Interscale Content Hub – BIM model quality control issues are a significant factor in determining the overall success of construction projects.
As you know, Building Information Modeling (BIM) integrates digital representations of physical and functional characteristics of places, which are more than mere graphical representations.
This means BIM has complexities, data-rich, and dynamic blueprints for the life cycle of any construction project.
That’s why rigorous quality control is essential to verify that your BIM model reflects the real-world project accurately and has no misalignments or clashes.
Errors, omissions, and inconsistencies within a BIM model can lead to costly rework, project delays, and even safety hazards during construction.
If the data is unreliable or missing, then the potential benefits of BIM become severely compromised for crucial downstream processes.
Hence, maintaining high-quality BIM models is not merely about aesthetic accuracy but ensuring functionality across all project phases, from planning to maintenance.
And in this article, we’re going to define each and every detail of the BIM QC issues.
Common Quality Control Issues in BIM
On any construction project, ensuring the accuracy and reliability of BIM data is a constant battle.
The integrity of this data is often undermined by incomplete, inconsistent, or simply incorrect information woven into the model.
This has serious downstream consequences in the form of costly design errors, escalating costs, and schedule delays.
To get a details insight into quality control issues affecting the costs, kindly check “The Real BIM Implementation Costs: Is It Worth the Investment or Not?“
A significant portion of these problems can be traced back to several primary culprits.
Geometric errors are particularly pernicious. These manifest as misalignments, clashes between modeled elements, or inaccurate dimensions.
These errors often arise during the initial modeling phase and can lead to significant problems if not corrected before construction begins.
A study by Mojtaba Valinejadshoubi in “The Development of an Automated System for a Quality Evaluation of Engineering BIM Models: A Case Study” on a Canadian infrastructure project showed that using an automated quality assessment system significantly reduced these types of errors and increased the average quality score of BIM models by facilitating timely adjustments.
Imagine a scenario where a structural column’s modeled position deviates from its intended design – this can create a ripple effect of clashes during construction or necessitate expensive field modifications.
Inconsistency and inaccuracy in data is another primary concern.
Key information such as material properties, specifications, or other vital data may be missing entirely, unreliable, or contradict itself within different sections of the model.
Inconsistent information renders the BIM model useless for critical downstream processes like cost estimation or procurement, hindering successful project execution.
Beyond geometric and data-based problems, modeling errors can introduce further confusion.
Essential components may be absent from the model, or unnecessary elements may be present.
These modeling missteps can lead to ambiguity and misinterpretation, potentially leading to incorrect construction work.
Additionally, coordination issues between multidisciplinary models, such as architectural and structural, pose a constant threat.
For example, if a structural beam is misplaced relative to its architectural equivalent, costly conflicts will only be discovered during construction.
Finally, non-compliance with project-specific or industry-wide standards compromises the integrity of the model and can create interoperability problems between different software or stakeholders.
Addressing these common quality control issues proactively is essential.
Failure to do so will inevitably cause a chain reaction of negative consequences during the construction phase, putting a severe strain on project budgets and timelines.
Impact of Quality Issues on BIM Projects
The ramifications of quality issues in BIM models extend far beyond the construction phase, impacting the building’s entire lifecycle.
Ignoring quality control leads to cost increases and operational inefficiencies and can even compromise the safety and longevity of the asset. Let’s examine how poor-quality BIM models can wreak havoc on a project.
Firstly, errors lurking within a BIM model frequently go unnoticed until construction is underway.
When problems are discovered on-site, the necessary design changes cascade through the process – forcing engineers and architects to revisit the model and triggering costly rework on the physical job site.
Delays are another direct consequence of BIM quality problems. Time is lost in resolving clashes, integrating design changes, and correcting inaccurate data.
These delays throw project schedules into disarray, potentially leading to missed deadlines and contractual penalties.
Inevitably, the snowballing expenses associated with rework and delays derail project budgets.
These cost overruns can jeopardize the overall financial viability of the venture, sometimes even resulting in complete project failure.
Beyond the immediate construction phase, inaccurate or inconsistent data severely degrades the long-term usefulness of a BIM model.
Information vital for operations and facilities management may be unreliable or missing altogether.
This can translate to inflated operational costs, inefficient maintenance practices, and a decrease in the asset’s value.
Standards and Protocols for Quality Control
We need to adhere to recognized standards and established protocols for effective quality control in BIM projects.
International standards like ISO 19157 provide a comprehensive framework for defining quality measures, the scope of evaluation processes, and methodologies for assessing the accuracy and consistency within BIM models.
Let’s look into the key instruments that guide BIM quality control.
BIM Execution Plan (BEP)
This fundamental document sets the tone for the entire project. It outlines goals, defines the roles and responsibilities of all stakeholders, and most importantly, establishes the quality standards to be followed.
A well-crafted BEP lays the foundation for maintaining high-quality BIM deliverables.
Kindly check, “Is your BIM Management Plan Falling Short? A Collaboration Nightmares?“ for more details about the BIM execution plan.
