How to Ensure BIM Quality Assurance and Validation: Best Practices and Key Steps

Building information modeling has been an essential part of the majority of complex construction projects in recent years, offering an increased level of efficiency, precision, and collaboration. The ability to create a digital copy of the future building’s parameters and characteristics makes it possible to have an unprecedented level of clarity during all of the major phases of construction, from design to building.

At the same time, the sheer complexity of BIM means that there is no widely accepted standard for BIM environments in specific parameters, which can lead to quality issues in the future. With that in mind, the importance of BIM Quality Assurance and Validation becomes obvious.

The primary purpose of these processes is to ensure the accuracy and consistency of BIM models while also checking for errors that might affect the state of the project state in the future and lead to complex rework. Being able to avoid mistakes and errors during on-site construction (which have been common for the industry for decades) can save a lot of time and resources for the project as a whole.

Our goal in this article is to explore and explain the necessary steps for creating flexible and useful BIM QA and Validation processes while also discussing best practices that may help. We are also going to provide a useful checklist for QA/QC processes in BIM environments and explain how some of these processes can be streamlined and improved.

Definition of BIM Quality Assurance and Validation

BIM Quality Assurance

BIM Quality Assurance (BIM QA) is the important process of creating the set of protocols and standards used to build and develop BIM models in specific cases. The primary purpose of BIM QA is to ensure the consistency and accuracy of BIM models while making sure they meet all project requirements.

The majority of QA processes are systematic reviews and checks performed at different stages of the modeling process in order to verify adherence to standards while ensuring that all of the information necessary for successful project execution is included in the project model. Being proactive in BIM environments (and the construction industry) makes it possible to verify whether BIM models are compliant with both project-specific requirements and general industry regulations.

One of the most important advantages of QA is the ability to reduce the possibility of the miscommunication and project errors that often lead to project delays, expensive rework, and budget overruns. The consistency and thoroughness of the implementation of QA in BIM can positively influence an issue that has plagued the construction industry for many decades.

BIM Validation

Making sure that the BIM model is aligned with all the operational and construction requirements of the project is the primary goal of BIM Validation. It confirms whether the BIM model and all of its components are correct and suitable for creation in the real world, verifying the model’s suitability for fabrication, maintenance, construction, etc.

Validation is performed to catch mismatches and errors between the model and its future physical re-creation. Being able to catch these issues early on makes it much easier and less expensive to resolve them compared with costly rework during the actual construction phase.

Value of BIM QA processes in the construction industry

Despite its initial reluctance and conservative nature, the modern construction industry is quite advanced and fast-paced. The complex nature of most construction projects in this environment means that even the smallest errors in a BIM model may rapidly escalate into substantial issues in later stages of the construction process.

The lack of proper quality control in BIM environments often leads to data inaccuracies, miscommunication, and even design discrepancies, all of which can lead to a number of serious issues down the line, such as rework, delays, or structural failures.

Example #1:  If there is an electrical system that was not modeled correctly in the BIM model, and the QA process is not able to catch it, then the on-site construction will inevitably encounter significant delays and the substantial additional expenses necessary for the retrofitting process.

Example #2: The lack of proper coordination between the mechanical and architectural systems in a BIM model can lead to inevitable clashes between the structural elements of the building and the ductwork during on-site construction. At that point, these issues can be resolved only via a substantial extension of the project timeline in combination with an expensive reengineering process and a significant budget increase.

From these examples and the general information about the topic, we can highlight some of the most noteworthy advantages that BIM Quality Assurance offers:

• Cost savings, made possible by the lack of construction clashes and design errors.
• Efficiency improvements, reducing the potential for last-minute changes and improving the possibility that construction projects are finished on schedule.
• Better coordination between departments because mistakes are found early on, serving as a reminder for similar situations in the future.
• Regulatory and compliance alignment ensures that the entire BIM model follows all of the necessary specifications, standards, and requirements, dramatically reducing the potential of non-compliance issues and improving the reputation of the construction team.

BIM Quality Assurance: Key Steps

The process of Quality Assurance in a BIM environment can be divided into three large categories depending on the current phase of project realization. It should be noted that the phases mentioned here are not directly associated with the commonly accepted phases of project realization (design, construction, etc.), because the majority of BIM QA processes revolve around the “modeling” phase.

Pre-Modeling

A substantial part of the BIM QA process occurs even before the model creation process is initiated, with just one word in mind: standardization. Correctly established protocols and standards for QA should set clear and achievable expectations for the quality of the different parts of the BIM model.

The most noteworthy element of this section is the creation of a BIM Execution Plan (BEP). This plan can be used to highlight a lot of useful information about the way BIM elements must be executed in a given project, such as naming conventions, data standards, tools, or file management protocols.

