Ceiling vs Slab
Core vs Columns
Structure vs Services
Total Clash Batches: 18
Each student is responsible for:
~9 clash batches
Grouping clashes based on similarities TASK 1 OBJECTIVES & ACTIVITIES (REVIZTO)
Append all discipline models
Publish to cloud
Ensure shared access
Apply discipline colours using Appearance Profiler
Verify consistency across models
Isolate allocated levels
Identify and tag issues
Assign severity and discipline
Track up to 20 issues per level
Refine to top 2 critical hotspots per level
Collaboration via stamps
Importance of visual checks
Limitations of manual checking
Create search sets
Run clash batches
Group clashes
Report key clash groups
This assessment focuses on model-based design coordination and clash detection using BIM collaboration tools, primarily Revizto. Students are required to undertake both manual and automated clash detection processes across federated discipline models to identify, analyse, and resolve design conflicts.
Key technical requirements include coordination of Ceiling vs Slab, Core vs Columns, and Structure vs Services, resulting in a total of 18 clash batches. Each student is individually responsible for approximately nine clash batches, with clashes grouped based on similarity in type, severity, location, and affected disciplines.
The assessment requires students to:
Federate multiple discipline models into a single coordinated environment
Apply appearance profiling to visually distinguish trades
Identify and document critical clashes through visual/manual inspection
Conduct automated clash detection using defined search sets
Analyse, group, prioritise, and report clashes with clear recommendations
The final outcome is a structured interference check report demonstrating technical competence, coordination understanding, and professional-level BIM communication.
The academic mentor guided the student through a structured, staged workflow aligned with industry BIM coordination practices. Each step built progressively on the previous one to ensure clarity, technical accuracy, and assessment compliance.
The mentor first guided the student in federating all discipline-specific models (architectural, structural, mechanical, electrical, hydraulic, and fire) into a single Revizto project. Emphasis was placed on:
Appending the latest model versions
Publishing the federated model to the cloud
Ensuring shared access across the project team
This step established a single source of truth, forming the foundation for all coordination and clash detection activities.
Next, the mentor explained the importance of appearance profiling for effective visual coordination. The student was guided to:
Apply discipline-specific colours using the Appearance Profiler
Verify consistency of colours across all appended models
Review other team members’ models for compliance
This step significantly improved model readability, enabling faster identification of clashes during both manual and automated checks.
The mentor then introduced the manual clash detection process, focusing on visual inspection skills. The student was guided to:
Isolate the allocated typical and atypical levels
Navigate the model to identify visible clashes (“hot spots”)
Tag issues using stamps and mark-ups
Assign severity levels and responsible disciplines
The mentor emphasised that this process builds spatial awareness and construction logic, which automated tools alone cannot provide.
To align with assessment requirements, the mentor instructed the student to:
Track up to 20 issues per level during the initial review
Analyse severity, constructability impact, and trade responsibility
Refine findings to the top two critical clashes per level
This step helped the student develop prioritisation and decision-making skills, ensuring that reporting focused on issues with the greatest project impact.
The mentor then guided the student in reflecting on the manual coordination process, highlighting:
The role of collaboration through stamps and issue comments
How interdisciplinary discussion supports clash resolution
The limitations of visual checks, such as hidden or tolerance-based clashes
This reflection reinforced the importance of combining human judgement with digital tools.
Finally, the mentor guided the student through the automated clash detection workflow, including:
Creating search sets aligned with the clash matrix
Running clash batches for Ceiling vs Slab, Core vs Columns, and Structure vs Services
Grouping clashes based on similarities (type, severity, location, and trades involved)
Reporting two key clash groups per batch with resolution recommendations
The mentor emphasised structured reporting and clear communication suitable for contractor-led coordination environments.
Through this guided process, the student successfully produced a structured interference check report supported by visual evidence, clash analysis, and professional recommendations.
Understanding of BIM-based model federation and coordination
Practical application of manual and automated clash detection
Development of visual literacy and spatial coordination skills
Ability to prioritise clashes based on severity and constructability impact
Effective use of Revizto collaboration, issue tracking, and reporting tools
Improved interdisciplinary communication and coordination awareness
By following a mentor-led, step-by-step approach, the student was able to meet all assessment requirements while gaining industry-relevant BIM coordination skills. The combination of structured guidance, progressive task execution, and reflective analysis ensured that both the technical outcomes and learning objectives of the assessment were successfully achieved.
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