Power Up: Energy-Use Simulations for Greener Factories

SERGEY ASTANIN: everyone. My name is Sergey, and I'm here to present you a new energy use simulation product called Flexcon Helios, which is supposed to be used with an Autodesk product called FlexSim. We believe that this tool may be-- may play an important role in transitioning to group of manufacturing to green energy.

My talk will be-- will have four-- five parts. First, I would like you to introduce to, what is our module? What is its idea, vision? Then I will present you a short demo, how it works. Actually, it will be more of a tutorial kind of presentation. So I think you will be able, also, to learn how to use it.

And then I will try to discuss two possible applications, two use cases of these two. Finally, I will give you a short overview of what to expect in the near future. I will give you our roadmap. I hope that this presentation will provide you a great learning experience, and I hope you can understand me well. So enjoy this presentation. Let's go.

So Flexcon Helios, Flexcon takes its name from our company name, Flexcon srl. We are a small Italian company based in Turin, Italy. We provide all kind of consulting services related to simulation, emulation, digital twin, and similar topics. And Flexcon has a long-standing relationship with FlexSim, more or less 20 years from the very beginning of FlexSim as a software.

Flexcon has over 100 clients, mostly in the fields of manufacturing, packaging, logistics, and material handling. And by working with many our clients, it brought us to be more than just a consulting company. We are co-developer of the FlexSim Emulation module. And we have also developed several custom FlexSim simulation solutions for different major Italian companies.

Our experience with energy simulation is probably-- has probably more than 10 years of history. The first energy use simulation model that we have developed, it was in 2015, and we successfully used it in various consulting projects. It was then overhauled in 2018 with a better user interface, faster and more accurate computational agent-- engine. But this year, in 2024, we are starting a new and develop a new approach called Flexcon Helios.

So what is the Flexcon Helios? And why we begin a new project now? We strongly believe that energy use simulation is important and will become even more important going forward. According to different sources, energy plays a huge role in greenhouse gas emissions, and energy use in industry, manufacturing, is a big part of that.

So the exact numbers differ from one report to another, but mostly they all agree that we are talking about a two-digit percentage of the global greenhouse gas emissions. And what's important, that energy demand is still growing worldwide, and particular, electricity demand is increasing.

An interesting aspect of energy use in 2024 and going forward is the rise of the renewable energy. And it brings such concerns to the table as intermittent or variable availability, dynamic pricing, and variable CO2 intensity. And it's not a fad. It's something that we need to get used to, and because it's still growing and it will be only bigger in the following years.

So the core ideas that made us rethink our approach to energy use simulation is this. If anything related to energy generation changes over time, costs, availability, CO2 intensity, then probably, if we consider energy consumption, we also need to consider not only how much energy is consumed, but also when.

FlexSim simulation models is a tool which allows to answer both questions because it's a natural output of a discrete event simulation model with a kind of Gantt chart, a kind of sequence of operations, which is possible. And it allows us to estimate how much energy is needed and when.

The tool that we are proposing, Flexcon Helios module, tries to tie together all three of them. So consider energy consumption in the context of a FlexSim simulation and connect it to different kinds of energy generation. An important question to ask is, why did we choose FlexSim as the platform? And because, why we did not develop a standalone product? And there is no better answer than the FlexSim website itself.

This is the front page of the FlexSim website. And while FlexSim is a relatively new product in Autodesk portfolio, it has a long history of simulation, of being a simulation, modeling, and analysis software of choice of many companies. In particular, we believe that FlexSim has the right level of abstraction, the light-- the right level of granularity, which allows to improve a wide range of systems and processes.

But what kind of systems are usually studied with FlexSim? Again, looking at FlexSim website, we can see that the number one application for FlexSim is probably industry and manufacturing. This is what makes it an interesting platform for us because it aligns with our experience. And this is why we think our model can improve FlexSim standing as an industry product.

What we propose is a FlexSim model. So Flexcon Helios is a FlexSim model. It's not a standalone software, but it's an add-on for an existing FlexSim installation. So it still requires a FlexSim license, but in addition, it can do something more. And the idea is that this module will allow to apply energy use analysis to basically any existing or future FlexSim model.

It's important because, at Flexcon, we think that it's essential to consider energy use simulation always in the context of other KPIs, other factors, not only how much energy did we consume, but also how much product we produced or something like that. This model will allow to analyze and predict three kinds of quantities, total consumed energy of the process or of the components of this process and power requirements, indirect carbon emissions from energy, and costs proportional to energy consumption.

