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Unleash the Potential of AI for Timber Connections Design in Revit

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Description

Designing timber connections is critical to ensure the structural integrity of timber constructions. An artificial system for designing timber connections would typically involve a combination of computational algorithms, databases of material properties, and engineering principles. Integrating AI systems with a code-checking system in Revit software allows engineers to explore different solutions and be certain of compliance with calculation regulations. Grouping and optimizing nodes, analyzing new node solutions, and automatically creating calculation reports in Revit can greatly reduce modeling and analysis efforts. We will also present a system capable of inserting nodes automatically and designing them according to the calculation actions present in Revit.

Key Learnings

  • Learn about automated modeling and code checking of structural connections in Revit.
  • Apply artificial intelligence to improve the design of connections.
  • Learn how to generate calculation reports of connections in Revit.

Speakers

  • Massimo Speziani
    He owns "Precast Designer for Revit" a single tool to design and analyze precast and timber structures. He has a structural engineering background and is a software developer providing Revit and Robot development services. Massimo holds a master's degree in structural engineering from the University of Brescia, Italy.
  • Ilaria Lagazio
    Ilaria Lagazio graduated in civil structural engineering, and after a brief experience in the field of industrial design, he started to operate in the yard industrialization field as building system development manager, focusing on the flow of building data from the model to the construction site. The interest for construction industrialization brought Ilaria to a field experience in United Arab Emirates, and she finally arrived at Autodesk, Inc., where, for more than 8 years, she has been working as Building Information Modeling (BIM) senior technical specialist.
  • Stéphane Balmain
    Stephane BALMAIN has over 10 years' experience in the construction field. After his M.Sc. Degree in Structural Engineering of Mining School of Ales and a specialization in Reinforced Concrete (CHEBAP), he joined SNC Lavalin in Nice in 2003. Due to his passion for computer science and analysis, he joined Robobat in 2005 as product manager for concrete. Since 2008, Stephane is a BIM technical specialist on structure and construction in Autodesk South Europe Team. BLOG: https://blogs.autodesk.com/villagebim/ Youtube: https://www.youtube.com/user/villageBIMsbalmain
  • Avatar for Giacomo Voltolini
    Giacomo Voltolini
    He is a renowned Structural and MEP Engineer specializing in timber structure design and seismic resistance. With a Master’s degree in Engineering from the University of Trento, he combines academic knowledge with practical experience. He excels in BIM and develops innovative software for timber structures and connections. His expertise extends globally, impacting projects across all continents. As CEO of his own company, he leads with pride and dedication alongside a fantastic team, driving advancements in timber design and solutions within engineering.
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Transcript

ILARIA LAGAZIO: Welcome, everyone, and welcome to this session. Before jumping to the content, let me introduce myself and my colleagues here. I'm Ilaria Lagazio. I'm a structural engineer, and I've been working in Autodesk for the last 18 years, where I'm currently covering the role of Senior Technical Solution Executive. Before this, I worked in a startup in Italy and Middle East aimed to industrialize the construction sites.

GIACOMO VOLTOLINI: Good morning. My name is Giacomo Voltolini, and I'm the CEO of MGE SRL, a company I've had the privilege of leading for the past 18 years. I'm a structural and MEP engineer, specializing in timber structures, including tall and multistory buildings, complex timber connection, seismic design, and [? common ?] modeling. I hold a master's degree in engineering from the University of Trento in Italy. In addition to my professional work, I'm actively involved in academia, teaching both at the university level and a specialized course focused on timber structures.

MASSIMO SPEZIANI: I'm Massimo Speziani, owner of Precast Designer for Revit, a single tool to design and analyze structures. I have a structural engineering background, and I work as software developer, mainly on Revit and Robot. I hold a master's degree in structural engineering from University of Brescia, Italy. And now I will hand the floor to begin the presentation to Ilaria.

ILARIA LAGAZIO: This is briefly the agenda of the session. We will cover an industry overview, the current status of BIM in timber construction, AI timber connection design in Revit, and we will close with future directions and conclusions. I will take just a few minutes before my colleagues will present the technical details to summarize a few concepts and challenges related to timber construction, in order to understand why it's so interesting to have such kind of third parties on top of out-of-the-box solutions.

