In the scenario described above, often, there is a critical gap in the QMS, as seen in Figure 4.0. While the analog variants — paper or pdf — will triumph over Models in a legal battle, there is potential for contractors to consume incorrect data. Legal costs and higher construc - tion costs notwithstanding, the gap in QMS of digital models open the possibility of building deficient infrastructure. Circling back to our definition of Digital Twins as comprising assets and processes, for design engineers, assets are the models (plans) they de - velop. QMS procedures are part of the process. So how could we create a “virtual representation” of these “real-world” entities and processes? One way in the engineering world is to leverage the iTwin platform, Bentley Systems’ implementation of Digital Twins. Using Bentley’s Model Review, we can create Digital Twins that are a virtual represen - tation of the assets we design and the QMS processes that we practice. In addition, with Bentley’s Model Review, we can create a virtual rep - resentation of spatial and non-spatial assets. For example, Digital plans and models, which are geospatially located, and snapshots of digital plans, such as pdfs, are examples of spatial data without a link to a digital geospatial reference. In contrast, reports and calculations are examples of non-spatial data. Virtual representations are created through Federation and Synchroni - zation. These sound like complicated terms. While the technology to implement them is complex, the concepts are relatively simple. The Architecture, Engineering, and Construction (AEC) industry has been practicing Federation and Synchronization since the beginning of the industry when the sector started producing plans. Let us consider the process of Federation. It entails creating an aggre - gate data model from multiple disparate data sources. In the analog era, it is the aggregation of plans that meet specific criteria—for example, compiling a set of plans that provide information on all the Drainage features in the project. Synchronization, on the other hand, is the pro - cess of establishing consistency between the aggregated data model
Figure 2.0
Figure 3.0
act of performing predefined checks. While Quality Assurance pro - vides confidence that appropriate Quality Control checks have been completed. Quality Assurance contains artifacts to prove that Quality Control was completed. Robust QMS exists within the engineering community when deliver - ing plans; an overview of the typical process is shown in Figure 2.0. A detailed process of quality control and assurances is depicted in Figure 3.0. The acts of performing checks, fixes, and verification constitute Quality Control. The artifacts, or proofs, generated from the Quality Control assure that agreed-upon quality control was performed. Both Quality Control and Quality Assurance together form the QMS 3 . Even when Models are used and exchanged in projects, it is for infor - mation purposes only. The by-products of Models, paper plans (or the pdf variant) are upheld as legal documents. As seen in Figure 1.0, more than fifty percent of the DOTs fall in this category. Critically, in this scenario, when models are shared but not as a legal document, often there is a gap in the QMS.
Figure 4.0
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