This is also where the bulk of data collection and organization efforts should be taken. Every BIM model is a treasure trove of information, but it must be collected and structured in a way that allows for seamless interaction without affecting the performance of the environment.

A clear definition of the roles and responsibilities of all users involved in a project dramatically reduces the possibility of miscommunication while making sure that the project is able to meet both regulatory standards and the expectations of the project owners. A variety of checks and review points for the future should also be set up here, increasing the probability that errors are caught early on without going over budget or exceeding deadlines.

Modeling

Accuracy becomes paramount as soon as the modeling process begins. Maintaining the integrity of a BIM model can be challenging without a defined set of best practices to follow. While the exact guidance and recommendations at this stage differ dramatically for different models, we can provide a general set of recommendations that should be performed when working on a BIM model with a QA mindset. These recommendations are presented in a separate section of this article as a checklist for improved convenience.

Regular clash detection checks are some of the most important actions at this stage to ensure that there are no conflicts between different building systems, such as mechanical, electrical, or structural elements. Solutions such as Revizto provide thorough and versatile clash detection capabilities in order to analyze the model and identify potential issues while also maintaining seamless cooperation and communication between team members who are working on the same project to guarantee the absence of miscommunication and improve efficiency.

Post-Modeling

The post-modeling stage is also often called the validation process, making it similar to the BIM validation process we discuss above. The purpose of validation is to work through a final set of checklists before signing off on the model itself, so the model must be complete, fully compliant, and meet all the project requirements without error. It is also not uncommon to use various automatic validation tools at this stage, detecting and resolving potential inconsistencies that may have been missed.

Making sure that the entire model is ready to be used as a guideline in a real-world construction process is paramount, and all of the systems must be integrated correctly. A final check like this is necessary to avoid errors during construction, cost overruns, project delays, and so on.

BIM Quality Assurance Checklist

The checklist is used in different stages of the creation of the BIM model in a hierarchical fashion, with one section following another.

1. Model integrity checks confirm the major definitions in a 3D BIM model, ensuring accurate naming conventions, appropriate IFC class mapping, valid layer management, and correct object tagging.
2. Physical representation check criteria verify that the space between all major elements is within the acceptable limits while also checking the unique identifier of the space numbers in the BIM data.
3. Design quality check revolves around the correct setup for materials and other parameters for BIM objects, as well as matching architectural property lines and building dimensions with their on-site counterparts.
4. MEP clash check ensures the level of presentation of each of the MEP elements and their potential for clashes with other objects in the BIM model.
5. Construction quality check covers the structural quality of the BIM data in the model. This mostly revolves around clash coordination between the building objects in the model: beams, columns, and slabs.
6. Regulatory alignment check is a self-explanatory recommendation to ensure compliance with standards and regulations, both industry-wide and project-specific. The BIM model must be mostly or fully developed so it can be verified against regulatory frameworks or external guidelines, which is why this recommendation is so low on the list.
7. Model completeness often serves as a final model check. It covers most general tasks that have not already been covered, including the verification of work sets, cleanup for unnecessary groups, views, and plans, error resolution, and other similar tasks.
8. Project output covers the generation of accurate documentation based on the complete BIM model: schedules, drawings, and reports. All model revisions should be documented and marked properly, as well.

It should be noted that one of the most important parts of these checklists is to use them as templates to be modified for particular industries and situations, rather than followed to the letter.

Best practices for BIM Quality Assurance

While the argument could be made that these checklists are sufficient “best practices” as it is, we can still provide a few more recommendations on what can be done to improve the quality of BIM models. There are at least two large “groups” of best practices that we can present here:

• Collaborative validation
• Continuous auditing and automation

Collaborative Validation

Since collaboration is one of the most noteworthy advantages of BIM, it is only natural that quality assurance processes involve a collaborative environment as well. Collaborative validation is a process of multiple disciplines working together on the same project to validate and review the model at different stages of its creation.

The involvement of different experts and specialists in the model verification process brings in multiple interesting perspectives that increase the chances that errors are identified and resolved, improving the overall quality of the project. The encouragement of open communication between stakeholders at different stages of the QA process makes a much more nuanced and thorough approach with fewer errors and better results possible.

Continuous auditing and automation

Quality checks do not have to be restricted to specific stages of model creation. They can (and should) be performed throughout the entire model creation process using a continuous auditing system. This way, most issues can be resolved as early as possible while maintaining compliance and improving model quality.

Consistent auditing processes are known for improving project quality by minimizing costly rework and notifying the responsible parties of noteworthy discrepancies. Many companies rely on third-party software to perform such processes, which is how we transition to the topic of automation.