First of all, we need to understand that wood products market size has grown strongly in recent years. It was around 750 billion in '23 to more than 800 billion in '24, and the projections of expansion are considerable. As from Wood Products Global Market Report, it will hit at 1,000 billion in '28, so the annual growth rate is around 7%. This construction market expansion observed in this historical period can be attributed to factors such as strong growth in emerging markets, low interest rates, growth of the world population, and growth in residential. Before going into the details of the specific technology, we can reasonably understand that, with the continued growth in the sector, wood industry will have a greater contribution to the gross world production.

There are some reasons that help this market to grow also related to specific technology and materials. Timber structures play a crucial role in structural engineering duties, due to sustainability, strength, and versatility. Timber structures offer specific structural benefits, like lighter weight, reduction of loads in foundation and lateral system, leading to more efficient for design.

Timber has been used in construction for centuries, including both building and bridge construction, and it continues to be quite relevant today, with modern advancements in timber connection and construction. Prefabrication is also playing a good role in this area, reducing labor costs and construction time. Wood offers, also, a natural aesthetic that you can difficultly achieve with other technologies. And, finally, wood is a renewable resource, and using it in construction could reduce the carbon footprint compared to traditional materials.

Of course, there are also challenges that engineers and architects must take in consideration in approaching this technology. For example, wood is anisotropic, and its strength can vary significantly, depending on species growth, defects, knots. It's also hygroscopic, meaning that it absorbs and releases moisture from the environment, and this can lead to changes that can affect the structural integrity of timber components.

Good construction design must take in consideration local regulations, local materials, rules, but it's also very important to understand and adapt the local production methodologies before setting up an analytical model. In fact, local methodologies often incorporate traditional building practice and knowledge that have been adapted and refined over generations. This practice can offer valuable insights and techniques that are well-suited to the local context, enhancing the overall quality and performance of the build.

Lastly, considering local production methodologies can facilitate compliance with local building codes and regulations. A big part of structural behavior is also connected to design of connection. Complexity is due to anisotropic nature of wood, and ensuring strong and reliable connections requires careful consideration of factors such as load distribution, joint detailing. And this methodology connection realization is also a consequence of the above localized production methodology.

This means that, apart from modelization of the frame, BIM wood connections are the most critical part of the model. We can find standard BIM libraries, but often they lack certain wood connections that require custom components to adapt to specific regulations, product methodology, local habits. Every structural engineer knows very well that the kind of connections that we design will drive the behavior of the structural frame, and this needs to be iteratively checked and optimized to find the best solution. This process is time-consuming and needs special expertise in both BIM software and timber engineering.

Then, if we consider this specific market, this specific historical and economical moment we are living, and considering the technologies that we are provided today, we need to look at an industrialized solution that takes into consideration efficiency, connecting the dots through a BIM model that is not descriptive but behavioral. And this means what could happen if we could be able to generate an interactive BIM model for wood structures that is inclusive of details in connection, in compliance with regulation, meeting production standards, and covering production phases in single interface, this will reduce dramatically manual adjustments. And the solution that my colleagues are presenting today can provide you a way to solve this puzzle, taking all these aspects in consideration. So let me hand over the presentation to Giacomo.

GIACOMO VOLTOLINI: Thank you, Ilaria, for your introduction, and good morning, again, everyone. Today, we will be discussing the process of designing a timber structure using the Building Information Modeling, or BIM method. Our focus will be on glulam beam and columns and CLT walls and slab. We'll explore the steps involved from the initial architectural model to the final structural fabrication model.

Now, let's take a look at the BIM process for timber structures, specifically focusing on glulam beams and columns and CLT. The process begins with the architectural phase, where we create a detailed architectural model that includes rough dimensions for the structural components. Based on this model, we move into the analytical phase, where the structure's behavior is evaluated under various loads and stress, according to the local regulation.

Next, we refine the structural model, making necessary adjustments to size of beams, column, and panels to ensure they meet the safety and performance standards. From there, we design the connection to each joint, whether it's columns, beam, or CLT panels. Finally, after verifying the architectural model to ensure any changes made align with the design intent, we generate a 3D model of the structural component, ready for CNC fabrication. This workflow ensures precise coordination from concept to construction.

In the architectural phase, we lay the foundation of the entire BIM process. This is where we create the initial architectural model of the building, defining the building's form, layout, and the key elements. While the focus is on the overall design, we also begin integrating rough dimensions for the structural components, such as glulam beams, columns, and CLT panels.

Also, thought these dimensions are not final at this stage, it's important to have a realistic idea of the structural elements early on. This ensures that when we move into the analytical phase, we already have a framework to evaluate and refine. Collaboration between architects and engineers is the key in this phase, as any significant structural elements needs to be aligned with the design intent of the building. The phase sets the stage for a smooth transition into the engineering aspects of the project, ensuring that both aesthetic and structures work in harmony.

