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To improve the current manual and iterative nature of clash resolution on construction projects, current research efforts continue to explore and test the utilization of machine-learning algorithms to automate the process. Though current research shows significant accuracy in automating clash resolution, many have failed to provide clear explanation and justification for the selection of their feature and label space. Since this is critical in developing an effective and explainable solution in machine learning, it is crucial to address this research gap. In this paper, the authors utilize an in-depth literature review and industry interviews to capture domain knowledge on how design clashes are resolved by industry experts. From analysis of the knowledge captured, we identified 23 factors considered by experts when resolving clashes and five alternative solutions/options to resolve a clash. Using a pool of industry experts, a modified Delphi approach was conducted to validate the factors and options and to determine a priority ranking. The authors identified 94 industry experts based on a predetermined qualification matrix to take part in the modified Delphi. Twelve participants responded and took part in the first round, and 11 completed the second round. A consensus was reached on all clash factors and resolution options. Factors including "clashing elements type," "constrained slope," "critical element in the clash," "location of the clash," "code compliance," and "project stage clashing element is in" were ranked as the most important factors, while "clashing element material" and "insulation type" were considered the least important. Participants also showed more preference to the "moving the clashing element with low priority in/along x-y-z directions" option to resolve clashes. These identified factors and options will be utilized to collect specific clash data to train and test effective and explainable machine-learning algorithms toward automating clash resolution. [ABSTRACT FROM AUTHOR]

To improve the current manual and iterative nature of clash resolution on construction projects, current research efforts continue to explore and test the utilization of machine-learning algorithms to automate the process. Though current research shows significant accuracy in automating clash resolution, many have failed to provide clear explanation and justification for the selection of their feature and label space. Since this is critical in developing an effective and explainable solution in machine learning, it is crucial to address this research gap. In this paper, the authors utilize an in-depth literature review and industry interviews to capture domain knowledge on how design clashes are resolved by industry experts. From analysis of the knowledge captured, we identified 23 factors considered by experts when resolving clashes and five alternative solutions/options to resolve a clash. Using a pool of industry experts, a modified Delphi approach was conducted to validate the factors and options and to determine a priority ranking. The authors identified 94 industry experts based on a predetermined qualification matrix to take part in the modified Delphi. Twelve participants responded and took part in the first round, and 11 completed the second round. A consensus was reached on all clash factors and resolution options. Factors including "clashing elements type," "constrained slope," "critical element in the clash," "location of the clash," "code compliance," and "project stage clashing element is in" were ranked as the most important factors, while "clashing element material" and "insulation type" were considered the least important. Participants also showed more preference to the "moving the clashing element with low priority in/along x-y-z directions" option to resolve clashes. These identified factors and options will be utilized to collect specific clash data to train and test effective and explainable machine-learning algorithms toward automating clash resolution. [ABSTRACT FROM AUTHOR]

Even with the utilization of software tools like Navisworks to automate clash detection, clash resolution in construction projects remains a slow and manual process. The reason is the meticulous nature of the process where coordinators need to ensure that resolving one clash does not lead to new clashes. The use of machine learning to automate clash resolution as a potential option to improve the clash resolution process has been suggested with research showing positive results to support the implementation. While the research shows high accuracy in predicting clash resolution options to support automation, the scope limits the discussion on the complex and often lengthy process of developing a machine-learning model. Based on this research gap, the authors in this paper discuss the development of a prediction model to identify clash resolution options for given clashes. The discussion is focused on individual steps involved in creating machine-learning models like data collection, data preprocessing, and machine-learning algorithm development and selection. The authors also address common challenges in the development of machine-learning models including class imbalance and availability of limited data. The authors utilize a multilabel synthetic oversampling method to generate different percentages of synthetic data to account for class imbalance and limited data sets. Using this data set, the authors trained five machine-learning algorithms and reported on their accuracy. The authors concluded that increasing the data set with 20% synthetic data, and using an artificial neural network to develop the machine-learning model to automate the resolution of clashes have generated better results with an average accuracy of around 80%. [ABSTRACT FROM AUTHOR]

