Building an AI-ready data architecture for SWISS KRONO
Impact
Together with SWISS KRONO, ML6 identified the different requirements for AI use cases. Few key requirements are a solid data architecture and infrastructure, multi-disciplinary teams and management/organisation support. Having these different angles in balance will help the organisation further to enable and embed use cases in its day-to-day operations. This enables every organisation to benefit from the actual output on a larger scale.
Intro to the customer
SWISS KRONO is one of the world’s leading companies in the production of wood-based materials. The group produces a wide range of products in the fields of interior design, flooring, and building materials. The company’s headquarters are located in Switzerland. SWISS KRONO counts around 5.000 employees and operates in eight different countries, including Switzerland, France, Germany, Poland, Hungary, Ukraine, Russia, and the USA.
Challenge
To ensure the right material quality for their customers and to improve the productivity and the efficiency of their production process, SWISS KRONO has the ambition to become a digital factory, transforming manual operations into digital ones. To track and to document the transformation of wood-based materials to finished goods, they implemented a Manufacturing Execution System (MES). Before scaling the implementation across different production sites, they wanted to guarantee that their efforts regarding the MES implementation are enabling future usage of AI across multiple divisions. For that reason, SWISS KRONO and ML6 collaborated to share best practices on data architecture, data mesh and enabling AI in general. SWISS KRONO realised that it is important to have an AI-ready data architecture before starting to work on specific AI projects.
Solution
In order to support SWISS KRONO in their AI journey, ML6 provided customised insights and recommendations to the company following exchanges during interviews, workshops, and collaborative feedback. ML6’s recommendations came as a set of functional building blocks so that SWISS KRONO knew how they could fit these blocks logically together. However, they were free to choose which technology they wanted to use for that purpose. ML6 wanted to propose the right balance between structure and flexibility.
Together with SWISS KRONO, ML6 identified the different requirements for AI use cases. Few key requirements are a solid data architecture and infrastructure, multi-disciplinary teams and management/organisation support. Having these different angles in balance will help the organisation further to enable and embed use cases in its day-to-day operations. This enables every organisation to benefit from the actual output on a larger scale.
Results
After an intensive collaboration with the stakeholders, ML6 provided a tangible list of principles to take into account during the future scaling of the MES. This list enables the MES team at SWISS KRONO to validate their implementation plans.