The introduction of third-party solutions into the auditing process can improve its capabilities even further, automating a lot of the auditing process to look for errors and discrepancies with minimal human intervention. There is an entire market of automated solutions for BIM quality verification, with features such as compliance verification, model validation, clash detection, and so on. Another important advantage of automation in quality assurance is the ability to reduce the complexity of processing large and complex BIM models.

As an example, solutions such as Revizto make it much easier to perform clash detection and issue-tracking processes using a convenient solution with extensive collaborative capabilities.

Overcoming common challenges in BIM Quality Assurance and Validation

As we have mentioned, the process of BIM Quality Assurance and Validation differs depending on the target industry and several other factors. However, we can highlight two common challenges that the introduction of BIM QA brings which apply to the majority of BIM projects:

• Data management is always a concern when it comes to BIM models because they store so much information, such as material specifications, on top of an existing geometric structure. The lack of defined data management practices is bound to spawn more and more data discrepancies and inaccuracies as time goes on.
• Interdisciplinary coordination was challenging before the mass introduction of BIM, and it remains a noteworthy issue in many situations to this day. The vast and complex nature of the construction industry creates a lot of specialized software that can rarely be used to export information or interact with other project participants. The introduction of BIM as a centralized source of information dramatically reduced the impact of this issue, but third-party solutions still must be able to export their information to BIM systems so it can be shared with other stakeholders.

Luckily, most major issues like these can be resolved with relative ease if there is enough effort and preparation involved.

The creation of structured and well-documented data management protocols can dramatically reduce the chaotic nature of large-scale BIM models in terms of data management. Performing regular storage audits with the help of industry-specific software and investing in cloud-based centralized data storage environments might also be viable as potential solutions to this issue.

The implementation of tools and services for real-time collaboration and the introduction of regular coordination meetings should be able to improve the transparency of work processes and improve interdisciplinary coordination. Working with open standards and formats such as IFC or COBie provides a lot more freedom of interoperability in many use cases, while the integration of clash detection solutions with clear communication capabilities (such as Revizto) helps when it comes to resolving interdisciplinary conflicts and clashes if there are any.

Conclusion

BIM Quality Assurance and Validation is a necessity for all modern BIM environments due to the ever-rising quality and performance standards in the industry. BIM is becoming more and more widespread, and the standard of what is acceptable is getting higher and higher. In this context, being able to combat most, if not all, issues with BIM models with defined processes and detailed checklists seems like the lesser evil, if nothing else.

Aside from making it much less likely that BIM models with many errors are produced, BIM QA and Validation also improve the accuracy and reliability of construction projects, with massively helpful clash detection and other measures. Solutions such as Revizto are a great help in complex BIM QA tasks, offering comprehensive clash detection and issue tracking capabilities with granular access to specific issues and easy communication between stakeholders when necessary.

The abundance of tools and measures to assist with these issues offer a lot of accessibility for less experienced users. Additionally, BIM QA is quickly becoming the norm rather than an extra step, which is why we recommend researching the topic thoroughly due to its value in a company’s overall success.

Frequently Asked Questions

Is there a difference between BIM QA and BIM Validation?

The most noteworthy difference between the two is the timing of their implementation. BIM QA is usually implemented throughout the entire modeling process, while Validation is mostly performed near the end of the modeling process.

Their purposes also differ significantly, since the former revolves around process control and model consistency, while the latter is more about the outcome of the modeling process being aligned with all the necessary requirements and factors so that a real-life structure can be implemented with no issues.

Can small or medium-sized businesses on a budget afford BIM QA processes?

It might seem difficult to cover all of the necessary elements in a BIM QA checklist if your company is on a budget. However, there are many other ways to perform the same processes at much lower cost.

For example, some tools for clash detection or model checking are either free or have low cost, and many BIM solutions even have built-in quality control features for validation or auditing. The creation of an internal QA team can be replaced by the outsourcing of specific QA tasks to reduce overhead without lowering the quality of the analysis.

Lastly, some of these processes are only partially connected with the topic of budgeting, including both education and the establishment of clear standards, neither of which needs a dedicated solution (only time and effort).

What is the difference between Quality Control and Quality Assurance in a BIM environment?

Quality Assurance in BIM ensures that the model is created in accordance with specific guidelines. It is a proactive approach at its core, affecting the model creation environment at different stages of the project lifecycle.

Quality Control, on the other hand, is a much more reactive process that always occurs when the model itself is already complete and is inspected or verified. Both processes have their own levels of depth, but Quality Assurance can usually resolve more errors than Quality Control due to the ability to affect different parts of the model creation process.