Unlock the Potential of Predictive Quality Control Across Your Manufacturing Sites
Achieve Consistent Quality Output & Efficiency and Break Down Data Barriers with Katulu
Predictive Quality Control: Improving Manufacturing Processes Across Sites
As a global manufacturing company, ensuring consistent quality and output across all production lines at all sites worldwide is a challenge. However, to improve overall equipment effectiveness (OEE) across manufacturing sites, sharing data between sites is essential, but often falling short due to IP protection as well as export control laws. A single site can not caputure sufficient data to implement predictive quality control, which requires large amounts of data. We have found a way to create quality synergies between sites without sharing any data and to comply with legal export control laws. Our platform bridges the data barriers between manufacturing sites to enable the use of AI across sites, while all sensitive data remains securely on-site. With our platform predictive quality control can be applied across various industries at global scale including manufacturing, automotive, aviation, energy and semiconductor.
Challenges of consistent quality across sites
Predictive quality control at global scale only works with the right technology partnerEvery production line is different due to multiple machine suppliers, several machine generations, as well as regular machine and process setup changes. Making it even harder to capture sufficient data for predicting quality issues. Furthermore, export control laws forbid the sharing of production data of various electronic and industrial goods, especially those classified as dual-use. In some countries, like China, export of data is forbidden altogether. These legal constraints prevent sites from collaborating across countries to overcome the lack of data.
How do we solve it?
Bridging data barriers with KatuluOur platform bridges the data barriers between manufacturing sites and enables the use of AI across sites while keeping sensitive data securely on-site. It allows local AI models of one site to be used globally with only three lines of code and enables the training of models directly at the manufacturing site - all the while staying compliant with export control laws and regulations. The combined learning from all sites results in robust optimizations that accounts for material variations, different machines, machine layouts, and processes. With our built-in support for edge devices from Siemens and Bosch Rexroth you can connect your site in seconds and data is no longer a limiting factor in predicting quality issues. Manufacturers use our technology for highly accurate predictive quality control across all sites worldwide and transfer best practices to all production setups for consistent quality, output and availablity.
How can you benefit?
Predictive quality control as competitive advantage across sitesOur solution not only provides peace of mind, but it also offers a competitive advantage across sites. You no longer need to worry about data access at site and export control or privacy laws as there is no need for direct data access. You can create synergies between all your manufacturing sites no matter where they are located. Leverage all your data across all sites to improve and predict quality issues before they happen.
Get started with Katulu today
Take the first step in improving quality across your global manufacturing sites. Request a chat with us to learn more about Katulu's capabilities to predict quality issues at scale.
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