shifts as well as unmanned weekends – so that companies in high-wage countries remain competitive in the long term.

Creativity and innovative thinking are required

Industry 4.0 is not intended to replace skilled workers, but to relieve and support them. Machines are more suitable for fast and precise routine work than for tasks that require emotion or creativity. This is where the great advantages of automation lie: people now have more time for work at a higher level of the value chain.

Human creativity and innovative strength is more strongly demanded when the professional profile of the skilled worker changes. Physically, they are almost no longer required at all, but must be flexible, mobile and conscientious in order to meet the new demands of the working world: Causal processes that were previously clearly comprehensible are becoming increasingly complex processes that need to be planned, supported and mastered.

Systems with independent machine intelligence, self-optimization and predictive analysis capabilities occupy a special place in these processes: a machine is no longer simply given commands, skilled workers interact with it as if it were a colleague. This too is a change that must be adapted to.