The Benefits of Factory Planning: From 2D to 3D and Back Again Using Cloud Solutions

ROBERT OSTERMANN: Dear, ladies and gentlemen, hello and welcome. It is a pleasure to have you here in this online class on factory planning using Autodesk Cloud Solutions. And I'm Robert Ostermann, the Business Owner and Developer of Factory Planning Methods for Magna Steyr.

To begin with, here is a brief overview of what we will discuss in this class. There was our requirements in general and benefits of cloud solutions, essential workflows, and case studies from Magna Steyr. And I will conclude with a short summary.

So let's begin with the introduction, discussing the requirements and benefits of Cloud Solutions. Now, to help you understand the subtitle of this presentation, here are some analyzed facts. At Magna in Graz, we currently have approximately 3 million files for one production site, covering about 1 million square meters. These files are managed using Autodesk Vault as holistic data management system and on the Autodesk Construction Cloud as project management system.

Now, from analyzing the CAD data, we found that about 37% of these assemblies are still 2D AutoCAD DWG files. And additionally, nearly a third of these 2D drawings are used for legal purposes, such as escape routes or fire protection plans and so on. And in most situations, AutoCAD still is the optimal tool to create plans using CAD data from various sources.

So in the context of factory planning environments, there is a logical statement to make. The combination of 2D, 3D, and point cloud data from various sources is fundamental to achieving successful outcomes.

And this slide just shows the importance of combining 2D, 3D, and point cloud data in factory planning environments. So now let's take a closer look at the benefits of using a cloud service. But first, let's understand the typical approach and requirements.

These involve dealing with different CAD systems, coordinating specific file formats, documenting issues and tasks, and in typical project practice, data is stored in various locations, exchanged through different systems and often requires the use of multiple CAD viewers for validation or extracting information.

Now, all these tasks are handled separately, and issues arise without any connection to their origin. So on the left side of the slide, you can see a schematic visualization of that. Now, using a common data environment doesn't change requirements or does restrict you to specific CAD or PDM systems, but it offers significant benefits.

And firstly, the CDEs stores data in a central location, eliminating the need to exchange files through external platforms. Secondly, it eliminates the need for additional software to validate or extract CAD information. And lastly, the CDE connects all tasks and issues to their original source, ensuring seamless traceability and efficient management.

You can see a visual example on the left side of this slide illustrating these advantages. But let's dive deeper into both approaches, using what I call a planning continuity diagram. And in this diagram, let's focus on the phases where issues have been arising and needed to be solved.

And now let's consider a real world example, where initially files were exchanged through a portal between two distinct planning teams or they're consolidated in the virtual twin. It doesn't really change the scenario. And now suppose one team requires changes. And they make markups and submit them in a PowerPoint presentation.

And then the other team provides an update. But the team that needs changes struggles to understand the precise modifications. And also, some changes remain unaddressed, requiring a meeting. However, due to the project style's schedule, they must propose necessary changes in the plans and have already ordered materials to maintain the timeline.

Now, following the meeting, they need to revise their plans based on the final approved solution. And all these inefficient workflows consume valuable time and financial resources while also requiring additional resources to meet the project's schedule.

Now, let's compare this using a common data environment with the Autodesk Construction Cloud and examine the issue-solving phase once more. So files no longer need to be exchanged, and a coordination model is constantly available, incorporating the intended planning versions of all the teams at any time.

And this model can be accessed by anyone at any time. And when a team provides a new version to fix errors, it is automatically incorporated into the overall collaboration model on the common data environment portal. Changes can then be analyzed immediately, or further issues can be easily documented. And this enables teams to resolve issues and provide final versions much faster.

So some may argue that the CDE approach is not a straight line either in the diagram. Yes, that's true. But let's consider it an idealization to highlight The difference to your typical approach. And furthermore, in my opinion, when using a common data environment, most of the time and cost-intensive issues would not have occurred.

So this also leads to another clear statement I like to make. The highest value of the Autodesk Construction Cloud, when used as a common data environment, is the ability to improve planning continuity in factory planning projects.