One of the key ideas of this development is to create a tool which is as similar to FlexSim native tools and libraries as possible, with the idea that it should be very easy to learn by existing FlexSim users. Speaking of system requirements, there is nothing special. It should work on any FlexSim enterprise installation.

I would like to note that everything that I will show you today is not a released product yet. We plan to do a public release in the first quarter of 2025. And everything that you see here is an early preview. You can think of an early beta, but there's a possibility to change or extend almost anything. And the presentation and the tutorial that I will show you, again, it is not the final product. So this tutorial does not substitute the final product documentation and it should not be used for purchasing decisions.

Speaking of the module, what are its components? It's almost impossible to talk about energy use simulation if we are not talking about energy consumers. In our case, any FlexSim object can be a consumer. And this is a good thing because we are standing on the shoulders of the giants here, and we are extending existing FlexSim simulations with the energy use simulation concerns.

The key tool that we add is energy use policy. It's a tool which will allow to define power requirements for groups of similar objects and aggregate energy use statistics for the group. It will also allow to study energy use efficiency within that group. But if we want to make one step further and talk about environmental impact costs, or if we want to aggregate energy use statistics, then we need another building block and its energy source.

A model can have any number of energy sources. The interesting part of energy sources is that they allow to define availability schedules, when they are available, how much energy they can provide at different moments of time. And they can provide carbon intensity and cost schedules. So this will allow us to cross-reference a FlexSim simulation and the simulated process with the availability of different energy sources and estimate possible carbon emissions or possible costs and so on.

The part which is probably as important as these two is our ability to analyze model results. And we do it by offering a library of Dashboard chart templates, which is an easy-to-use tool, which to create custom visualization, custom data collection instruments, to analyze all aspects of energy use. I will show them later.

But before we proceed, I would like to say a couple of words about modeling assumptions that we make-- that we made. First of all, we assume that energy consumption rate, the power requirement of an object, depends only on its state and its content. In the FlexSim world, it means the state of an object roughly corresponds to a phase of the process. And content of the object roughly corresponds to the quantity of material being processed.

So if energy consumption can be defined in terms of these two criteria, it should be possible to apply Flexcon Helios. Then for simplicity, we assume that the consumed power remains constant for the entire duration of the state, so for the entire duration of a phase of the process. So we approximate power curves with piecewise constant step functions.

Another voluntary choice that we made in this version is to avoid, to interfere, with the simulated process. So Flexcon Helios remains as a mostly silent observer of the simulated process and does its energy counting thing, calculates how much energy is required, what is the peak power requirement, but it never stops the model. It lets it run till the end. So it should be relatively easy to introduce it gradually without providing a complete energy use model for a complex model.

Speaking from the modeling paradigm, Flexcon Helios remains firmly in the pure discrete event simulation field. So there is no physical model, no complicated engineering formulas. Our main idea is that, with this model, we are mostly interested to study how the order of operations or the duration of different operations can affect energy use. So we are not trying to simulate things like energy dissipation or something like that.

And with these assumptions and limitations, I believe there are at least three major use cases and two major applications of this tool. The first one is estimating the costs of-- the energy costs and carbon emissions due to energy. That is, that if we can change the order of operations or production schedule, then it means that the same amount of product, the same process, may actually use different energy sources and, thus, probably reduce costs or emissions.

The second possible application is using this model for estimating power requirements. In many complex systems, there are many processes or many operations running in parallel. And the natural output of a discrete event simulation, which FlexSim is, is being able to see which processes may run simultaneously. And when two or more processes run simultaneously, they also consume simultaneously. And it means this is the off period of a possible peak consumption, and we can use this period to rightsize our energy subsystems.

Finally, the third application area for the module is using it for analysis and energy accounting in simulated systems because while we certainly can measure how much energy is required for each group of consumers, but in some cases, it's important to consider energy use efficiency because some operations may contribute to transformation of the product, and we may consider them as value-added consumption, and some operations do not.

But it's only one perspective. In the same model, we can also analyze which energy sources we can use. So we can still have costs or environment impact of this production process. And we can also have an arbitrary category of consumption, which may be related to a production area, to the type of product produced, to even the reason something is consumed, like powering motors or using it for cooling.