Once the architectural model is in place, we move into the analytical phase, where the focus shifts to the structure's performance. In this step, we create an analytical model based on the architectural design, translating the building's structural element, like glulam beams, column, and CLT, into a model that can be used for engineering analysis. The goal here is to evaluate how the structures will behave under various loads, such as dead loads or live loads, wind, and seismic forces, ensuring that everything complies with local regulation.

This step is crucial, as it allows us to identify potential issues with the structural design and make any necessary adjustment. The analytical model provides us with the valuable data to ensure that the structural elements proposed in the architectural phase are not just aesthetically pleasing, but also safe, efficient, and capable of withstanding the forces they will encounter through the building's life cycle.

In step three, we apply loads and stress to the analytical models we've created. This is where we simulated real-world conditions, including dead loads, live loads, and seismic forces, to evaluate how the structures will perform. Using local regulation and codes as a guide, we ensure that the timber elements, such as the glulam beams and columns and CLT panels, can safely withstand the forces that they will be exposed during the building's lifetime.

During this phase, we often needed to adjust the size and configuration of certain structural elements. For example, a beam or a column might need to be resized to handle higher loads. These changes are critical to ensure both safety as efficient. This phase is all about refining the structural model to ensure we have the right balance between performance and material usage.

In step four, we focus on one of the most critical aspects of the timber construction, the design of connection. This connection, whether between glulam beams and columns or panels, are crucial to ensuring the structural integrity of the entire building. In this phase, we design each connection in detail, considering factors such as the type of the load the connection will carry, the material involved and the overall stability of the structure.

Timber connection can be complex, requiring precise coordination between different elements to ensure proper load transfer without compromising the building's safety. We look at the end of each beam, column, and CLT panels to define the connection point and their enforcement, whether with metal plates, bolts, or other fastener. It's at this stage that the theoretical design meets a practical construction as we ensure that every connection is not only structurally sound, but also feasible to fabricate and assemble on site. Well-designed connections are a key to the strength and durability of the entire timber structure.

In step five, we revisit the architectural model to ensure that any changes made during the structural design and connection phase are fully aligned with the overall design intent. After refining the structural components and the finalizing of the connection detail, it's essential to update the architectural model to reflect this adjustment. This step ensures consistency between the structural and architectural models.

For example, if we change the dimension of a beam that is visible in an interior space, it might affect the aesthetic of the layout of the room. Coordinating these changes ensure that the building maintains both its structural integrity and its design vision. This phase is critical for avoiding a discrepancy during construction and ensures that the project moves forward smoothly, with both the architectural and engineering teams working in sync.

In the final step, that is, step number six, we generate the 3D CAM model, which will be used for fabrication. This is where the structural design we've developed, include the glulam beams, the columns, and CLT, is transferred into precise data that can be read by CNC machines. The CAM model includes every detail of the timber components, from exact dimension to the position of cuts and connection points, ensuring that the parts are fabricated with millimeter precision.

This step is essential for bridging the gap between design and construction. With the CAM model, we create a fabrication-ready digital twin of the structure, ensuring that the timber elements can be efficiently produced and assembled on site. By automating this process, we reduce the potential for human error and ensure that the structural components fit together perfectly during the construction. This final stage in the BIM workflow ensures that the design becomes a reality, with all the precision and accuracy required for a successful timber construction.

In this current six-step BIM process, we rely on multiple software tools at different stages, each requiring manual data transfer. Every time data moves between platforms, there is a risk of errors creeping in. These errors can accumulate as we progress, leading to inaccuracy in structural dimensions, loads calculation, or connection design. Over time, this small issue can become significantly, causing a delays, cost overruns, and even structural failures.

By switching to an all-in-one platform, we eliminate the need for data transfer and manual update. This not only reduces the chance of errors, but increases overall accuracy by up to 14%, bringing it close to 99%, compared to the current 85% that we estimate. On top of that, the all-in-one solution significantly boosts efficiency. One person can now do the work of four, five people, reducing the workload by 78%. Ultimately, this approach streams the entire process, ensuring a faster, more reliable result with far fewer mistakes, while optimizing both time and resources.

With that, I'd like to hand things over to my colleague Massimo, who will guide us through the model and calculation of timber connection directly within Revit.

