Sustainability is now a business imperative for manufacturers.
Energy use has a direct impact on operating costs and long-term competitiveness for manufacturers world-wide. It also has a wider consequence. The way manufacturers manage resources has repercussions that extend well beyond the factory floor.
The scale of the opportunity is significant.
In Ireland, manufacturers accounted for 17.7% of final energy consumption in 20241, representing 25.4 TWh of energy demand.
Across the EU, greenhouse gas emissions from manufacturing fell by 16% between 2015 and 20252. That is meaningful progress and also reflects how much focus is already being placed on reducing the environmental impact of industrial activity.
The regulatory environment is reinforcing this direction. Under the EU’s Corporate Sustainability Reporting Directive, companies within scope are required to report on sustainability-related risks and impacts, including climate-related information. This increases the importance of having reliable operational data behind sustainability reporting and decision-making.
For manufacturers, better operational insight can help turn that ambition into practical action.
Production data can help teams understand:
- where energy use is highest
- where process performance is creating unnecessary consumption
- where operational changes could reduce energy demand
Better visibility gives manufacturers a stronger basis for action.
Applying AI to an energy-intensive process
DMI recently worked with a global industrial company to explore how artificial intelligence could improve operational efficiency and support more informed decision-making.
By applying machine learning to manufacturing data, the project demonstrated how AI can improve the accuracy of energy-related predictions and reduce delays in operational feedback.
The solution achieved over 90% prediction accuracy and eliminated a feedback delay of more than 30 minutes, giving operators much faster insight into process performance and a significant reduction in energy consumption.
The results highlighted the potential for manufacturers to move beyond simply monitoring energy consumption towards using their data to identify opportunities for measurable improvement.
By applying AI, the organisation achieved multi-million-euro savings through reduced energy consumption. The solution achieved a prediction accuracy of more than 90%, while a feedback delay of more than 30 minutes was eliminated from the process.
Turning operational data into action
As manufacturers generate more operational data, technologies like machine learning can help uncover patterns that would otherwise be difficult to identify. Real-time analytics can then support faster decisions on the factory floor.
The value comes from applying these technologies to clearly defined operational challenges.
At DMI, we work with manufacturers to understand where those opportunities exist. We help test and validate digital solutions in real production environments, giving organisations the evidence they need before scaling them more widely.
The potential is already being demonstrated at scale
Siemens’ manufacturing site in Fürth, Germany, was recognised by the World Economic Forum as a Sustainability Lighthouse after using digital technologies to significantly improve its energy performance. The site achieved a 64% energy savings per unit of production, while increasing production output by 145%3.
The factory uses extensive energy monitoring and digital systems to understand where energy is being consumed and identify opportunities for improvement.
Examples like this demonstrate the scale of what can be achieved when operational data is used effectively.
Better insight enables better decisions
As energy costs remain a major concern and sustainability expectations continue to increase, manufacturers will need greater visibility across their operations.
Better insight enables better decisions, and in energy-intensive manufacturing, those decisions can have a measurable impact on both business performance and energy consumption.
From insight to measurable impact
Manufacturers already have access to growing volumes of operational data. The opportunity is to use that data more effectively to understand where meaningful improvements can be made.
The examples from Siemens and DMI show what this can look like in practice. When digital technologies are applied to clearly defined operational challenges, they can reduce energy demand and strengthen manufacturing performance.
For manufacturers, the next step is greater visibility across operations and a clearer understanding of where digital solutions can deliver measurable value.
At DMI, we help manufacturers identify those opportunities, test solutions in our accelerators on-site in Limerick and build the evidence needed to scale what works.
- Sustainable Energy Authority of Ireland (SEAI), 2024 Energy Statistics
- Eurostat, EU Economy Greenhouse Gas Emissions, 2026
- Siemens, Fürth Sustainability Lighthouse
