True Demand - from assumption to knowledge-based prediction
Understanding 'True Demand' is a critical challenge in electronics manufacturing, and a major point of SC4EU. When business partners forecast their chip requirements, they may not use actual demand figures, often inflating numbers to maintain larger inventories.
This can trigger a 'bullwhip effect' where small changes in demand at consumer level escalate all the way up the supply chain - which added to the recent chip crisis. For a better prediction, SC4EU employs anonymous surveys, secure data sharing, and semantic technology to gather high-quality, reliable information on the true demand. The shift from assumption to knowledge-based prediction may ensure that production is aligned with the real needs reducing the risk of surplus or shortage, thereby mitigating the bullwhip effect.
Survey - confidentially sharing data for a smarter production
The SC4EU project uses a survey as a key tool to get a clear picture of the real needs in the semiconductor market. As part of the True Demand approach, the survey is designed to collect honest information from companies about how many chips they actually need.
It is an opportunity for businesses to share their data confidentially, anonymously, and without disclosing or giving away any secrets. It is a tool for the entire industry to operate more cost-effectively through better planning and avoiding waste. Providing true demand data, the survey will help companies across Europe to make smart decisions in their chip production.
Digital Reference - common language for an entire ecosystem
SC4EU will take Digital Reference (DR) to new heights. As a Semantic Web based data model and its ontologies, a DR platform for the complete industry acts as a universal vocabulary in the complex world of semiconductor supply chains.
In essence, it is a vast library of terms and definitions, which everyone can understand and use. With this common language, companies can communicate and collaborate more effectively, ensuring safe and secure data sharing concerning chip needs or production processes. Since DR proved to be ideal for discrete data handling and precise planning in the previous projects, it will be refined and expanded to an entire ecosystem that includes ontologies and knowledge graphs from all entities in the supply chain. As a common comprehensive vocabulary, the cutting-edge solution has the potential to set standards for the future semiconductor industry.