Industrial AI in action: from pilots to deployment

Industrial AI uses artificial intelligence to improve manufacturing processes. By analyzing production data, it helps manufacturers predict breakdowns, reduce waste, use workers’ time better, and improve product quality.

Orgalim members develop and use these technologies in their own factories, work together with others such as Amazon and Microsoft with their AI knowhow, and expand their use with partners and customers.

Examples deployed by Orgalim membership

Agentic AI 

Agentic AI is made of “agents” that can plan and execute multi-step tasks autonomously to achieve a specific goal with limited human supervision. Bosch Manufacturing Co-Intelligence is currently used for shopfloor troubleshooting and workforce scheduling; Bosch reports around €0.85 million per plant per year in quality-cost reductions and up to €2 million per plant per year from scheduling optimisation. Siemens is enhancing its generative-AI tools with agentic AI, with its copilot already used internally and tested by 100+ companies across a wide range of industrial sectors. 

Industrial Copilots

Industrial Copilots are AI assistants built into industrial tools. They support workers by explaining information or generating code, while humans remain in control of decisions and actions.

  • ABB’s Genix Copilot supports predictive maintenance and shop-floor operations. It has increased asset reliability by up to 20%, reduced unplanned downtime by 60%, and cut troubleshooting time by up to 80%. In one factory, first-time-right production rose from about 30% to over 80%.

  • Schneider Electric’s copilot, part of the EcoStruxure platform, helps engineers configure and modify systems faster by generating code and documentation and supporting legacy systems. It has reduced configuration work by up to 50% and shortened line changes from weeks to hours.

Domain-specific tools

There are also many tools designed to solve specific problems. For example, FESTO AX uses AI to detect problems early and improve maintenance, quality, and energy use. In some cases, it has reduced downtime by up to 25% , saved up to €30,000 per year in energy and maintenance, and cut waste by up to €100,000 per year per production line in semiconductor factories.