Introduction Repair and maintenance personnel in the field of facilities management (FM), have a much higher rate of injury and illness than the national average. Research has shown that a major contributing factor to these high incidence rates is the disorganization and fragmentation of relevant safety information, coupled with the often time sensitive nature of FM tasks. Practical application In order to improve worker’s safety during the FM phase, a BIM-based Safety for Facilities Management (SFFM) framework is being developed to categorize, consolidate, process, and efficiently present job specific, relevant safety information to FM personnel. Method In order to properly develop the SFFM, the safety information that is applicable to FM staff must first be identified, organized, and categorized. This is executed through a number of research methods, structured within the theoretical framework of Six Sigma’s Define-Measure-Analyze-Design-Verify (DMADV). Results By systematically collecting, analyzing, and categorizing data within the Define Phase of DMADV, an iterative process with validation steps provides a rigorous and a comprehensive evaluation of the data. Conclusion This paper describes the data collection and analysis methods, known as the Define Phase, of Six Sigma’s Define-Measure-Analyze-Design-Verify (DMADV) methodology, in order to develop safety properties that are utilized within the BIM-based SFFM framework. [ABSTRACT FROM AUTHOR]

Maintenance personnel in the field of facility management (FM) are at constant risk of electrical shock, falls, crushing, cuts and bruises, and as a result, have a much higher rate of injury and illness than the national average. Case study analysis confirms that many recorded accidents could have been avoided had the victim followed appropriate hazard mitigation steps to safely execute a FM task. Currently, safety information is conveyed through training seminars, documents, and meetings. This information, although comprehensive, often remains fragmented among multiple resources. Research has shown that the more time and effort an individual must spend obtaining information, the less likely they are to retrieve the information and obey the stated warnings, directly relating to injuries and fatalities. This research attempts to mitigate these issues by describing current market trends, available technologies, and limitations. The paper presents a BIM-based framework to support safe maintenance and repair practices during the facility management phase, through safety attribute identification/classification, data processing and rule-based decision making, and a user interface. By developing a BIM-based framework for FM safety, an underutilized/under-researched usage of BIM is being explored. [ABSTRACT FROM AUTHOR]

Electrocution is among the ‘fatal four’ in US construction according to the Occupational Safety and Health Administration. Learning from failures is believed to be an effective path to success, with deaths being the most serious system failures. This paper examined the failures in electrical safety by analysing all electrical fatality investigations (N= 132) occurring between 1989 and 2010 from the Fatality Assessment and Control Evaluation programme that is completed by the National Institute of Occupational Safety and Health. Results reveal the features of the electrical fatalities in construction and disclose the most common electrical safety challenges on construction sites. This research also suggests the sociotechnical system breakdowns and the less effectiveness of current safety training programmes may significantly contribute to worker's unsafe behaviours and electrical fatality occurrences. [ABSTRACT FROM AUTHOR]

During some of the different building design stages, typical construction materials/components are often grouped together to form what is called building assemblies. One of the most important tasks in the design development stage of building design is the selection of the appropriate building assemblies to be used in the various elements of the building, e.g. walls, roofs, floors and so on. This decision will have a significant impact on the performance of the building with respect to the various design criteria. Although this decision cannot be entirely separated from other design stages, the use of decision-making techniques can render this a more rational decision. In this paper, a computer tool is developed for selecting the best combination of building assemblies for each particular design situation. The tool utilizes some of the existing decision-making models in a single comprehensive procedure. In the described procedure, the building assemblies are selected by finding a trade-off between a set of designer-specified criteria. The analytical hierarchy process (AHP) is used to determine the relative importance weights for the different criteria. In addition, various methods for determining an aggregated criteria performance for each alternative solution is described. A heuristic algorithm is used to search for the best assembly combination among the different building assemblies. A computer prototype that implements the selection procedure is developed in Visual Basic as an add-in to AutoCad. [Copyright &y& Elsevier]

Lane closures during paving operations on rural two-lane roads usually restrict the continuity of paving operations, causing delay in paving time and thus affecting the production rates. This paper presents a simulation model that was developed to assess the impact of the different variables on paving operations under lane closure conditions. The model developed is a high-fidelity computer simulation that incorporates an animation interface. The model involves traffic simulation as well as the construction process itself, and allows users to study the interaction between the two. Variables such as distance from plant, number and types of trucks, traffic volume, length of lane closure, maximum allowable work zone speed, and lane closure strategies are incorporated in the model. Users of the model can adjust these variables according to any particular project and consequently measure the effect on production rates and cost. A construction-oriented discrete event simulation language, Stroboscope, was used to develop the model and a 3D animation was developed to visually simulate the construction process for visual verification. The model was then used on a case study to evaluate paving operations. Sensitivity analyses were conducted using the simulation model to investigate the effects of the different variables on productivity and cost. [Copyright &y& Elsevier]