So this is the idea. What is the model? And I will proceed with a small demo and tutorial. In general, I believe that energy use simulation requires four steps. First of all, we need a FlexSim model. Then we may add energy use policy to this model, define them. And already, at this step, we can calculate the total amount of energy used, power requirements, and energy use efficiency.

Going one step further, if we add energy sources and provide carbon intensity and cost data, we might be able to simulate indirect carbon emissions, costs proportional to energy, but we can also aggregate energy use consumption by source. The final step of any simulation is data analysis. And the tool that we provide is a library of Dashboard chart templates. I will show some of them later.

Building a FlexSim model can be a very simple task, which takes probably a minute or two. In this case, I have accelerated. And the model is created in 15 seconds, actually, instead of two minutes. Sometimes, it takes month to build an adequate model of a process, so it depends. But assuming that we have built a model, we can proceed adding energy use objects to this model.

Just a few words of what we have in this model. In this model, we have a source object, which is usually a point of entry of material into the material flow model, a conveyor system which can consume energy, a container, a buffer of some kind, called queue in this case, and two processing stations with variable cycle time. Both have-- both are semi-automatic. So they require some human intervention, initially, and then they proceed into the automatic phase.

In this model, I would like to measure consumptions of the process or objects in the conveyor system. Step two, adding energy use policies. Like many other FlexSim tools, to add an energy use policy to the model, we need to go to the toolbox. Use green plus button, find Flexcon Helios menu, and add a new energy use policy. As simple as that. That's a pretty straightforward way to add new tools in FlexSim.

What is energy use policy exactly? Energy use policy is a tool which defines power requirements for a group of similar objects consuming energy for the same purpose. It collects and aggregates statistics about the consumption, and it may distribute load between multiple energy sources according to their priority.

If we take a look at how a configuration user interface is structured, it has four tabs, and these tabs match four aspects of its definition. The first tab, called Consumers, is where we can define a list of objects consuming energy. The second tab, called Consumption Rates, is where we can define power requirements of these objects. And the third tab is where we can connect energy sources available to this policy. And the final, fourth tab, Statistics, is where we can find some of the simulation results.

Looking into more detail how this user interface is structured, you may notice that on the top, there is policy name. And normally, there is more than one policy in the model. So it's a good idea to give it a descriptive name. A model can have, basically, an unlimited number of energy use policy. We can enable or disable them by using Enabled checkbox on the upper right corner.

And if we think that this policy can be reused in other models, in the bottom left corner, we can find a button, which can save it to a user library. This allows to reuse this policy in different models. So let's configure this policy. We give it a name, Processor Consumption. And to add consumers, we use either a sampler tool, a button with a pipette, or we can use a plus button, which is a standard way in FlexSim to connect objects by looking them by type, by name, by group, or by their location in the model.

As soon as we have defined consumers, we may go to the second tab, Consumption Rates, and define consumption rates. Consumption rate is nothing-- we are speaking about electricity consumption, consumption rate is nothing else than power. We can choose an appropriate-- yeah, we have to repeat it for all kinds of consumers.

But let's look at the structure of the user interface. We can choose an appropriate unit of measurement. By default, the object defaults to kilowatt and kilowatt hours for power and energy, respectively. We can use an appropriate state profile. Most of the standard FlexSim objects have only the default state profile, but in some cases, users define additional state profiles and they may be useful to define-- may be more convenient to define power requirements.

Power requirements use this-- the second column of this table uses the same unit that we have defined above. Note that there are two more columns called Multiplier and Analysis. By clicking in the Multiplier column, we can tell FlexSim that consumption in this state should be proportional to the content of the object. Basically, it's our way of saying that consumption is proportional to the quantity of the material within the object, let's say on a conveyor or on a station, which can process more than one item at a time.

And the fourth column, if we click there, we can add a value-added category to this kind of consumption. In this example, consumption in the processing state is considered value added and all other consumption is not considered to be value added. In some models, it is convenient to define, also, baseline consumption, which happens regardless of state. Basically, it's something that the object consumes just to keep the lights on.

And as soon as we defined our energy use policy and connected consumers to these energy use policies, we can already run an energy use simulation. We can reset and run the model. And in the Statistics tab of the policy, we will see some results, like consumption rates, total consumption, and value-added consumption, as small buttons with the pin icon is the standard FlexSim way to add charts or these statistics to a Dashboard.