MASSIMO SPEZIANI: Thank you, Giacomo. Today, we are excited to take you on a journey through the great evolution of timber connection design, from manual drafting to cutting-edge AI-driven automation in Revit, revolutionizing efficiency, accuracy, and creativity in structural engineering.

Let's start by revisiting the early days of timber connection design, where manual drafting was the norm. Engineers calculated and sketched every details by hand and AutoCAD, a process that, while true, was also a time-consuming and susceptible to errors.

Fast-forward to the advent of digital tools. We see a significant shift with the introduction of Revit automation. This innovation streamlined the drafting process, leveraging Building Information Modeling to enhance accuracy and efficiency. While this marked a considerable improvement, it still required a substantial manual input for complex design.

Now, we can enter to the third step, the revolutionary leap of AI for engineers in two points. The first point is large language models for building technology. Imagine describing your design needs in plain language and receiving a detailed BIM model instantly. This groundbreaking capability bridges the gap between conceptual ideas and technical specification, transforming how we approach design.

But the evolution doesn't stop here. Generative AI pushes the boundaries even further, offering the ability to quickly generate multiple compliant design options. This not only accelerate the design process, but also opens up new possibilities for innovation, allowing us to explore a different range of solutions optimized for performance, cost, and aesthetic.

Let's explore how these innovations are shaping the future of timber connection design in paving the way for a more efficient and creative approach to engineering. Before exploring this new possibility, we will show an overview up to date of timber connection automation and code checking in Revit.

In Revit, the foundation for creating structural connection lies in defining rules in families. For steel structure, we have already integrated in Revit some automation. But, often, this is time-consuming for complex design or lacks in terms of code checking. This complexity can slow down the integration of sophisticated solutions.

For precast concrete structure, we have developed an automation solution in Revit, Precast Designer for Revit, to streamline the creation of connections. However, these, too, come with these challenges. While it often offers considerable flexibility, it demands preliminary setup work and doesn't always integrate code checking. Here, you can see an example of precast concrete columns with their connection.

Now, let's turn our attention to timber structure. Currently, we have very few automation solutions for timber connection in Revit. This gap presents a significant opportunity for innovation. Imagine leveraging AI-driven tools not only to simplify the process, but also ensure code compliance solutions and optimize design efficiency.

We will delve, now, the standard automation process of modeling and checking connection using predefined rules. We can do this for timber connection with Precast Designer for Revit, a powerful tool originally developed for the precast concrete industry and now extended to timber structures. This software automates the creation of nodes in Revit, streamlining the placement of connections on timber elements.

With this tool, you can save time, reduce errors, and enhance the overall efficiency of your design process. To create a node, you need to set up predefined rules in family. Precast Designer then can adopt these connections based on existing boundary conditions.

Let's explore some examples featuring three types of beam-to-beam connection. The rules can be applied to virtually any element, like columns, beams and panels. The process is very simple. Once the Automatic Connection tool is started, you can simply set the object for which we want to create the connection. If multiple option rules are available, you can activate the [? decisional ?] rule.

After the connection is inserted, it can be modified using standard element parameters in Revit or standard editing operation. In this demonstration, we highlight the type of connection, beam-to-beam connection, designed and verified according to [INAUDIBLE] slotted connection-- this is a robust solution for various structural needs-- and a compression connection with an additional steel plate. This connection can enhance stability and load-bearing capacity.

This sophisticated tool not only simplifies the design process, but also ensures precision and compliance with engineering standards. Automation of connection generation is now combined with code checking. Let's dive into some example of code checking for timber connection using Revit.

Once the connection are inserted, we can perform automatic code checking with both American and European standards. The action input for the connection can be read directly from Robot structural analysis result inside Revit or using some parameter inside Revit or with the connection with Excel.

For this demonstration, we showcase a simple connection at the base of a panel. The outcome is a comprehensive calculation report according to the standards. From this Revit model, we can automatically generate detailed drawings, coordinate with a calculation node. The calculation report contain all the verification and can be saved in various formats, including Word.

However, we can significantly enhance this model and check operation using AI. For instance, while we have performed checks on a single connection, AI opens the door to self-design or autonomous design, where the software not only checks, but also optimizes and suggests design. Now, we can explore the exciting frontier and see how AI can revolutionize our approach to timber connection design, take us from manual verification to intelligent automated design.

Now we can start the exciting journey into the future of structural design, where artificial intelligence is transforming the development of initial design solutions. In this video, we will demonstrate advanced AI technology. Large language models like ChatGPT are now revolutionizing the way we create BIM models.

