We recently had a virtual fireside chat with ChatGPT, asking the famous AI a dozen of questions around the positioning of Samp. ChatGPT will take you through the key concepts by which Samp delivers value to water and energy operators.
Note: all answers are reported without any editing (except for the font format)
Is it possible to link P&ID objects with their representation in a reality capture 3D point cloud?
Yes, it is possible to link P&ID objects with their representation in a reality capture 3D point cloud.
This can be achieved through various means such as image recognition and object tracking, registration of the 3D point cloud data with the P&ID, and by incorporating metadata and semantic information into the 3D point cloud data.
By linking the two, it can help improve the accuracy of the representation and provide a better understanding of the physical assets in the real-world environment.
Could you list possible use cases of such “piping and instrumentation point clouds”?
Yes, the linking of P&ID objects with 3D point clouds can have various use cases in the construction, engineering, and maintenance industries, including:
- Planning and design: The linked point clouds can be used for facility planning, design and engineering.
- Asset management: The linked data can provide more accurate information on physical assets, including their location, condition and maintenance history.
- Construction management: The linked data can be used to verify and validate the construction process and ensure accuracy and consistency between the design and physical build.
- Maintenance and inspection: The linked data can be used to plan maintenance and inspection activities, identify potential issues and support decision making for maintenance and repair work.
- Quality control: The linked data can be used to verify the quality of installed equipment and systems and ensure they meet design specifications.
- Virtual and augmented reality: The linked data can be used to create virtual and augmented reality experiences, allowing users to experience and interact with the physical facility in a simulated environment.
- Training and simulation: The linked data can be used for training and simulation purposes, allowing workers to practice tasks and procedures in a virtual environment before performing them in the real world.
How to estimate the typical value of these use cases for an average industrial facility? Could you propose a formula for each?
Estimating the typical value of the use cases for linked P&ID and 3D point cloud data in an average industrial facility can be challenging and would depend on several factors specific to each facility. However, a general formula that can be used to estimate the potential value is:
Value = (Savings from reduced downtime + Savings from improved maintenance and inspection + Savings from reduced errors and miscommunications + Savings from improved design and planning) – Cost of implementing linked P&ID and 3D point cloud data
Here, the cost of implementing linked P&ID and 3D point cloud data would include the cost of acquiring and processing the 3D point cloud data, the cost of integrating it with the P&ID data, and any ongoing costs for maintenance and updates.
- Savings from reduced downtime: This can be estimated by multiplying the average daily cost of downtime by the expected reduction in downtime as a result of implementing linked P&ID and 3D point cloud data.
- Savings from improved maintenance and inspection: This can be estimated by calculating the cost of manual maintenance and inspection activities and comparing it to the cost of automated maintenance and inspection using linked P&ID and 3D point cloud data.
- Savings from reduced errors and miscommunications: This can be estimated by calculating the cost of errors and miscommunications that occur as a result of incorrect or incomplete information and comparing it to the cost of errors and miscommunications with the implementation of linked P&ID and 3D point cloud data.
- Savings from improved design and planning: This can be estimated by calculating the cost of manual design and planning activities and comparing it to the cost of automated design and planning using linked P&ID and 3D point cloud data.
When a lower level of details is needed and facilities have limited access or complex structures, how does the speed and cost of acquiring 3D point cloud data with mobile scanners compare with the cost of acquiring 3D point cloud data with terrestrial laser scanners?
When a lower level of detail is needed and facilities have limited access or complex structures, mobile scanners can be a better option compared to terrestrial laser scanners. This is because mobile scanners are typically more portable and can be used in a wider range of environments, making them a good choice for facilities with limited access or complex structures. Mobile scanners are also typically faster and more cost-effective for smaller or simpler environments, as they can be moved quickly and easily from location to location.
However, the cost and speed of acquiring 3D point cloud data with mobile scanners can still vary widely depending on the size of the facility, the complexity of the environment, and the desired level of accuracy. Mobile scanners may not be able to achieve the same level of accuracy and detail as terrestrial laser scanners, as they rely on smaller sensors and can be affected by motion during the scanning process.
Terrestrial laser scanners, on the other hand, are typically more accurate and capable of capturing higher levels of detail, but they are also more expensive and require more time to set up and use. Terrestrial laser scanners are typically used in larger or more complex environments where a high level of accuracy is required, or in situations where the environment is too large or complex for a mobile scanner to be used effectively.