So to conclude the introduction part of this class, here is an overview of the following content. We will examine the processes that the BIM Collaborate modules can support to achieve this common data environment approach. And I will show specific workflows and case studies from Magna Steyr factory planning projects to illustrate these concepts.

I also like to draw your attention to the process which is divided into manage, collaborate, coordinate, analyze, compare, and evaluate because this will be highlighted throughout the entire presentation. And additionally, I'd like to point out that there is a class handout available where you can find more information about certain workflows.

So in the first workflow part, I will focus on the Manage and Collaborate workflows. And when talking about managing all the factory data of an entire production facility site, whether considering the building and infrastructure data or the machinery and equipment data, there's also a clear statement to be made.

Autodesk Vault seamlessly integrates and organizes your entire factory data, while the Autodesk Construction Cloud enhances the transparency, traceability, and utilization of planning data across projects. But what's the reason for that? Now, this slide highlights three key features that are important for understanding as-is data.

Firstly, it is crucial to understand the lifecycle of files without copying them to different locations as done in project environments managed by the Autodesk Construction Cloud. And this leads us to one of the most important features. Autodesk Vault ensures visibility and traceability of file dependencies and the used version.

Additionally, it helps to standardize file properties which are also synchronized between, for example, the project information, Revit, and the Vault Database. This also means that certain information doesn't need to be included in a naming standard and can also be used as attributes to structure data views.

Now, this brings us to the next slide here, which aims to clearly explain the purpose of each platform. Vault is a holistic data management that is synchronized with projects managed on the Autodesk Construction Cloud, whose purpose is to manage project data for internal and external teams.

So from a data structure perspective, on the left side, all the data is stored in Vault. But the system being the master of certain data varies. Vault serves as the master for all the as-is data, which is then synchronized to different projects as needed, indicated by the blue numbers here on this slide.

On the ACC, for each individual project, Docs, the file management module, serves as the master, indicated here by the green numbers. And all these data are constantly synchronized between both platforms. But now let's shift our focus to the main purpose of this presentation on how to efficiently utilize the Autodesk Construction Cloud for factory planning projects.

And as mentioned earlier, when working on docs in the project, there is no file-based lifecycle. However, there are two approaches to handle this. One approach is to work with the current version, which means that if data is referenced, for example, in AutoCAD, it always reflects the latest saved version of a file. And this is illustrated here on this slide.

But depending on the size of a project and the number of teams and planning disciplines involved, there's likely a better way to manage files. And this is illustrated on this slide. Now, in the middle, you can see an additional data layer where an intended version is shared and used by other teams or planning disciplines.

Referring to the AutoCAD example, this means a drawing is not directly referenced but used as a shared version, which can be compared to an intermediate lifecycle state in Autodesk Vault. And this process of sharing a version can be supported by the Design Collaboration module on the Autodesk Construction Cloud, where created versions and their sharing with other team members or planning disciplines can be tracked and reviewed on a timeline.

So on this slide, you can see a comparison of both methods from a data structure perspective. On the left side, marked with number 1, you see that a version is copied to a shared folder by the Design Collaboration module, where it is accessed and used by others, as indicated by the number 2. And on the right side of the slide, marked with number 3, you can see that the latest or current version is accessed and used at any time.

So next, I'd like to show you a case study of Magna Steyr in Graz, where these workflows have been used to manage and collaborate a very large overall layout of a general assembly. And essentially, this case study aims to demonstrate the management of very large data structures. And what you see here is a reference explorer view of the overall layout, which contains approximately 1,000 file references.

The video on the slide demonstrates that this overall layout can be opened directly from Docs without any limitations and as quickly as it would have been from a local drive.

So the next video shows that the same overall layout, consisting of all these references, that it can be viewed online in the web browser with very good performance. And team members can review it can create markups and assign tasks or issues to communicate within a team.

So considering a typical workflow to maintain an overall layout for different internal and external planning teams or disciplines often involves coordinating and tracking files shared via data exchange. Issues and markups are commonly captured as screenshots in separate documents such as PowerPoint or PDFs.