We are proud to introduce DesignMaster. DesignMaster is an innovative tool that acts as a designer assistant, enabling the execution of various operations with ease and efficiency. This tool leverages the power of AI to streamline and enhance the design process, making it more intuitive and less time-consuming. Imagine a scenario where you can select all timber panels at the base level or ground level and create specific connections, all by simply typing a prompt. DesignMaster turns this vision into reality, allow you to focus on creativity and design, rather than getting bogged down by the repetitive tasks.

Let's delve into one example to illustrate the capabilities of DesignMaster. Using this tool, we can type a simple prompt and send to DesignMaster-- set a wall at the ground level, and apply a connection of type base to the bottom of selected wall. Instantly, the tool identifies all relevant timber panels at the ground level and automatically generates the required connection using Revit families. This automation not only saves time, but also reduce the potential of human error in the initial design phase.

But the innovation doesn't stop here. After creating the initial solution for the connection, we can further refine our model. For instance, if we need to adjust the number of the SKU using in this connection, we can do easily through another prompt informed by a quick query sizing calculation. This approach can dramatically reduce the time and effort typically required for a series of manual operatioms and complicated configuration.

This natural language interface make it accessible even for those who may not be highly technical, democratizing the use of advance design tools. DesignMaster helps the generation of initial BIM model ready for the next design steps.

Now, after the use of this tool and large language model, we will see how the power of generative AI can achieve automatic design and configuration of connection.

Now, we'll take a look on how, with the help of AI, we can have automatic design of connection. On the left, we can see a base panel connection for the green wall calculated with the tools seen before. Generative AI-driven design tools have the ability to generate multiple design options that are fully compliant with relevant standards and codes. These not only accelerate the design process, but also offer the spectrum of solutions tailored to specific project needs, material, and environment conditions.

We will use DesignMaster, as in the next video, to generate different design solutions. The chart on the right featured the resistance ratio on the horizontal axis, the where less is better, from 0 to 1, and the green factor on the vertical axis, with 100% indicating minimal material usage. This scatterplot visualizes the relationship between the two criteria.

There is a positive correlation between the two factors. As resistance ratio increases, material usage will decrease. There is also a nonlinear relationship between the two criteria. And there is, on the top part of the chart, a clustering of points, indicating that many solutions with both the ratio and the minimum material usage are present.

Ratio of resistance must be less than 1 because it's the maximum allowed from the current standard. And there is another aspect, is the consistency. There are no significant outliers. There is a consistency relationship between the two variables. By leveraging generative AI, we can navigate the complexity of design within parallel speed and precision, ensuring that every solution is not only feasible, but also optimized for different criteria.

In this video, we will demonstrate how DesignMaster can change the way engineers design timber connection. By leveraging action derived from Robot's data analysis model, and already stored in Revit, we can design the connection at the base of a timber panel using a single prompt.

In this example, we ask to DesignMaster to generate about 50 design solutions of selecting nodes for our review. All calculations are performed at high speed on a cloud infrastructure, ensuring that the process is fast and efficient, as you see in the video. Once the calculations are completed, these solutions are displayed in a chart on the left, as illustrated before. By clicking on a solution within this graph, you can view some of its main configuration parameters, such as the type of connector, the number of connectors, the position of the connector.

DesignMaster allow, also, you to set different connectors for a comprehensive catalog, giving you the flexibility to choose the best components for your design. Once a suitable solution is identified, applying it to the Revit model is very simple. You need only to provide the solution ID through another prompt. In this demonstration, we are referencing Eurocode 5, ensuring that all solutions are compliant with current standards. This led to the update of initial design model developed before.

DesignMaster is also integrated with the [? Salmon ?] [INAUDIBLE] tool. It's integrated with Robot structural analysis, enhances its capability to deliver robust connection design. The integration with Robot allow engineers to leverage the powerful analysis tool through DesignMaster. By requesting the generation of a connection calculation model, using the action derived from the Revit result, engineers can ensure their designs are not only accurate, but also compliant with necessary standards.

As a request is made, DesignMaster, using the existing data in Revit, to create a detailed output model. The model is created with plate shell alignment in this case and include all necessary load combinations, ensuring every aspect of the connection is analyzed. The Robot model is calculated locally, and it provides a detailed distribution of stress on every steel plates inside the connection. This analysis is very important and is crucial for understanding the true performance of the steel plate under various load conditions.

One of the standout features of this integration is this flexibility it offers. Within the prompt, users can specify the type of analysis they require-- that can be linear or not linear-- and the type of Robot model that he wants. This allow for a tailored approach to connection design and allow to follow different range of project requirements and complexity.