In general, when a lower level of detail is needed and facilities have limited access or complex structures, mobile scanners can be a good choice, but the specific choice between mobile scanners and terrestrial laser scanners will depend on the specific needs and circumstances of each facility.
When sharing linked P&ID and 3D point cloud data, why is it better to rely on a streaming web portal rather than file exchanges with an executable software?
Relying on a streaming web portal for sharing linked P&ID and 3D point cloud data can have several advantages compared to file exchanges with an executable software:
- Accessibility: Streaming web portals allow for remote access to the data from any location with an internet connection, making it easier for multiple stakeholders to access the information they need.
- Collaboration: Streaming web portals often have built-in collaboration tools, allowing multiple stakeholders to work on the data simultaneously in real-time, leading to more efficient and effective collaboration.
- Security: Streaming web portals typically have robust security measures in place to protect the data, reducing the risk of data breaches and unauthorized access.
- Version control: Streaming web portals often have version control features, allowing users to track changes made to the data and revert to previous versions if needed.
- Ease of use: Streaming web portals are typically user-friendly and require no specialized software or hardware to access, reducing the need for training and technical support.
- File exchanges with an executable software, on the other hand, can be more complex and require the use of specialized software and hardware, as well as a higher level of technical expertise to access and use the data.
In general, streaming web portals offer a more accessible, secure, and user-friendly solution for sharing linked P&ID and 3D point cloud data, making them a better option for many industrial facilities.
What is the value of using georeferenced point clouds linked with P&ID, compared with only point clouds linked with P&ID? Could you give examples?
Georeferenced point clouds linked with P&ID provide additional value compared to only point clouds linked with P&ID. This is because georeferenced point clouds are anchored to a real-world coordinate system, allowing them to be easily integrated with other geospatial data, such as maps, satellite imagery, or building information models.
Here are some examples of the added value of using georeferenced point clouds linked with P&ID:
- Location-based analysis: Georeferenced point clouds linked with P&ID can be used to perform location-based analysis, such as determining the proximity of potential hazards to specific assets, or determining the impact of construction activities on nearby assets.
- Asset management: Georeferenced point clouds linked with P&ID can be used to create an up-to-date digital twin of an industrial facility, allowing for improved asset management and maintenance planning.
- Emergency response planning: Georeferenced point clouds linked with P&ID can be used to develop emergency response plans, such as identifying the closest fire hydrants or emergency exits, or determining evacuation routes.
- Planning and design: Georeferenced point clouds linked with P&ID can be used to inform the planning and design of new facilities, by providing accurate and up-to-date information on the existing environment and infrastructure.
In conclusion, georeferenced point clouds linked with P&ID offer additional value compared to only point clouds linked with P&ID, by allowing for improved location-based analysis, asset management, emergency response planning, and planning and design.
Are georeferenced point clouds linked with P&ID commonly available?
Georeferenced point clouds linked with P&ID are not yet as commonly available as traditional 2D P&ID drawings. However, their use is becoming increasingly prevalent in the utility and oil & gas industries, as well as in other industries, due to the advantages they offer in terms of improved asset management, increased operational efficiency, and reduced downtime.
The technology for creating and managing georeferenced point clouds linked with P&ID is rapidly advancing, and the cost of acquiring and using this data is decreasing. As a result, it is likely that the use of georeferenced point clouds linked with P&ID will become more widespread in the near future.
Is it complex to link georeferenced point clouds with P&ID? Why?
Linking georeferenced point clouds with P&ID can be a complex process, especially if the data is large, complex, or if there are significant differences between the point cloud data and the P&ID data. Some of the challenges that can arise when linking georeferenced point clouds with P&ID include:
- Data accuracy: The accuracy of the point cloud data and the P&ID data must be ensured to ensure that the linked data is useful and meaningful.
- Data compatibility: The point cloud data and the P&ID data must be compatible, in terms of data format, data structure, and data quality, to ensure that they can be linked effectively.
- Data management: Large amounts of data must be managed efficiently, to ensure that the linked data is accessible, up-to-date, and secure.
- Data visualization: The linked data must be visualized effectively, to ensure that it is easily understood and used by stakeholders.
In conclusion, linking georeferenced point clouds with P&ID can be a complex process, but the benefits of having accurate, up-to-date, and accessible data can be significant. With the right tools and processes in place, the complexity of linking georeferenced point clouds with P&ID can be effectively managed, and the benefits of having linked data can be realized.
