Artificial Intelligence

Artificial Intelligence To Drive Intelligent Production – Metrology and Quality News


Big data and AI give Industry 4.0 a huge boost. Intelligent software solutions can use the high volumes of data generated by a factory to identify trends and patterns that can then be used to make manufacturing processes more efficient and reduce their energy consumption. This is how plants are constantly adapting to new circumstances and undergoing optimization with no need for operator input. And as the level of networking increases, the AI software can learn to “read between the lines,” which can lead to the discovery of many complex connections in systems that aren’t yet or are no longer evident to the human eye. Intelligent software with sufficiently intelligent analytical technology is already available. But whether data processing is performed using a cloud solution or at the local level (for example, using Edge computing) will depend on the user’s requirements. Data on an Edge platform is available more quickly and at a higher resolution, whereas a considerable amount of computing power is available in the cloud. In many cases combining edge and cloud computing  is required to benefit from both worlds.

MindSphere, the cloud-based, open IoT operating system from Siemens, can be used to link products, plants, systems, and machines. It is one of the most important foundations enabling the use of AI in industry. MindSphere performs extensive analyses to make the vast amounts of data generated by the Internet of Things (IoT) useful for optimization, simulation, and decision-making.

The digital twin enables virtual testing of a variety of scenarios and promotes smart decisions in areas such as optimizing production. In the future, using a digital representation of a machine tool and the associated manufacturing process, AI will be able to recognize whether the work-piece currently being manufactured meets quality requirements. Moreover, it determines the production parameters that need to be adapted to ensure that this remains the case during the ongoing production process. As a result, production is made even more reliable and more efficient and companies even more competitive.



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