The output of this process is linked to a Robot file, which can be easily accessed and opened to review the detailed calculation result provided by DesignMaster. This not only streamline the workflow, but also ensure that all design decisions are backed by comprehensive analysis and data. By the integration between DesignMaster and Robot Structural Analysis, engineers can achieve a higher level of precision and confidence in their connection design, going to a safer and more efficient structure.

For each design solution, DesignMaster allows you to easily generate a complete [? code ?] creation report in various formats, such as Word, Excel, or PDF. You can type a simple prompt, and you can request for the specific connection, the calculation report. Then you can press the link created, and the calculation report will be opened.

Nodes can be calculated as a single node or grouped in order to improve the solution for a group of nodes of the structure. Here you can see an example of what calculation report with all the checks necessary for this code.

GIACOMO VOLTOLINI: Thank you, Massimo. Looking ahead, the future of engineering design will be shaped by the growing role of AI. We are entering an era where AI will revolutionize both architectural and structural design processes, offering a faster and more efficient solution. From generating innovative design to performing complex structural code checks in real time, AI will empower engineers to push boundaries, optimize materials, and minimize errors. This technology will bridge the gap between creativity and precision, leading to more sustainable and innovative building solutions.

As we reach the end of our presentation, we can't help but ponder the future looks like a Dynamo in the age of DesignMaster and advanced language models. Will language models render visual programming obsolete? The answer lies in the remarkable capability of language models, which allows for intuitive and natural language interaction that can dramatically simplify complex design tasks.

DesignMaster exemplifies this potential, offering a seamless base command can quickly generate and optimize BIM model using complex AI code. With language models that promise to streamline and accelerate the design process, they don't necessarily spell the end for programming. Instead, they complement it, increasing the versatility and power of our toolset.

Dynamo and similar tools will still play a crucial role, especially for those who prefer visual workflows and need a highly customized solution. In essence, the rise of language models represent not the destruction, but the evolution of visual programming. It's about giving designer and engineers more choices and greater flexibility in how they approach their work. The future of design is one where AI and the human ingenuity work hand in hand, pushing the boundary of what's possible.

The evolution of structural code checking with the next generation of LLMs, Larger Language Models, is an exciting development in the field of structural engineering. This advancement has the potential to revolutionize how engineers verify compliance with the building codes and standards. The evolution could shift engineers in focus from a routine code checking to more creative design aspects, can require new skills in efficiently using and interpreting AI assistant code and checks, and in the end potentially change liability and professional responsibility paradigms.

Thank you for your journey, for joining us in this journey into the future of design automation. Let's embrace the possibility and continue to innovate it together. Let me hand all over again to Ilaria.

ILARIA LAGAZIO: Thank you, Giacomo. Just a few words about the conclusion after looking at this such amazing tool develop. We listed, at the beginning, to a series of challenges and needs that I think were well faced and solved in the above presentation. Basically, indeed, we saw how design can be optimized, how manual activities can be reduced, how libraries can be flexed on top of our needs, and how, at the bottom of the line, advanced connection design is made accessible to a broader range of engineers and designers. At this point, I think it's clear that the solution on top of Revit model able to calculate the structure in background, handling personalized connection, and generating executive drawing automatically from the model is what we need to address this kind of market.

Thanks, everyone, for attention.

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We use Salesforce Live Agent to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Salesforce Live Agent Privacy Policy
Wistia
We use Wistia to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Wistia Privacy Policy
Tealium
We use Tealium to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Tealium Privacy Policy
Upsellit
We use Upsellit to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Upsellit Privacy Policy
CJ Affiliates
We use CJ Affiliates to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. CJ Affiliates Privacy Policy
Commission Factory
We use Commission Factory to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Commission Factory Privacy Policy
Google Analytics (Strictly Necessary)
We use Google Analytics (Strictly Necessary) to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Strictly Necessary) Privacy Policy
Typepad Stats
We use Typepad Stats to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. Typepad Stats Privacy Policy
Geo Targetly
We use Geo Targetly to direct website visitors to the most appropriate web page and/or serve tailored content based on their location. Geo Targetly uses the IP address of a website visitor to determine the approximate location of the visitor’s device. This helps ensure that the visitor views content in their (most likely) local language.Geo Targetly Privacy Policy
SpeedCurve
We use SpeedCurve to monitor and measure the performance of your website experience by measuring web page load times as well as the responsiveness of subsequent elements such as images, scripts, and text.SpeedCurve Privacy Policy
Qualified
Qualified is the Autodesk Live Chat agent platform. This platform provides services to allow our customers to communicate in real-time with Autodesk support. We may collect unique ID for specific browser sessions during a chat. Qualified Privacy Policy

