Submitted by Sheila Kester, VP of Operations at TwinThread
For your engineers to feel they have strong visibility into the energy consumption of your operations, they must have access to data reports at the machine level. The plant level and line level reports are not enough because they don’t drill down far enough to see where energy waste is occurring.
A large factor in energy waste is within the machines themselves. Temperature and vibration excesses and deviations within machines are where energy consumption compounds over time. So, you need to know the operational details of each machine to understand where there are opportunities to improve energy efficiency.
As an example, let’s assume your family vehicle typically consumes a tank of gas per week. However, last week, it only took half that time to consume the entire tank. What happened? Well, to know that, we need to know all the factors.
Such as, who was driving the vehicle? What are their driving habits? How far did they drive? How fast did they drive? How was the vehicle running? What’s the condition of the vehicle? Was it particularly warm or cold outside last week? All of these factors will paint a picture of how the gas was consumed quicker and will allow us to predict whether a similar event will occur in the future. The same goes for your machines. The details matter, no matter how seemingly insignificant.
You need machine-specific data. This means having sensors or meters that can collect data and monitor specific conditions. Many production / manufacturing organizations already have these in place. The key is to exploit that critical information by connecting those sensors to tag-based data or to feed it directly into troughs that evaluate based on production data, energy data (across all facets), or cost data.
A “production data” trough typically relies on an MES system and evaluates what is running / what is being made (SKU or product based), how frequently the production process is subjected to a planned stoppage, how often the process must be stopped unexpectedly, whether there are swings in external variables (temperature, humidity), and production volume. In other words, what good is it to know you consumed a certain amount of energy one day and a lot more the next if you don’t know the relative output of the production line?
An “energy data” trough pays close attention to the changes in consumption across all assets (identifying top performers). It takes into account any type of energy (WAGES or other). It also tracks variation in consumption from production line to production line, or SKU to SKU.
A “cost data” trough allows you to more accurately attach a cost to production processes and the energy consumption associated with that process.
All of this data and evaluation will allow you to uncover patterns that would otherwise remain hidden. Questions like, “when are we most efficient energy-wise?”, or “when are we least efficient?”, begin to become more clear. Answering these questions will allow your operation to begin recognizing patterns and taking preventive actions before events culminate and lead to excessive energy costs or, worst-case, asset failures.
This data also allows you to standardize energy output to units of consumption. The first step in creating greater efficiency is establishing a baseline. Once that is done, you can optimize production processes to match performance expectations.
If you’d like to learn more about TwinThread’s Predictive Operations Platform, and how easy it makes accessing your energy data and insights, get started here.