Industry Standards
Adherence to standards like the National BIM Standard (NBIMS) and various ISO standards ensures a consistent approach across different teams and BIM software.
These standards offer comprehensive guidelines for modeling practices and data management.
A notable study titled “BIM-Based Quality Control for Safety Issues in the Design and Construction Phases,” by Seunghwa Park and colleagues demonstrates this impact.
Due to the sheer complexity of modern construction projects, the paper advocates for implementing automated quality-checking processes within BIM environments.
The paper also is leveraged within the paper to demonstrate the method’s effectiveness in practice.
This automated approach reinforces industry standards’ vital role in improving coordination and collaboration between project stakeholders.
The ultimate goal of such standardization is to elevate quality control practices across the entire construction industry.
Company Standards
Many organizations supplement industry-wide standards with their own internal BIM standards.
These tailored standards address specific workflows, unique data requirements, or quality benchmarks relevant to the company’s operations.
Checklist for BIM Quality Control
A well-structured checklist is the backbone of a thorough BIM quality control process. You must include procedures that validate your models.
This should include checks for proper model setup, coordination between different design disciplines, ensuring that the model accurately reflects real-world construction intent, and verifying that the final deliverables meet project-specific requirements.
Now here’s a drill down into the key areas your checklist should cover.
- Model setup and validation: This step ensures that BIM models are set up in accordance with predefined specifications and are checked for geometry accuracy and data consistency. This step includes validating model dimensions and spatial relationships, and ensuring that each model component is correctly named and labeled according to project requirements.
- Clash detection: Using advanced software tools, perform clash detection to identify and resolve conflicts between different model elements. This proactive step is crucial in preventing construction delays and cost overruns by addressing issues before they manifest on the construction site.
- Compliance checks: Ensure that all models comply with industry standards such as ISO 19650, COBie, and IFC, as well as the project’s specific BIM Execution Plan (BEP). This also includes checking the level of development (LOD) to ensure that the model meets the required detail and accuracy levels.
- Quality assurance and correction: Regularly review and correct any discrepancies found during the quality checks. This involves updating naming conventions, resolving standards compliance issues, and aligning data consistency across all models. Ensuring that each step of the model creation and revision adheres to the set standards minimizes the risk of errors.
- Final reviews and documentation: Document and report all validation results, maintaining detailed records of checks performed, outcomes, and corrective measures taken. This documentation is vital for audit purposes, ensuring transparency and accountability in the quality control process.
Tools and Technologies for Enhancing BIM Quality
Incorporating advanced tools and technologies significantly boosts the precision and efficiency of BIM quality control processes.
Firstly, specialized model-checking software offers automation that streamlines the identification of errors, clashes, and deviations from established standards.
These tools act as intelligent ‘proofreaders’ for your BIM model, tirelessly scanning for potential problems.
Collaboration Platforms, or Common Data Environments (CDEs), are another essential tool. A CDE provides a centralized, secure space for teams to share BIM models and other vital project information.
This promotes seamless communication, facilitates efficient issue tracking, and underpins a collaborative approach to resolving quality control issues.
Finally, data validation tools serve the vital function of gatekeepers.
They ensure that all information entered into your BIM model is accurate, consistent, and adheres to predefined standards.
Preventing incomplete or flawed data from entering the model is essential for maintaining its usability and integrity.
Beyond these core technologies, look to emerging innovations like the integration of BIM and Virtual Reality (VR).
The VR allows you for a fully immersive ‘walkthrough’ of your model, facilitating the visualization of potential errors or constructability problems early in the design phase.
How Our Services Can Help Your BIM Quality Control
The successful collaboration between Interscale and Ewert Leaf, a leading architectural firm, is an example of how partnering with a specialized BIM services provider can significantly enhance your project outcomes.
Our approach to BIM quality control demonstrates a commitment to leveraging cutting-edge technologies to proactively address potential issues like model errors, clashes, or data inconsistencies – all of which can derail your project if left unchecked.
Our technology-driven solutions are crucial to their success in the Ewert Leaf case study.
By utilizing advanced BIM tools and specialized workflows, Interscale is better equipped to pinpoint discrepancies that could hinder construction or lead to costly re-work.
Beyond a singular focus on error-checking, we understand the importance of continuous quality control throughout the entire project lifecycle.
This ongoing vigilance helps ensure your BIM model remains a valuable asset, from the earliest stages of design all the way through to the completion of construction.
Perhaps most importantly, the Ewert Leaf case highlights Interscale’s collaborative approach to problem-solving.
When you partner with Interscale, you gain an ally invested in proactive communication and the development of tailored quality control strategies that address the unique needs of your project.
That’s why kindly check how our Interscale BIM management can help you offload these complex BIM quality processes so you get back to doing what you do best.
Conclusion
Your teams can ensure their models are accurate, reliable, and valuable resources throughout the building lifecycle by understanding the common challenges affecting BIM models.
With a rigorous approach to quality control, you can realize the BIM model quality control issues and BIM’s full potential to streamline construction processes and reduce errors.
