Siemens and Merck
Making machines talk to each other better
Siemens and Merck want to enable machines to communicate more and better with each other in order to ensure the quality of manufactured products.
Merck and Siemens are aiming for a complete solution in which customers can rely on a central, non-manipulable data source from production to quality control in the laboratory. Siemens plans to build an object-centric IIoT data ecosystem in which objects can exchange data in a trusted and secure environment. The partners also want to combine Merck's crypto-anchor technology portfolio with Siemens' proven traceability system (Trusted Tracebility) (an end-to-end system that can be used to track the product family tree) and enable their seamless interaction using blockchain technology. The first pilot projects are set to begin next year. The solution should be scalable and can be used along the entire value chain.
"Value chains and product life cycles must become more transparent and sustainable. Together with Merck, we will develop a completely new digital solution that allows machines to communicate with each other in a trustworthy manner and exchange production and laboratory data, for example," said Siemens Executive Board member Cedrik Neike. Customers could increase the efficiency of their production and at the same time ensure the sustainability and quality of their products in many areas.
The technology is likely to be of particular interest in sectors where quality control plays a major role, such as the food and beverage and pharmaceutical industries. However, other areas are also conceivable. "We see clear potential in our cooperation with Siemens to fundamentally change quality control and assurance in a wide range of industries," said Laura Matz, Chief Science and Technology Officer at Merck.
In cheese production, for example, the system could link data from production - whether the system has been rinsed or how long the milk has been heated - with results from laboratory tests on germs. Data from the supply chain could also be added - such as which farmer the milk comes from and when the tanker truck was cleaned.
The combination of this data should also facilitate new business models in which people no longer pay for a plant or machine, but for its performance. To stay with the cheese example, for example, payment would be made for how much cheese of what quality was produced.