And additionally, specific viewers are necessary to access and approve different CAD files. But using a common data environment streamlines this process. And a team member can easily access the required files at any time. They can efficiently create traceable markups and related issues using a web browser-based tool, which also enables them to view, communicate, or create transmittals and approve their plannings.

So now let's take a closer look at the next important functionalities that support factor planning in collaboration and coordination processes. First, it is important to note that when setting up a coordination model on the Autodesk Construction Cloud, not all file formats can be used natively.

So some of the approximately 70 possible file formats need to be utilized as a Navisworks cache or document file. And here on this slide is a brief overview of that.

Now, you can see here another comparison regarding the file structure and Autodesk Docs, especially related to implementing files for coordination purposes, whether used as a current or a shared version. And once again, I'd like to remind you that you can refer to the class handout for a detailed review of these aspects and to gather more background information.

So on this slide, I've provided a comparison of using, as mentioned before, a Navisworks cache file versus a Navisworks document file, NWC versus NWD. And in general, if the CAD file already represents the intended state with no changes required for appearance or visibility, you can just use the Navisworks cache file, the NWC file.

But if changes are necessary or you want to analyze the differences between versions, it is recommended to use the NWD file, the Navisworks document file. And this slide provides a visual representation of what I've mentioned before. And it shows a AutoCAD DWG file used as a Navisworks cache file with no changes and an NWD file with certain changes related to transparency or layer colors.

So next, I'd like to show you a case study of Magna in Graz, where this workflow has been used to provide a coordination model. And the video shows a combination of 2D, 3D, and meshed point cloud data. And based on what you've heard or learned earlier, the DWG file due to necessary visual changes has been implemented as an NWD file and the point cloud as an NWC file.

You can also see some issues that have been created, the documents, certain deviations between the reality, the point cloud, and the 2D layout. So the next video shows the same data being connected to Cintoo, which I will also discuss later in this presentation. But first, let's compare again a typical versus a common data environment approach in providing coordination models.

And once more, consider the typical workflow to maintain a coordination model. Now, there's always a need to track data exchanges and implemented file versions. Additionally, issues and markups are often captured on screenshots in separate documents, such as PowerPoint. And specific viewers are required to view and approve coordination models.

But using a common data environment means that any team member can access the coordination model at any time. They can easily access the data to create traceable markups and related issues using web browser based tools. And furthermore, they can perform additional tasks such as creating transmittal or approving their plannings.

So let's continue with important functionalities that support factory planning related to coordination and analysis processes. And when discussing coordination and analysis, it basically involves utilizing the clash detection features on the Autodesk Construction Cloud. And as you may already know, only specific file formats can be directly used for coordination model. And these formats are also the ones that can be automatically analyzed for clashes.

Now, in cases where automatic clash detection is not supported, there are two approaches to solve this issue, and this is shown on this slide. On the left, there is a data exchange referenced in a Revit model, enabling automated clash detection. And on the right, Navisworks and the Coordination Issue add-in are used to access the Coordination Model directly from the Autodesk Construction Cloud, allowing to create manual clash detections and synchronize all the created issues or all the found issues with the Autodesk Construction Cloud.

So if you are not familiar with data exchanges, let's take a look on it on this slide. And imagine an Inventor model being shared as a data exchange and referenced as a data exchange in Revit. And it's also important to note that data exchanges are versioned on the Autodesk Construction Cloud. And if there are any updates available, a notification will be displayed.

So essentially, the main purpose of a data exchange is to enhance connectivity between CAD systems. And the image on the bottom right illustrates this and shows how an Inventor model is used as a data exchange in Revit to design table trays and piping systems.

So this slide compares both workflows and their data structures. And I want to remind you to review the class handout as it will give you the chance to take your time and study these concepts more efficiently. But now I'd like to show you another case study of Magna in Graz where these workflows have been used to analyze clashes between models and a point cloud as well as clashes related to models of a production facility.

And the first video showcases a conveyor system and a steel structure implemented as an Inventor file and a STEP file, which are manually checked for clashes against the point cloud in Navisworks. Therefore, the coordination model view from the Autodesk Construction Cloud was used, and any identified issues were synchronized with the Autodesk Construction Cloud.

