Upon retrospection, most MEP professionals, may it be MEP contractors or HVAC contractors, are of the opinion that when Navisworks was first introduced it revolutionized their means of clash detection and resolution. Inclusion of viewpoints, clash reports, Excel worksheets, BIM execution plan and file management using cloud technology paved a pathway for these professionals to turn up with the most creative ideas.
However, the practices are indicative to the fact that it involves tremendous efforts to fix these clashes and coordinating every little detail is cumbersome. The current approach of batch reporting of clashes contains numerous errors and can take up to months to resolve them. Besides, these prolific clashes require skills and collaboration for mitigation of their effects. Most MEP design engineers working in large commercial or public building construction projects, with or without Autodesk Revit; look at clash detection as a crucial challenge.
On the contrary, professionals who have developed a foresight saw this approach to be turning out inefficient in keeping up the market demands, a few years from now.
MEP consulting and design firms, along with MEP and HVAC contractors have realized that clash detection and resolution form a critical part in meeting committed deadlines, avoiding rework and materials wastage; and now is in need of a facelift. The batch clash detection has to be made continuous and this was the catch in cutting short the currently elongated time lags. Their anticipation for the need of continuous clash management and the need to resolve them in real time is essentially the key to disrupt the challenges faced in meeting deadlines.
Some essential features
Talking about the continuous clash detection strategy in MEP model the current common platform based software has its limitations in more than one aspect. Say for instance, these software deals clash detection as a separate process from the core modeling and delivers aggregated clashes in batches. Besides the time lag is also considerable and solving these errors takes up a fair amount of time.
On the other hand, the continuous clash detection process demands various features like real-time clash detection, integration of clash with model, increases available metadata and finally various file sharing for immediate model updates and establish enhanced collaboration.
Unique qualities that can be achieved with consistent clash detection
Let us look at some of the unique and preeminent qualities that come along with the continuous clash detection strategy:
- Real-time clash detection in MEP modeling, the tracking of clashes is soon when it is created; as a result, clashes are continuously tracked and managed which eliminates the need to deal it separately. It eliminates the concept of maintaining a ‘clash-ledger’ and dealing one by one.
- It actively manages a metadata for each of the clash created, with the detailed set of database containing details such as date and time of the creation, modeler who created it, systems and files that were in use when the clash was generated and such other relevant information.
- It determines many management methodologies equipped clash tracker that are rich with information pertaining to any of the error in model, deeper with metadata and of higher granularity than the traditional batch clash detection approach.
- It also eliminates the manual input to close any issue of the clash. Just as when the clashes are detected and an issue to solve them is generated, they are flagged as solved once dealt with completely saving the additional time lag required in manual closing.
- It maintains and updated database with a list and detailed information for the clashes generated since the beginning until the finalization. With such continuous approach, each clash will have meaningful data to it.
Continuous clash detection is a game changer for clash detection not only because it has a quicker clash detection techniques but also because it runs actionable information throughout the project. It allows coordination meetings to be more strategic and focused on concerning issues. It helps streamlining the modeling efforts and deals the clash detection as a part of modeling; saving ample amount of time.
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