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Purpose Organizations involved in facility management (FM) can use building information modeling (BIM) as a knowledge repository to document evolving facility information and to support decisions made by the facility managers during the operational life of a facility. Despite ongoing advances in FM technologies, FM practices in most facilities are still labor intensive, time consuming and often rely on unreliable and outdated information. To address these shortcomings, the purpose of this study is to propose an automated approach that demonstrates the potential of using BIM to develop algorithms that automate decision-making for FM applications. Design/methodology/approach A BIM plug-in tool is developed that uses a fault detection and diagnostics (FDD) algorithm to automate the process of detecting malfunctioning heating, ventilation, and air conditioning (HVAC) equipment. The algorithm connects to a complaint ticket database and automates BIM to determine potentially damaged HVAC system components and develops a plan of action for the facility inspectors accordingly. The approach has been implemented as a case study in an operating facility to improve the process of HVAC system diagnosis and repair. Findings By implementing the proposed application in a case study, the authors found that automated BIM approaches such as the one developed in this study, can be highly beneficial in FM practices by increasing productivity and lowering costs associated with decision-making. Originality/value This study introduces an innovative approach that leverages BIM for automated fault detection in operational buildings. FM personnel in charge of HVAC inspection and repair can highly benefit from the proposed approach, as it eliminates the time required to locate HVAC equipment at fault manually.

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In construction, workers are frequently exposed to ergonomic risks that can lead to musculoskeletal disorders. To prevent ergonomic injuries, proper assessment of ergonomic risk is a key to identifying risk factors and modifying work practice in a timely manner. In field observation, however, difficulties in visually estimating human postures (e.g., body joint angles) required for ergonomic analysis have led to inconsistent results due to the subjectiveness of observers. This study thus proposes a fuzzy logic approach to posture-based ergonomic evaluation tools. Rapid Upper Limb Assessment (RULA) is selected as a case study to describe the fuzzy logic modelling of RULA scoring systems and discuss the application to modular construction shops. The results of validation comparing correlations with biomechanical analysis — used as a ground truth — reveal that the proposed system produces more accurate results than traditional methods and hence helps minimize human errors in observation for reliable on-site ergonomic assessment.

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Building Information Modeling (BIM) is an increasingly popular method for generating and managing facility information during the life cycle of a building, ranging from facility conceptualization, through design, construction and its operational life. Organizations involved in Facility Management (FM) have the opportunity to use BIM as a knowledge repository to document evolving facility information and to support decisions made by the facility managers during the operational life of a facility. This paper demonstrates the potential of using BIM to develop algorithms that automate decision making for FM applications. The potential of utilizing BIM as an analysis tool is demonstrated through the scenario of HVAC (Heating, Ventilation, and Air Conditioning) system failure in an operating facility. In case of a typical HVAC malfunction today, facility occupants record complaints in a ticketing database maintained by the FM organization. Upon receiving notification of HVAC system failure, facility inspectors visit the location to confirm the reported failure. Upon confirmation, facility managers review building plans and specifications to develop a detailed plan of action to repair any HVAC components suspected of damage. Based on the plan of action, inspectors visit the facility to inspect and, in case of damage, repair the appropriate HVAC system components. These FM practices -as currently implemented across the industry -are labor intensive, time consuming, and often rely on unreliable and outdated information. To address these shortcomings, the authors propose an alternative methodology of HVAC fault detection in operational buildings. The authors implement an algorithm that leverages complaint ticket data and automates BIM to determine potentially damaged HVAC system components. Based on the list of HVAC components suspected of damage, the algorithm develops a plan of action for the facility inspectors. Finally, the authors discuss the advantages of the proposed method as well as the challenges of implementing automated BIM-enabled decision making processes in the FM industry.

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The AEC (Architecture, Engineering, Construction) industry is an information intensive industry and all related processes employed during different phases of a project, including planning, designing, building, manufacturing, occupying, and maintenance, involve vast amounts of data that is used for a wide variety of purposes. Building Information Modeling (BIM) is a powerful shared knowledge resource which stores this data to support decision making about a facility through all these different phases in its life cycle. Nowadays, BIM is mostly used in the design and construction phases while it can also be highly beneficial beyond those stages. For example, in the Operation and Maintenance (O&M) phase, BIM could be used for automated facilities management or robotic inspection to provide semantic knowledge for navigation. For any implementation not related to the original intent of the BIM (design), organizations need to be able to represent their project data in a common interpretable form, which provides the possibility of an accurate exchange of data among different software products and platforms, known as interoperability. This study has investigated the current state of interoperability between software products used as Building Information Modeling tools. The main focus has been on a popularly used format for BIM models, Industry Foundation Classes (IFC), since it has been specifically developed to enable standardized data exchange. The research methodology involved a comprehensive literature review and the gathering of all fragmented prior research related to the field in order to develop a consistent understanding of the current state of knowledge. This was accompanied with a detailed case study that evaluated and compared two dominant pieces of BIM software, Revit and Bentley, and examined their interoperability strengths and weaknesses while using the IFC format.