Let's go on. To see energy consumption statistics for individual consumers, we just can click on this, select this consumer in the 3D view of the model. And in the Properties panel, we need to find energy statistics. Yes, in the Properties window of the object, we need to find Energy Statistics panel, and there we can read its current power and total consumption for the entire period for the entire simulation.

We can obtain-- we can represent these results in a much more appealing way if we use Dashboard chat templates. Dashboards is a kind of document window in FlexSim, which can contain-- control user interface elements. Or most often, it is used for charts. Flexcon Helios adds three categories of chart templates to the Dashboard library. You can see them in the library, on the left.

And if we want to analyze energy use policies, we need to use chart templates from the energy use policy and then, in the options of this chart template, connect an appropriate-- add an appropriate energy use policy to this chart. After resetting and running this model, we will be able to see the results. I will quickly scroll to the end of this video.

And let's go on. So to summarize it, we need to open a Dashboard, add a chart template from the Dashboard library, add energy use policy, so a matching object to this chart template, reset and run the model, and then adjust star-- style, colors, size of the chart, and so on.

At the moment, we provide three kinds of charts for energy use policy, energy consumption charts, which allow to measure the amount of energy consumed, like measured in kilowatt hours or any other unit, consumed power against time, which allows to monitor power requirements and how they changed in much more detail, and energy use efficiency, which these charts allow to see how much energy we used for value-added tasks and operations and how much we used for everything else.

Many charts are provided in different visual forms, like pie chart, bar chart, or even table chart. For consumers, we use this similar approach, but chart templates are found in a different section of the library. We have energy consumer templates. And at consumer level, we can monitor the total consumption and we can measure the power intake, basically, the average, the maximum and the current power.

So, again, we have two categories. Mostly, it's the same workflow. And it is exactly the same workflow that is used for standard FlexSim chart templates, like output, state time, state, and so on. Among these statistics, I don't know if you noticed, there was a statistic called Unmet Demand. We could see it in the Statistics tab of the energy use policy user interface.

In this case, as we haven't added any resource to this model yet, the energy use policy cannot distribute load between multiple sources. So the only thing that it can track is that the entire consumption rate was not provided by any source. This statistic can be a useful indicator to see that the energy system components are probably undersized with respect to the process.

So let's add some energy sources to our model. To do that, we need to switch to the 3D view of the library. And in the Flexcon Helios section of the library, we can find another source object with different visual forms and representations. We need to add it to the library. But to make it active, it needs to be connected to one or more energy use policy.

There are two ways to do it. We can go to the energy use policy section of the energy source and use the green plus button to connect it to an energy use policy. Another way to connect energy source to an energy use policy is to open energy use policy user interface, go to the Energy Sources tab, and use the green plus button or sampler button to add source to the policy.

Assuming we have done that, we just need to configure the source. Almost the entire configuration of the source is done through the EnergySource panel of its properties. There are two most important properties to configure. The first one is called generation rate, or as we call it, nominal generation rate. Basically, it's the nominal power, which this source can provide.

Why it is nominal? Because for many energy sources, the actual-- the power that they can actually deliver can vary in time. And to define this time-dependent behavior, we need to define also a generation time table accessible through added generation timetable, but in a second, I will show you how to compile this table.

Other properties of the energy source are units of measurement for power, energy, carbon equivalent, and the currency used for the costs. So if we are looking at generation timetable, this is probably the most important part of energy simulation configuration, and it is very dependent on the final end user.

Very often, we think it might be convenient to use a periodic schedule. So the schedule can be repeated daily or with any other period of time. And for each interval within this period, we can define yield, which is the percentage of the available power with respect to the nominal generation rate. And that's why we call it nominal, but not the actual generation rate. This way, we can easily model energy sources, such as photovoltaic systems.

In order to-- the fourth and the fifth column of this table are called Carbon Intensity and Cost. Technically speaking, they're optional, so we can leave them at zero. But if we want to simulate carbon emissions, the indirect carbon emissions due to energy consumption or cost proportional to energy consumption, we need this data.

Again, these data are highly client specific. We invite you to explore some configuration examples that you can found under the Examples dropdown menu in the top right. But in general, it's a good idea to prepare this data before running the simulation, like in Excel. And we recommend using-- we integrated this table with a FlexSim Excel import tool to facilitate to help importing this data from outside sources.

