AI for Resource and Process Efficiency in Plants

Packaging production relies on energy, water, raw materials, consumables and maintenance, and small inefficiencies quickly add up to cost and emissions. We already collect some machine and consumption data, but we lack tools that translate it into concrete actions.

We are looking for AI‑based solutions that analyse data from meters, machines, sensors and production systems to detect anomalies and recommend improvements. Examples include identifying lines or shifts with abnormal energy or material use; highlighting patterns behind scrap and rework; suggesting better machine settings or maintenance windows; or simulating the impact of process changes, new equipment or on‑site generation. We are open both to pure software working on existing data and to solutions that add targeted low‑cost sensing where it really creates value.