WHY OVERCOMING SILOED DATA POSES A CHALLENGE
• Legacy systems and infrastructure: Manufacturing often relies on a mix of legacy and modern systems, making it challenging to integrate data across platforms that were not designed to communicate with one another
• Diverse data formats: Different departments like production versus supply chain generate and use data in varying formats and structures, complicating efforts to unify and standardise
• Limited interoperability: Equipment and software from multiple vendors often lack seamless compatibility, creating silos
• Resistance to change: Employees accustomed to established workflows and systems may resist adopting new technologies or processes
• Data ownership and privacy concerns: Departments or teams may guard their data due to concerns over ownership, security, or competitive advantage, hindering collaboration
• Lack of strategic vision: Organisations without a clear, company-wide data strategy often fail to prioritise integration efforts.
“ We’ ve worked together to provide manufacturers with the digital infrastructure to centralise their data, making it accessible for AI applications across the production lifecycle,” Fabien says.“ One example is the Manufacturing Data Engine( MDE), a cloud platform that stores and analyses data from factory machines, enabling faster and more efficient operations.”
First launched in 2022, MDE functions as a centralised data repository, aggregating information from factory sources and processing it for analysis. The platform integrates with Google Cloud’ s AI and machine learning tools to support