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Improve your experience – allows us to show you what is relevant to you

Google Optimize
We use Google Optimize to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Google Optimize Privacy Policy
ClickTale
We use ClickTale to better understand where you may encounter difficulties with our sites. We use session recording to help us see how you interact with our sites, including any elements on our pages. Your Personally Identifiable Information is masked and is not collected. ClickTale Privacy Policy
OneSignal
We use OneSignal to deploy digital advertising on sites supported by OneSignal. Ads are based on both OneSignal data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that OneSignal has collected from you. We use the data that we provide to OneSignal to better customize your digital advertising experience and present you with more relevant ads. OneSignal Privacy Policy
Optimizely
We use Optimizely to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Optimizely Privacy Policy
Amplitude
We use Amplitude to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Amplitude Privacy Policy
Snowplow
We use Snowplow to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Snowplow Privacy Policy
UserVoice
We use UserVoice to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. UserVoice Privacy Policy
Clearbit
Clearbit allows real-time data enrichment to provide a personalized and relevant experience to our customers. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID.Clearbit Privacy Policy
YouTube
YouTube is a video sharing platform which allows users to view and share embedded videos on our websites. YouTube provides viewership metrics on video performance. YouTube Privacy Policy

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Customize your advertising – permits us to offer targeted advertising to you