The planning process is critical to the successful development and execution of a construction project. Current planning practices adopted by the construction industry continue to be substantially manual. Project information is primarily exchanged via paper documents, and the visualization of the facility is marginally communicated using 2D drawings. Functions are generally planned independently of one another. Previous research efforts developed systems that are characterized as responsive decision systems, relying mainly on programmed knowledge and heuristics for decision-making; reducing or eliminating the role of the human planner. This paper presents a framework for a new planning approach that will utilize virtual reality (VR) modeling techniques coupled with object-oriented technologies to develop an integrated virtual planning tool called the Virtual Construction Environment (VCE). The proposed VCE will enable the project team to undertake inexpensive rehearsals of major construction processes and test various execution strategies in a near reality sense, prior to the actual start of construction. A proof of concept prototype is currently being developed. [Copyright &y& Elsevier]

Describes Space Constrained and Resource Constrained, a knowledge-based system designed for scheduling repetitive floors in multistory projects. Overall architecture and components of the system; Three groups of schemata structures defined; Other important applications of the system; Capabilities and limitations of the system.

Current as-built Building Information Model (BIM) deliverables generated following design and construction generally do not fulfill facility management needs. To provide total value to the facility owner, as-built models should be configured to provide needed critical operation and maintenance information, solve operational challenges, and improve safety and efficiency in various ways. In addition to having complete and accurate data, as-built BIMs should be configured to be systems-centric enabling facility owners to visualize model graphics from a systems perspective. This is critical during a maintenance emergency when the model user needs to identify components belonging to the building systems that are contributing to or impacted by the emergency and be able to make well-informed timely decisions. This paper contributes to the existing body of knowledge by defining and documenting requirements and procedures for configuring systems-centric as-built BIM models. A multi-level building systems classification is developed, and fourteen specific properties are defined. The implementation is discussed using a case study approach analyzing the mechanical and plumbing systems for a science and classroom building of a 4-year academic institution. By developing systems-centric models, facility staff can respond to emergency maintenance and analyze the impact of the event by isolating the elements of a specific system related to the emergency and display these elements explicitly. • Current as-built Building Information Model (BIM) do not fulfill facility management needs. • As-built BIM should be systems-centric to allow visualization and analysis of the building systems. • Requirements and procedures for configuring a systems-centric as-built BIM model is proposed in this paper. • A system classification as well as systems-centric properties are developed and identified in this paper. • Facility staff can respond to emergency maintenance and analyze their impact using the proposed models. [ABSTRACT FROM AUTHOR]

Effective facility management is a critical aspect of ensuring an adequate physical environment to administer care. Maintaining the environment is complicated with numerous critical systems because of occupants with compromised immune systems, and the need to maintain the systems with minimal effect on clinical operations. The complexity and importance of tasks that facility managers deal with require them to have adequate, up-to-date, and easily accessible information. This paper presents a case study that analyzes the impact of facility management on healthcare delivery. The work was completed in the preliminary stages of a research initiative for developing a lifecycle information management system to support facility management within healthcare. A case concerning mechanical systems and critical failures in a healthcare setting is analyzed to identify the types of information needed to adequately perform maintenance tasks. The information is then analyzed for origin along the lifecycle of the facility, its format, and suitable granularity. The aim of the discussed research is to support the development of a healthcare facility information management framework and product model. The product model and framework will aid in the efficient and effective management of facility and clinical information to support facility management activities in healthcare environments. [ABSTRACT FROM AUTHOR]

Abstract: Facility management within healthcare is required to ensure that complex systems are maintained and operational while causing minimum interruption to clinical activities and maintaining patient safety. Their tasks are complicated by fragmented and sometimes incomplete information. To help facility managers better manage lifecycle information pertinent to managing the facility and responding to facility related patient safety events, an object oriented product model is proposed in the context of developing a healthcare facility information management framework. The product model is developed as a result of various case analyses that were conducted using Unified Modeling Language (UML) Use Cases to examine information needs for existing healthcare facility maintenance operations. The resulting classification system and its uses to respond to patient safety events are discussed in this paper. [Copyright &y& Elsevier]