Benefits of MHSS in AM/FM MHSS utilizes a standardized scoring system to enable dedicated AM/FM management supported by objective facility data. It creates a friendly onboarding process for unseasoned staff with a gentle learning curve and comprehensive facility information. It allows the users to ac- cess different data aggregations from multiple perspectives to deepen their understanding of the whole building/facility. Most importantly, it avoids an overdependence on experience-oriented O&M practices to make the FM/AM program flexible, adaptive, and more resilient. Its direct contributions are cost-savings and enhanced O&M efficiency/ef - ficacy. Another notable benefit of MHSS lies in its capability of storing, analyzing, learning, and then providing predictive decision-making support via years of iteration. As illustrated in Figure 3, information from historical archives, discrete data silos, historic sensor readings, or daily reports from the Computerized Maintenance Management system (CMMS) will be gradually integrated and purified from “dis - ordered and fragmented assets” into “intangible and decision-making supported digital assets,” which are as crucial as physical ones. Figure 2: Correlation between Enterprise-level Health Scores and Health Scores of Five Essential Digital Twin Modules. Credit: Kai Yin and Jiayi Yan
O&M management system accumulating data, including the decisions made by the facility managers for different events, and algorithms, co- efficients, and threshold adjustment of the scoring system can become training data to adjust the O&M management system to meet the cur - rent project needs. MHSS Scoring Mechanism After establishing MHSS methodology, the next step is to consider its practical application mechanism. As the two previous articles men- tioned, there is a need for multi-level user data management, as shown in Figure 1. According to the decision maker’s role and responsibility, user requirements can be divided into three levels: (1) the technical level for daily O&M; (2) the middle-level for project integration and management; and (3) the owner-level for overall decision-making and control. However, the MHSS with the five listed modules cannot fully satisfy these requirements based on these multi-level user data man- agement requirements. Therefore, it is essential to include weighted coefficients based on the users’ level and their roles to accurately ob - tain the evaluation scores for the overall health of the current project. Table 1: A sample of modular health scoring categories, coefficient, and parameters. Credit: Kai Yin and Jiayi Yan
Figure 3: Evolution of Assets from “Disordered” to “Ordered.” Credit: Kai Yin and Jiayi Yan
Additionally, the MHSS powered DMSS is an essential component of Enterprise Asset Management (EAM) that oversees the entire facility from a high level. Most of the time, detailed asset data requires corre - sponding Subject Matter Experts (SMEs) (i.e., Structure, MEP, HVAC, etc.) to utilize. For non-technical/engineering staff, the scoring system is a quantifiable method that is straightforward enough to make high-level decisions or plan strategies. Recalling the “3X3” principles discussed in the first article , the MHSS powered DMSS is the final execution of that concept. With the creation of different permission groups, the user will be able to log into their own dashboard tailored specifically to their needs. Achieving this goal breaks down the “knowledge/technology barriers” between all staff and stakeholders to let them communicate and share insights in an open environment. Lastly, DMSS should also
For companies or organizations with multiple projects and facilities, the overall corporation scores can be the aggregate of each individual project score multiplied by its weighted coefficient, as shown in Figure 2. Based on these scores, facility managers can quickly locate the prob- lem with an individual project or module, specific piece of equipment, or personnel issue and make timely decisions. Figure 1: Multi-level User Data Management Requirements. Credit: Kai Yin and Jiayi Yan
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october 2021
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