The Blog of operational excellence and energy management for industry


Browse our articles, expert advices and clients testimonials: our experience save your time!

Organise your energy data to the right level of detail

Each function in a factory handles its data in its own specific information system: production, for example, uses SCADA and building automation systems, the energy department uses Excel, while maintenance uses CAMMS. Not only is the data not shared, it is also recorded at different time increments: just think of gas consumption in a workshop, weather data, plant working/idle status, steam flow rate or production scheduling… So how can the data be aligned? And how can the data then be used to boost energy efficiency? At Blu.e, the data engineer collects, cleans and classifies raw energy data, which the energy engineer then converts into a meaningful form that can be used to guide operational management. Read on to learn how it works.

 

“Take the example of a car manufacturer whose workshops are fitted out with 10,000 meters and sensors,” suggests Quentin Bonnand, energy engineer at Blu.e.“The data they yield becomes meaningful when it is organised with a view to achieving energy efficiency.”

The manufacturer divides the data into four categories:

  1. External data such as weather conditions and energy prices;
  2. Internal energy data obtained from the building management system: electricity and other utility meters;
  3. Data from supervision processes. For example, the air speeds and hygrometry in paint booths must be maintained consistently within very narrow ranges of values to ensure proper application of the paint.
  4. Operating events: plant operation or downtime, alarms, etc.

Each of these data sources will require specific processing operations to produce a database and indicators that are meaningful for the operational staff. For example, electricity meter indexes, which are recorded every minute, are not meaningful as they stand. However the difference between these minute-by-minute indexes is meaningful in that it reflects a production line’s electricity consumption at that instant.

 

Choosing the right time increment: second, minute, hour, day or week?

If the aim is to optimise plant performance, it’s not enough to know how much energy is being used at a given point in time. You will need to be able to see how the indicators vary over time. “It’s important to choose the right time increment for the data being examined and especially the intended purpose.”

Consider these three examples.

  1. For Management, who wants to know how much energy its sites are using, weekly or monthly reporting is sufficient to check whether they are exceeding the target benchmark consumption figures.
  2. “The situation is different for an operator looking to tweak his machines’ settings to obtain the best energy performance per unit of production.” Where real-time monitoring is the objective, the most appropriate time increment for operators to manage the plant is the minute or possibly a 10-minute span.
  3. When the goal is to analyse one-off phenomena such as a spike in the pollution released by a waste incineration plant, the best time increment is the second“This is known as troubleshooting: the analysis consists in finding the causes of a problem and results in changes to the plant’s regulation.”

Weekly reporting, minute-by-minute monitoring or second-by-second analysis: that about sums it up… doesn’t it? Not quite. The question of what time increment to use is studied in great depth by the Blu.e engineer in collaboration with the site stakeholders, who are most familiar with how the factory operates.

 

Align the data to mine its full operational value

We align all of the data on the same time baseline so that we can then study and compare the different types of data. The data obtained using different time increments is extracted, transformed and loaded into a single database by a little software robot known as an ETL (for Extract, Transform, Load). “We prepare and clean the data in the ETL. Among other things, this helps us create the performance monitoring indicators and the variables for operational management assistance in our blu.e pilot® tool”, concludes Quentin Bonnand. For example, the heating system operator will see the instructions for starting up and shutting down the plant, while the production process operator will have real-time management instructions to ensure optimal energy efficiency. So, ready to get to grips with managing your factory’s energy use?

 

To find out more about data structuring: an article on what a data engineer does.