There is a number of peculiar energy source configurations to consider. Some energy sources do not provide constant power, but they change over time. If we want to simulate a wind farm or something like that, it might be convenient to define generation rate not as a number, but as a statistical distribution. In this case, a random value, random sample, will be evaluated at the beginning of each interval of the time table, and it will be maintained for that interval.

Another particular configuration, which may be useful in some cases, is an energy source with a constant available power. In this case, rather than creating an energy generation time table with just one line, an easy solution is to uncheck Use Generation Time Table box and disable generation time table completely. Unfortunately, in this case, we won't be able to simulate carbon emissions, of course. But still, we think that in some applications, it may be a useful option.

It's important to understand that the order of energy sources, how they are connected to energy use policies is important because energy use policy will always tries to maximize utilization of the first energy source. And only if it cannot provide enough power, it will request power from the second, from the third, and so on. There are blue arrow buttons in the Energy Sources tab of the energy use policy, which allows to define the priority.

Like with energy consumers, to see the statistics of the energy source, it's enough to click on the energy source in the 3D view of the model, and we will see different statistics. And like with energy use policy and energy consumers, there are dedicated chart templates in the Dashboard library to analyze different aspects of the energy sources.

I will quickly scroll to the end of the video. So at the end of the video, we can see that I added three charts to measure total energy output per source, total carbon emissions per source, and total energy cost per source, but there are more. We can analyze data delivered by an energy source, according to which policy it consumed it. We can analyze how much it delivered in different periods of time, so by hour or by another period.

We can represent this data also as a line chart, so value against time. We can go into more detail and watch, what is the delivered power over time? Or we can also use chart templates to measure the maximum delivered power observed during the simulation. And this output can be used to rightsize the energy subsystem. Almost all charts provide a table representation, which can be useful to import this data in reports, in text materials, and so on.

So to summarize what we have seen in this tutorial, any FlexSim object can be a consumer from the point of view of FlexSim headers. The one component which is-- which defines energy consumption is called energy use policy. It defines-- allows to measure total consumption, it allows to measure power requirements, and it allows to estimate energy use efficiency for a group of similar consumers.

If we want to go further and add energy sources to the model, we can measure carbon emissions or simulate costs proportional to energy. In this case, we also simulate variable availability of energy sources. For data analysis, there is a library of dashboard chart templates. Most of them require just a few seconds to create a chart and start collecting data of some kind. I have just a little time left. So let's discuss different applications. I would like to talk about two examples.

The first one is an example of a manufacturing facility. Actually, it's a facility where we can optimize production schedule. And we would like to see, what is the impact of this schedule on carbon emissions? In the second example, I would like to show you how Flexcon Helios can be applied to a more typical FlexSim model. So it will be a complex manufacturing system, and we will use Flexcon Helios for, basically, energy, stimulated energy counting in that model.

In the first example, we will consider a sterile injectables manufacturing facility. This model is inspired by a real manufacturing process, but all data that I show you are completely made up for demonstration purposes. So no secrets here. The process has three stages, filling, which requires working-- the filling line works four shifts per week.

Then the product goes into quarantine, where it needs to stay at least 24 hours. And then it goes into the packaging line, which operates several shifts per week. Finally, the finished product can go into the warehouse. The idea is to look what we can improve into this process from the scheduling point of view and whether these improvements can allow us to use on-site photovoltaic system in addition to the grid electricity.

The straightforward translation of the system into model has more or less the same number of objects. We had a source object, which represents upstream production process, a filling line, which is just a processor object with an appropriately chosen processing time, a flow storage object, which allows us to define a minimum dwell time, so a quarantine period. And the packaging line is represented by a processor with a different processing time.

Finally, we consider three possible schedules for the filling line, working four consecutive shifts starting on Monday, working two shifts on Monday and two shifts on Tuesday, and working only one shift per day Monday to-- through Thursday only during the daytime. And we also consider two packaging schedules.

One is starting at 9:00 AM and another is starting at 8:00 AM, with the idea to see how one-hour shift of the production schedule can impact carbon emissions in a system like this. As usual, we need to define energy use policy for each kind of consumption, so one energy use policy for the filling line, another energy use policy for the packaging line. And we need to provide two energy sources with different generation rates and different availability schedules.

So what will happen if we run this model for six days, which is more or less the complete production cycle in this system? I've run this model through FlexSim experiment tool, so doing more or less 48 simulations for each configurations. And what we can see, each dot represents a different simulation, so different possible outcome. They are divided in five groups, five scenarios.

