The paths and strategies used by digitization processes in industry differ widely, yet they share a vision: a fully automated "smart factory" which is self-regulating – both as a whole and in every detail – and detects the optimum settings for each parameter to ensure maximum overall equipment effectiveness (OEE).
Companies are already taking steps towards achieving this goal through numerous individual projects. When approaching tasks of this nature, it is important to define clear goals for increasing the OEE of a machine, line or entire production system. Otherwise, companies run the risk of losing track of their overall aims. "Whether it’s reducing waste or optimizing quality – the journey is as individual as our customers," says Marco Castro, Head of Hauni Consulting.
Many goals, one path
As Castro explains, the specific tasks and measures involved in the optimization can differ significantly at the project level. "However, it makes sense for the project design to follow a set pattern. It starts with the definition of the goal. Then we proceed to identification, collection and analysis of the correct data, derivation of actual improvements from that data, checking the success of individual measures and ensuring that the optimization retains its effectiveness over the long term."
The right choice
In recent years, Hauni has equipped its machines with the sensors, network connections and visualization systems necessary for efficient monitoring. As so often, however, the devil is in the detail – or, more precisely, in the choice of details. "Our state-of-the-art M-Generation machines have a total of around 3,000 different parameters. On average, 10 percent of these – i.e. around 300 – are relevant for achieving a specific goal. An operator will usually be familiar with about 25 of them and an expert with a further 25 – that leaves another 250 parameters. Identifying these requires extremely specialized knowledge."