Why equip all of your machines with energy meters if you just want to optimise your industrial site’s energy consumption? Your factories already have a lot of data to work with to start saving energy. You simply need to know what data you need, where to find it and how to mine it. Blu.e by Engie has some handy tips.
“Contrary to popular belief, measuring the energy consumption of each machine will not, in itself, help you save energy in a factory,” says Antoine Roland, energy engineer at Blu.e. “You generally need to correlate the energy consumption figures with factory productivity, and factor in parameters that will affect industrial activity, such as the production rate, machinery running condition or the weather.
In the end, energy data represents less than 10% of the data we use.” It’s good to know that this data is available without having to invest in new meters. Each machine naturally supplies a wealth of information, but factory owners generally have no idea how useful it can be for saving energy.
Production and maintenance data are your best allies
Factory production lines, for example, provide access to a plethora of production data, such as the volume and variety of products manufactured, or parameters such as temperature, pressure and machine throughput. These can be used to calculate a key performance indicator, “specific energy consumption”, which is expressed as the number of kWh used per unit of finished product.
Another essential parameter for optimising energy consumption can be found in the maintenance data yielded by machines equipped with machine-wear warning systems.
Use external data to control the process
But that’s not all: weather conditions, commodity prices, finished-goods prices and the staff leave calendar can also affect the pace of factory operations and so play a role in specific energy consumption. “This non-machine-related external data is a good indicator of whether the factory is operating to capacity,” says Antoine Roland. “It also makes it possible to adjust settings in real time to factor in the weather or the factory’s headcount. For example, the time taken to heat a furnace, hence the amount of energy used, will not be the same in mild weather as in freezing weather. The factory owner will adapt the machine settings to the broader context.”
Cross-reference energy data to boost performance
These three types of data – production, maintenance and external data – can be aggregated, cross-referenced with energy consumption readings and shown on the same dashboard. Analysing the results obtained will then help optimise the factory’s energy performances: “If the number of kWh consumed per unit of finished product varies with the throughput, the opening of a valve or the condition of an automatic control unit, for instance,” explains Antoine Roland, “we know that these are the parameters we need to adjust for best results.”
Better still, factory owners looking to improve overall performance will find many other benefits to be gained by studying and analysing data. For example, data can be used to:
- justify a machine purchase on the basis of actual data and calculate the return on investment;
- see when a parameter is veering off-course and anticipate maintenance operations;
- take external factors such as the weather into account when forecasting the factory’s activity levels, so as to constantly fine-tune production strategies;
- help a facility improve by comparing its results with those of other factories in its group.
“It’s an excellent way to boost emulation and improve performances across the company!”, concludes Antoine Roland.
About a real-life example: our article “MINATEC: Targeting -10% less energy for the production and distribution of utilities”