The future of manufacturing

...is autonomous.

Virtual machine operators and a rapid increase in the degree of autonomy in production

Quality assurance in manufacturing is one of the work steps that is currently still very time-consuming and prone to error. In addition, inspection of workpieces separate from the production process is resource-intensive and there is an increasing shortage of qualified workers.

By merging the production and quality process using existing data, it is possible to intervene in production control at an early stage. Manufacturing processes can thus be controlled automatically. As a result, fewer scrap parts are produced from the outset, machine operators have a lighter workload and process cost overheads are also reduced.

The white paper on "The Future of Manufacturing" uses the example of metal machining to show how a significant increase in added value is possible across the entire product life cycle.
Further information on this topic can also be found in our blog under "Data-driven process control". It addresses the challenge of automatically controlling complex physical systems and how this is possible using a data-driven approach.

If you have any questions about advanced manufacturing, please contact our specialist directly.

Fill out the form now and receive the white paper:

Due to their very nature, precision applications such as metal cutting require a sophisticated quality assurance process. Coordinate measuring machines in separate measuring rooms or in shop floor-compatible at-line cells are usually used for this purpose. The problem with this: bulky intralogistics, time investment and personnel requirements.

In the white paper, we present a solution that directly links the quality process with the production process, resulting in high value creation potential.

You will receive our white paper as download after completing the adjacent form.

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Kai Schoppe Key Account Manager Manufacturing Solutions

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If you want to have more information on data processing at ZEISS, please refer to our data privacy notice.