The next video here-- on the next video here, you can see clashes being automatically analyzed by implementing the Inventor file or the Inventor models as a data exchange. And the clashes are already structured here, which makes it easy to create issues and review them within a team.

So once more considering a typical workflow, it is always common to encounter the same problems as described in the previous use cases. But by utilizing a common data environment approach, it is important to emphasize that the coordination model being checked for clashes is always up to date and aligned with the correct or intended versions.

And the automatic clash detection feature proves highly beneficial by significantly saving time, ensuring planning continuity, and providing early feedback on design issues.

So in the final section of workflows, I'd like to demonstrate the functionalities that support factory planning in terms of comparison and evaluation processes. Now, this slide demonstrates which modules can be used to perform comparison workflows.

So it is possible to compare individual files in Docs and the design collaboration. And there is also a method to understand changes in entire coordination models. But first, let's take a look at how this appears for a single NWD file. And pay attention to the Changes windows on the left, where you can see the model structure of the selected element that has changed between selected versions.

And on the right, detailed information is provided to understand the specific changes. The same model has been used here as a data exchange in Revit. And some differences can be observed in the model structure as well as the displayed units.

Now, this comparison illustrates that there may be inconsistencies depending on how data is used in a comparison workflow. But however, it is crucial to understand and identify changes in the context of factory planning processes, which can still be accomplished.

As mentioned before, there is a method to compare specific versions of coordination models, holistic coordination models, as seen before. And this involves manually triggering a copy and saving it to Autodesk Docs. Now, these created versions of coordination models snapshots can then be compared to understand changes. And that's what you can see here on this slide.

So there is another workflow I'd like to share with you. Now, due to the complexity that machinery and equipment data can have, and in cases where a supplier doesn't want to share a detailed model due to intellectual property concerns, Autodesk Inventor can help automate simplification processes by defining certain filters and rules.

And in the final workflow, I'd like to briefly discuss Cintoo. It is an efficient tool used to analyze deviations between CAD data and point clouds or between point clouds and point clouds, as well as CAD data in combination with simulation data versus point clouds. And it serves as Magnus evaluation tool and offers functionalities that are not available on the Autodesk Construction Cloud.

And additionally, we use Cintoo to create meshes from different point cloud data sources. So in the last case study of Magna in Graz, I'd like to share an example that involves comparing simplified machinery and equipment data. And additionally, I'll demonstrate how Cintoo is utilized to evaluate deviations between a CAD model and a point cloud.

In this video, you can see models created from Factory Design Utilities along with their synchronized layouts. And as mentioned earlier, snapshots were regularly saved to Docs, allowing to compare different versions. And you can see the use of model filtering and the selection of specific elements to examine the changes.

And here at the end of the video, a production line within a 20,000 square meter building combined with the overall layout can be seen and all made possible through the simplification workflows. In this video, you can see a deviation map between the CAD model and all the stocks and the point cloud and Cintoo.

Now, these comparisons don't require any calculation time, and they can also be documented with issues and markups on the Autodesk Construction Cloud.

So let's take a final consideration between a typical approach and a common data workflow. Now, besides the common problems of sharing and tracking coordination models, A very critical issue can be added. There are no efficient ways to analyze planning iterations and what's been changed. And this can lead to significant additional costs and time.

But using a common data environment can be very beneficial for setting up coordination models and understanding planning iterations and what has changed.

So to summarize these workflows in a few words, combining Autodesk Vault as the holistic factory data management system with the Autodesk Construction Cloud as the factory planning project management is not just my recommendation. It's a logical use of systems for their intended purpose.

Then understanding the essential functionalities of workflows of BIM Collaborate, which combines Autodesk Docs, the design collaboration, and the model coordination is crucial for succeeding with the Autodesk Construction Cloud for factory planning.

And finally, I'd like to suggest that even if not everything works perfectly right now or as straightforward as expected, it is very important to submit support cases. And also, I recommend joining the Autodesk Feedback Community to share your thoughts and suggestions.

So from my side, I'd like to thank you for taking the time to listen to this presentation. I wish you success in your future projects and hope you can be even more efficient with the workflows I've shared in this presentation. So thank you and see you in the Q&A.