Elmec Group: energy monitoring and OEE in sheet metal processing

The context

Founded in 1989 as a craft workshop dedicated to industrial assembly, Elmec Group is today a structured industrial group spread across several sites and specialising in the processing of rolled metal: from joining the Perdieci holding company in 2022 to the merger with Carpelab in 2024 and the acquisition of NordLog in 2025. As the group grew and its machinery multiplied, Elmec came to need more granular visibility over consumption and performance: putting an objective figure on what happens in the department, to turn energy and production data from an undifferentiated cost item into a lever for efficiency. Behind that need lay a broader one: building a solid data foundation from which to develop OEE calculation, maintenance management and job costing.

The project

IDA starts where many management systems stop: with consumption monitoring. The project followed exactly that logic, measuring the draw of the various utilities, electricity, compressed air and technical gases such as nitrogen and oxygen, together with the consumption of individual machines. The result is a structured database from which any kind of dashboard can be generated, such as the productivity and OEE dashboard, an indicator the company had never had.

The results

With IDA, Elmec moved to management based on verified data, and the results arrived quickly. Compressed air emerged as the plant's largest item of electricity consumption, around 66% of the electrical total, with compressors left running at all times: simply scheduling a weekend shutdown, an intervention at zero cost, delivered an estimated saving of around 10,000 euros a year. The same data also turned investments into safer decisions, backed by measurable ROI: the automatic bending machine, which previously recorded an average OEE of 70% over a 12-hour shift, today reaches 85% running 24 hours a day, with peaks of 38 continuous hours. Entirely on its own, Elmec has also integrated Claude, Anthropic's AI, with IDA to create custom dashboards for management: from the weekly reports, the AI generates tailored visual summaries that can be consulted on a smartphone too.

The next step is to extend the project to the Verona plant to compare the performance of the two sites, bring the data into the department on real-time screens and move on to production costing: assigning a cost item to each processing stage, up to ten for a single job, linking it to machine consumption and operator cost.