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The advancement of technology and information systems have pushed the world into a data explosion era. The capture capability and focus of information has evolved from products, services, and customers, to the current data-centric status. With the enrichment of available data, the potential becomes limitless to apply it to enable higher performance design, more efficient construction processes, and more effective operations and maintenance solutions. However, it also introduces another layer of complexity that has never been experienced before. A simple data base is no longer sufficient. The means and method of how to collect, manage, distribute, and streamline the data from dif- ferent stakeholders for various building lifecycle stages has become the determining factor for the overall performance, effectiveness, and efficiency of the design, construction, and operations and maintenance. The development of the ISO 19650 series and various classification standards, i.e. COBie, Uniformat™, aim to address the need for in- formation standardization. While ISO 19650 is still being developed, there is an urgent desire for an immediate solution. None of the exist- ing coding standards can fully address the needs during the hand-off process nor are sufficient to support asset management. This leads to various “Frankenstein” solutions arising from individual organizations that need to tailor standards for their specific data requirements. To that end, this article introduces an Facility Management- (FM) ori- ented Data Dictionary Management System (DDMS) as the conceiv- able and practical solution to bridge the gaps of the project lifecycle delivery. It can potentially support the future ISO 19650 Series when it is released and serves as the foundation of the data management for the FM digital twin. This article first reviews the current as-is condition during the handoff process and the issues found in traditional asset management practice, followed by introducing the example of a cus- tomized FM-oriented Data Dictionary Management Solution. Lastly, it depicts how an FM-oriented Data Dictionary can change asset man- agement and serve as the backbone of the FM digital twin. As-is Condition While there are foreseeable long-term benefits of BIM integration from the Project Information Model (PIM) to the Asset Information Model (AIM), the experience of the practical applications is far from ideal. On top of that, there is an inherent data management issue during the operations and maintenance stage. Part 3: Implementation of An FM-oriented Data Dictionary Management System (DDMS) for Lifecycle Project Delivery Continued from PARTS 1 AND 2 By Dr. Eve Lin, Dr. Xifan (Jeff) Chen, and George Broadbent New Era of BIM Lifecycle Implementation
Figure 1: As-is IPD Scenario
Gaps from PIM to AIM As discussed in the previous two articles in this series, despite the availability of several classification standards based on owners’ experiences, they spent extra time and effort on overcoming dif- ficulties regarding data sufficiency, interoperability, and consistency from upstream phases (i.e., design, construction, commissioning). The main contributing factor is the lack of an industry-accepted asset data classification and codification. Moreover, several essential data requirements for the facility management stage fail to be encompassed in the Integrated Project Delivery (IPD) Process, and BIM Executive Plan, contractual language (as shown in Figure 1). At the outset of its initiation, all the project stakeholders, i.e., architects, engineers, and contractors, should be around the table drafting, and developing their project deployment plan to streamline the design construction process. Unfortunately, facility managers are often the ones left out during the planning. Before occupancy, when the owners or facility managers acquire as-built models for the use of their operations and maintenance (O&M) routines, the delivered models contain all the details with per- fect graphical representations. But they are missing the data required for facility management, i.e. warranty information, serial numbers; or have inconsistently populated data, like manufacturer, model numbers, etc. The reason is because during the delivery phase, designers, general contractors, and commissioned parties don’t fully comprehend what the facility manager needs. Meanwhile, there are no specific AM (As - set Management) /FM data requirements or standards to regulate Qual - ity Assurance/Quality Control (QA/QC)) for their data submission. In spite of early project integration efforts, without a standardized and accepted data dictionary that meets their asset data management needs, each stakeholder still works in their own silo, focuses on their own specifications, uses different contractual languages, and has different sets of parameters in their PIM. When the time for handoff comes at the end of construction, the scattered information becomes unmanage- able and difficult to consolidate. Before a feasible AIM can be formed and input into a maintenance management solution, additional work and resources are required to untangle this inconsistent and ambiguous data, as well as gather all the missing information from the PIM. Issues in Traditional Asset Management Data Dictionaries Besides the aforementioned gaps between PIM and AIM, there are several inherent issues and drawbacks within the traditional asset management realm. The first regards the asset management data dic - tionaries, which are typically either maintained or directly hosted on Computerized Maintenance Management Systems (CMMS), such as IBM Maximo®, SAP, or Archibus. For example, when setting up a Maximo® environment, it is necessary to define a set of classifica -
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csengineermag.com
october 2020
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