The SIGNN project establishes international, interdisciplinary doctoral network that aims to address critical challenges faced by Europe’s manufacturing industry, including global competition, supply chain disruptions, rising energy costs, and evolving regulatory landscapes such as the European Green Deal. By integrating cutting-edge engineering solutions with advancements in artificial intelligence (AI), machine learning (ML), mathematical modeling, and process optimization, SIGNN seeks to develop innovative, energy-efficient, and climate-neutral solutions to transform industrial operations. The project leverages a unique interdisciplinary consortium of eight leading academic institutions and sixteen industrial partners spanning diverse sectors, from technology provision to process industries and supply chain management. SIGNN is structured around three research objectives: advancing data-driven industrial modeling, enhancing process monitoring and fault detection, and innovating decision-making systems through optimization and control. Complemented by an integrated doctoral training program, the initiative prioritizes cross-sectoral collaboration, equipping researchers with technical, entrepreneurial, and interdisciplinary skills to foster industrial innovation and sustainable practices. Ultimately, SIGNN aims to strengthen Europe's innovation capacity, ensuring a robust pipeline of highly skilled professionals to drive the continent’s transition toward digitalized, smart, and sustainable manufacturing.