Adobe Analytics
We use Adobe Analytics to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Adobe Analytics Privacy Policy
Google Analytics (Web Analytics)
We use Google Analytics (Web Analytics) to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Web Analytics) Privacy Policy
AdWords
We use AdWords to deploy digital advertising on sites supported by AdWords. Ads are based on both AdWords data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AdWords has collected from you. We use the data that we provide to AdWords to better customize your digital advertising experience and present you with more relevant ads. AdWords Privacy Policy
Marketo
We use Marketo to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. We may combine this data with data collected from other sources to offer you improved sales or customer service experiences, as well as more relevant content based on advanced analytics processing. Marketo Privacy Policy
Doubleclick
We use Doubleclick to deploy digital advertising on sites supported by Doubleclick. Ads are based on both Doubleclick data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Doubleclick has collected from you. We use the data that we provide to Doubleclick to better customize your digital advertising experience and present you with more relevant ads. Doubleclick Privacy Policy
HubSpot
We use HubSpot to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. HubSpot Privacy Policy
Twitter
We use Twitter to deploy digital advertising on sites supported by Twitter. Ads are based on both Twitter data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Twitter has collected from you. We use the data that we provide to Twitter to better customize your digital advertising experience and present you with more relevant ads. Twitter Privacy Policy
Facebook
We use Facebook to deploy digital advertising on sites supported by Facebook. Ads are based on both Facebook data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Facebook has collected from you. We use the data that we provide to Facebook to better customize your digital advertising experience and present you with more relevant ads. Facebook Privacy Policy
LinkedIn
We use LinkedIn to deploy digital advertising on sites supported by LinkedIn. Ads are based on both LinkedIn data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that LinkedIn has collected from you. We use the data that we provide to LinkedIn to better customize your digital advertising experience and present you with more relevant ads. LinkedIn Privacy Policy
Yahoo! Japan
We use Yahoo! Japan to deploy digital advertising on sites supported by Yahoo! Japan. Ads are based on both Yahoo! Japan data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Yahoo! Japan has collected from you. We use the data that we provide to Yahoo! Japan to better customize your digital advertising experience and present you with more relevant ads. Yahoo! Japan Privacy Policy
Naver
We use Naver to deploy digital advertising on sites supported by Naver. Ads are based on both Naver data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Naver has collected from you. We use the data that we provide to Naver to better customize your digital advertising experience and present you with more relevant ads. Naver Privacy Policy
Quantcast
We use Quantcast to deploy digital advertising on sites supported by Quantcast. Ads are based on both Quantcast data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Quantcast has collected from you. We use the data that we provide to Quantcast to better customize your digital advertising experience and present you with more relevant ads. Quantcast Privacy Policy
Call Tracking
We use Call Tracking to provide customized phone numbers for our campaigns. This gives you faster access to our agents and helps us more accurately evaluate our performance. We may collect data about your behavior on our sites based on the phone number provided. Call Tracking Privacy Policy
Wunderkind
We use Wunderkind to deploy digital advertising on sites supported by Wunderkind. Ads are based on both Wunderkind data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Wunderkind has collected from you. We use the data that we provide to Wunderkind to better customize your digital advertising experience and present you with more relevant ads. Wunderkind Privacy Policy
ADC Media
We use ADC Media to deploy digital advertising on sites supported by ADC Media. Ads are based on both ADC Media data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that ADC Media has collected from you. We use the data that we provide to ADC Media to better customize your digital advertising experience and present you with more relevant ads. ADC Media Privacy Policy
AgrantSEM
We use AgrantSEM to deploy digital advertising on sites supported by AgrantSEM. Ads are based on both AgrantSEM data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AgrantSEM has collected from you. We use the data that we provide to AgrantSEM to better customize your digital advertising experience and present you with more relevant ads. AgrantSEM Privacy Policy
Bidtellect
We use Bidtellect to deploy digital advertising on sites supported by Bidtellect. Ads are based on both Bidtellect data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bidtellect has collected from you. We use the data that we provide to Bidtellect to better customize your digital advertising experience and present you with more relevant ads. Bidtellect Privacy Policy
Bing
We use Bing to deploy digital advertising on sites supported by Bing. Ads are based on both Bing data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bing has collected from you. We use the data that we provide to Bing to better customize your digital advertising experience and present you with more relevant ads. Bing Privacy Policy
G2Crowd
We use G2Crowd to deploy digital advertising on sites supported by G2Crowd. Ads are based on both G2Crowd data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that G2Crowd has collected from you. We use the data that we provide to G2Crowd to better customize your digital advertising experience and present you with more relevant ads. G2Crowd Privacy Policy
NMPI Display
We use NMPI Display to deploy digital advertising on sites supported by NMPI Display. Ads are based on both NMPI Display data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that NMPI Display has collected from you. We use the data that we provide to NMPI Display to better customize your digital advertising experience and present you with more relevant ads. NMPI Display Privacy Policy
VK
We use VK to deploy digital advertising on sites supported by VK. Ads are based on both VK data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that VK has collected from you. We use the data that we provide to VK to better customize your digital advertising experience and present you with more relevant ads. VK Privacy Policy
Adobe Target
We use Adobe Target to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Adobe Target Privacy Policy
Google Analytics (Advertising)
We use Google Analytics (Advertising) to deploy digital advertising on sites supported by Google Analytics (Advertising). Ads are based on both Google Analytics (Advertising) data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Google Analytics (Advertising) has collected from you. We use the data that we provide to Google Analytics (Advertising) to better customize your digital advertising experience and present you with more relevant ads. Google Analytics (Advertising) Privacy Policy
Trendkite
We use Trendkite to deploy digital advertising on sites supported by Trendkite. Ads are based on both Trendkite data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Trendkite has collected from you. We use the data that we provide to Trendkite to better customize your digital advertising experience and present you with more relevant ads. Trendkite Privacy Policy
Hotjar
We use Hotjar to deploy digital advertising on sites supported by Hotjar. Ads are based on both Hotjar data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Hotjar has collected from you. We use the data that we provide to Hotjar to better customize your digital advertising experience and present you with more relevant ads. Hotjar Privacy Policy
6 Sense
We use 6 Sense to deploy digital advertising on sites supported by 6 Sense. Ads are based on both 6 Sense data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that 6 Sense has collected from you. We use the data that we provide to 6 Sense to better customize your digital advertising experience and present you with more relevant ads. 6 Sense Privacy Policy
Terminus
We use Terminus to deploy digital advertising on sites supported by Terminus. Ads are based on both Terminus data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Terminus has collected from you. We use the data that we provide to Terminus to better customize your digital advertising experience and present you with more relevant ads. Terminus Privacy Policy
StackAdapt
We use StackAdapt to deploy digital advertising on sites supported by StackAdapt. Ads are based on both StackAdapt data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that StackAdapt has collected from you. We use the data that we provide to StackAdapt to better customize your digital advertising experience and present you with more relevant ads. StackAdapt Privacy Policy
The Trade Desk
We use The Trade Desk to deploy digital advertising on sites supported by The Trade Desk. Ads are based on both The Trade Desk data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that The Trade Desk has collected from you. We use the data that we provide to The Trade Desk to better customize your digital advertising experience and present you with more relevant ads. The Trade Desk Privacy Policy
RollWorks
We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

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