Optimisation of processes in Industry 4.0 is based largely on analysing data collected in real time using sensor technology. This needs to be evaluated using data mining based on algorithms so as to highlight the potential for optimisation. Using micro control systems as early as the product development phase offers opportunities to define a variety of areas for action and to collect and interpret data.
Development of new 4.0 products is based on process data and expert system data evaluation. This evaluation gives detailed information about process-based influences and mechanical weaknesses. A data model is created at the start of every new product development. A large measure of reliability is then provided by a simulation that takes into account processes, their active and reactive elements, and known or previously only simulated potential consequences of reactions.
Product optimisation is largely concerned with predictive maintenance. Expert systems play a crucial role in this area. Here, too, it is algorithm-based data evaluation that makes it possible to identify faults and influencing factors at an early stage. Ensuring errors are eliminated before they become a reality is a key principle that involves a large volume of knowledge.
The drive for creative destruction and constant innovation is generated by this continuous balancing act between product and process.
Reference: Industry 4.0, A white paper by SEW-EURODRIVE
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