Energy is one of the most significant costs in any industrial plant and, paradoxically, one of the least managed using actual data. Most companies know how much they pay on their monthly electricity bill, but they do not know which machine, process, or shift is responsible for which part of that consumption. Without that granularity, optimization is impossible.

IIoT allows for the installation of energy meters at relevant points in the facility, connecting them to the cloud to obtain real-time consumption with the level of detail you need: by line, by machine, by shift, or by product reference. With this information, savings opportunities stop being assumptions and become actionable data.

Why is industrial energy consumption so difficult to optimize without data?

The fundamental problem is that the electricity bill aggregates all consumption into a single number. It does not tell you if the compressed air compressor consumes 30% of the plant’s total energy while running idle during the lunch break. It does not tell you that a specific machine consumes twice as much as expected because it has a degraded motor. It does not tell you that the night shift starts equipment an hour earlier than necessary.

These inefficiencies exist in practically every industrial plant. The difference between those that correct them and those that do not is simply having (or not having) the data to see them.

The main culprits of hidden energy consumption

Equipment running on standby

Many industrial units consume a significant fraction of their rated power even when they are not producing. Compressed air compressors, HVAC systems, industrial ovens, hydraulic pumps… If this equipment remains on during stops, shift changes, or holidays due to a lack of automation or visibility, the cumulative cost is substantial.

Degraded electric motors

A motor that has lost efficiency due to bearing wear, insulation deterioration, or inadequate lubrication can consume 10–15% more than its nominal specification. Multiplied by the annual operating hours and the cost per kWh, the economic impact is considerable. And it is not detectable without monitoring.

Unmanaged power peaks

In industrial electricity tariffs, power peaks (the maximum power demanded in a short period) incur a cost in the power term of the bill. Staggering the start-up of large equipment to avoid simultaneous peaks can significantly reduce this cost without any investment in hardware.

Compressed air

Compressed air is one of the most inefficient energy vectors in industry: on average, only 20–25% of the electrical energy consumed by a compressor is converted into useful work. Distribution network leaks (which can represent 20–30% of the compressor’s output) and oversized equipment are the primary sources of inefficiency.

The energy optimization process with IIoT

Step 1: Instrument and connect

Install energy meters at relevant points (machine panels, production lines, utilities such as compressors, HVAC, or lighting) and connect them to the cloud via an IIoT gateway.

Step 2: Establish the baseline

Once the data flows to the cloud, the first objective is to understand the current consumption profile: how much each piece of equipment consumes per production hour, how much during downtime, and what the distribution of consumption is throughout the day and week.

Step 3: Identify inefficiencies

With the baseline established, data analysis allows for the identification of anomalous patterns: equipment consuming power in the early hours when there is no production, machines whose consumption has gradually increased in recent weeks, or processes with consumption per unit much higher than the reference.

Step 4: Act and validate

Improvement actions (modifying start-up sequences, scheduling automatic shutdowns, planning the replacement of degraded motors) are implemented and their impact is validated directly in the consumption data. Savings are quantifiable and attributable to specific actions.

How much can be saved?

Well-executed industrial energy efficiency projects achieve reductions of between 10% and 30% in energy consumption. In a plant with an annual electricity bill of 500,000 euros, this represents between 50,000 and 150,000 euros in savings per year. The investment in instrumentation and the IIoT platform is typically amortized in less than 12 months.

Do you want to know what part of your electricity bill you can eliminate? coppioT connects your energy meters to the cloud and provides the data to act. Request a demo.