Are georeferenced point clouds linked with P&ID of value to utilities networks and plants, or to midstream oil & gas pipelines and facilities? Why?
Yes, georeferenced point clouds linked with P&ID can provide significant value to both utilities networks and plants, as well as midstream oil & gas pipelines and facilities. Here are a few reasons why:
- Improved asset management: Georeferenced point clouds linked with P&ID can provide accurate and up-to-date information on the location, condition, and capacity of assets, such as pipelines, valves, and tanks, which can improve asset management and maintenance.
- Increased safety: Georeferenced point clouds linked with P&ID can provide real-time information on the performance of assets and networks, which can help identify potential safety issues and improve overall safety.
- Reduced downtime: Georeferenced point clouds linked with P&ID can provide early warning of potential issues, which can reduce downtime and avoid unplanned maintenance.
In conclusion, georeferenced point clouds linked with P&ID can provide significant value to both utilities networks and plants, as well as midstream oil & gas pipelines and facilities, by improving asset management, increasing operational efficiency and safety, and reducing downtime.
By linking point clouds with P&ID, is it possible to get an object-oriented semantic point cloud, which could offer similar capabilities to a CAD model as a means of hosting equipment information attributes?
es, linking point clouds with P&ID can result in an object-oriented semantic point cloud that can offer similar capabilities to a CAD model for hosting equipment information attributes.
By linking the point cloud data with the P&ID data, the resulting semantic point cloud becomes more than just a collection of points in space; it becomes a representation of the physical assets, with the attributes and information from the P&ID data attached to each object.
This can provide a more comprehensive and accurate understanding of the assets, and can be used to support various applications, such as asset management, inspection and maintenance, revamping and retrofit projects, and more. By linking the point cloud data with the P&ID data, the resulting semantic point cloud can provide a complete and up-to-date representation of the assets, which can support effective decision-making and improve the overall efficiency of the asset management processes.
Why is it a more efficient route than the traditional “scan-to-BIM” approach that many operators use for facilities management?
Linking point clouds with P&ID can be a more efficient route than the traditional “scan-to-BIM” approach for facilities management for several reasons:
- Speed and Accuracy: Linking point clouds with P&ID allows for the creation of a more complete and accurate representation of the assets, as it combines the physical information from the point cloud with the functional and design information from the P&ID. This can save time and reduce errors compared to the traditional “scan-to-BIM” approach, which often requires manual input of information from various sources.
- Dynamic and Up-to-Date: Linking point clouds with P&ID allows for the creation of a dynamic and up-to-date representation of the assets, as changes to the physical assets can be quickly reflected in the point cloud and linked with the P&ID information. This is in contrast to the traditional “scan-to-BIM” approach, which often involves manual updates to the BIM model and can lead to outdated information.
- Better Collaboration: Linking point clouds with P&ID can improve collaboration between different departments and stakeholders, as it provides a common and up-to-date understanding of the assets. This can be particularly valuable in large and complex facilities, where multiple departments and stakeholders may be involved in facilities management.
Therefore, linking point clouds with P&ID can offer several advantages over the traditional “scan-to-BIM” approach for facilities management, including improved speed and accuracy, dynamic and up-to-date information, and better collaboration.
Will this approach make visual asset management more affordable to the midsize industrial operators in terms of price and implementation speed?
It is possible that linking georeferenced point clouds with P&ID can make visual asset management more affordable for midsize industrial operators in terms of both price and implementation speed. Some potential benefits include:
- Reduced Scanning Costs: By linking point clouds with P&ID, there may be a reduction in the overall cost of scanning and data acquisition, as the need for manual input of information from multiple sources is reduced.
- Faster Implementation: The process of linking point clouds with P&ID can be faster than traditional “scan-to-BIM” approaches, as it eliminates the need for manual input of information and can be automated using software tools.
- Improved Accessibility: Linking point clouds with P&ID can provide a more accessible and user-friendly representation of the assets, which can be particularly valuable for midsize industrial operators who may have limited resources for managing complex facilities.
However, it is important to note that the affordability of visual asset management using linked point clouds with P&ID will depend on several factors, including the size and complexity of the facility, the resources available for implementation, and the cost of the software and hardware required. In general, the more advanced and comprehensive the solution, the higher the cost will likely be.