The first scenario is the original scenario. The second and the third are scenarios where filling line worked two shifts per day. And the last two scenarios are scenarios where the fill line worked only during the daytime. The second and the third scenario are different by, what was the scheduling of the packaging line? And the fourth and the fifth, again, the difference is the scheduling of the packaging line.

The interesting conclusion is that, yes, change in production schedule, even small changes to production schedule, can have an impact on carbon emissions, on indirect carbon emissions. But a surprising observation from this experiment is that, sometimes, we have an unexpected increase in carbon emissions, like working only during the daytime, which may seem like the better choice when we have a photovoltaic system available.

Actually, my result in high emissions-- and the more detailed charts which we plotted for these simulations allows us to see why. With filling working only two shifts per day, it concludes its production cycle, its weekly production cycle, by Tuesday. So packaging works mostly by using solar power.

We can see that there are only minor peaks from the grid output at the end of the day, Wednesday through Saturday. But working only during the day results that the operation time for the filling line and the packaging line now coincide. And the capacity of our solar system, photovoltaic system, is not sufficient to support both. And in this case, the overall impact is actually worse.

So what we may learn from this example that, yes, production schedules and small, even small adjustments to production schedules can have-- can make a difference. And simulation is a tool which allows to easily explore different what if scenarios, different combinations of production plans, schedules, orders, operations, and so on. And combined with Flexcon Helios model, this may help to optimize power usage, costs, and emissions.

The second example is concerned with the more complex manufacturing system. In fact, in this case, we have six different kinds of objects and manufacturing lines with automatic CNC machines, semi-automatic CNC machines, manual assembly stations, conveyor systems of two kinds, and an automatic warehousing system. This kind of model is more or less a very typical flexing application.

Assuming that, in this case, we are concerned not with the costs or emissions, but just trying to understand how much energy we use and where, we can define our energy use policy by the type of the machine, assuming that similar machines have similar consumption patterns, and by the reason of consumption, like the same machine can consume to power its drives for auxiliary power or for cooling and compressed air. Converse of different widths can consume with a different rate.

And in a system like this, it's important to identify which states of the model objects contribute to the transformation of the product and which don't. By labeling these states as value added, we will be able to analyze efficiency of our energy consumptions, of our energy consumption.

To properly aggregate the results, this model uses not one, but four energy sources. All of them are grid energy. But in this case, we use energy sources, like an statistics aggregation tool. And statistics of these energy sources will provide a-- will inform our decisions about right sizing of the power components.

By running these applications, we can create all the usual charts, which Flexcon Helios supports. So we can see how much energy we consumed. In this case, I simulated 24 hours. What was the carbon? What carbon emissions correspond to this consumption? Again, it is very geographically dependent. And even it depends on day of the year.

And we can also simulate costs. Who wants to go into more detail, we can always analyze consumption by hour and see that there is some cyclicity in this production process, which is indeed what takes place there. And we can measure, what is the possible peak power consumption of the system? So in the bottom life-- bottom right, we can see the power curves of different energy sources.

By looking at the energy simulation output from the energy use policy point of view, we can analyze consumption by group and consumption by reason. So we can see how much we spent for cooling and compressed air as opposed to keeping our conveyors in motion. But also, we can analyze consumption of individual objects and see the peak average and maximum power consumption. From the energy use efficiency point of view, we have a ready-made tool. Just need to add energy use policy to this chart and have all the results there.

So as you have seen, Flexcon Helios, it is very straightforward how Flexcon Helios can be applied to existing and very typical FlexSim models. So we think it can be applied to manufacturing system, to material flow systems, and to systems with warehousing components. And even if we don't consider carbon emissions and costs, the use of Flexcon Helios model can still be useful to right size the components, and to do energy counting, and to have an insight where the energy spend, when, and for what reason.

Coming to a conclusion of this presentation, I would like to give you some reference points when you can actually try this product, when it will be available. And so at the moment, we expect to start consulting projects using Flexcon Helios this year, so the second quarter, 2024. And we will make it available, let's say closed beta pre-release to closed partner-- to select partners end of January, beginning of February 2025.

At that point, we expect it to be more or less the final version. But to keep everything smooth and as bug free as possible, realistically, we expect the public release by the end of the first quarter 2025. I hope that one day, you will try this product and you will find it easy to use and very useful. Thank you for your attention.