Building Information Modeling Information Research Articles

Disruptive method for managing BIM design and construction using Kanban

Abstract Companies in the construction sector need effective information management. In particular, the transmission of information within a company is key to improving its management and competitiveness. Currently, many companies in the construction sector are making a great effort to implement the building information modelling (BIM) methodology. Such implementation requires collaborative work through the Cloud between the different agents in the construction process of any project. In fact, information management in BIM projects is related to the creation, storage, transfer and efficient application of information within a three-dimensional (3D) virtual model of the project. The size of the project also determines the optimal management approach. The main problems resulting from poor information management may be a lack of coordination between actors, loss of information or misinterpretation of information. This work has two stated objectives. The first objective is to carry out a literature review of the applications of BIM technology and the importance of managing knowledge according to International Organisation for Standardisation (ISO)- 19650. The second objective is to propose a disruptive method based on the Kanban tool to properly manage BIM information in the design and construction phases. This paper has practical implications for the improvement of BIM application for project managers.

IMPLEMENTATION OF BUILDING INFORMATION MODELING (BIM) PRINCIPLES AND INFORMATION TECHNOLOGIES FOR STRUCTURAL ANALYSIS IN THE DESIGN OF REINFORCED CONCRETE AND СOMPOSITE STEEL-REINFORCED CONCRETE FRAMED BUILDINGS

The development of Building Information Modeling (BIM) in historical context hasbeen analyzed, including CAD systems for 2D and 3D modeling, considered predecessors of modern BIM systems, parametric 3D modeling systems, the use of information technologies for structural analysis, issues of combined use of BIM systems and information technologies for structural analysis.Using the example of a 20-story frame-monolithic residential building, the sequence of creating a building information model in PC SAPPHIRE, forming a calculation model of the reinforced concrete frame in PC Lira-SAPR through direct integration of the specified software complexes is demonstrated. The issues of preparing a building information model in PC SAPPHIRE for transfer to PCLira-SAPR are discussed, as well as the issues of refining the calculation model in PC Lira-SAPR, including assigning stiffness and load characteristics, and selecting reinforcement for structural elements. Тhe sequence of creating a calculation model of a steel-reinforced concrete frame for three options of steel-reinforced concrete columns is considered: tubular concrete columns; tubular concrete columns with rigid reinforcement by cross steel strips; tubular concrete columns with rigid reinforcement by cross double T-sections.For the selected most loaded columns, mainly on the first floor, operating under the conditions of central or off-center compression, the sequence of forming refined calculation models is demonstratedby modeling these columns and areas of their connection to the floor slabs with 3D finite elements.Equivalent stress iso-surfaces are provided, as well as separate iso-surfaces of equivalent stresses of the steel shell and separately the concrete core of the columns

Comprehensive Calculation Method of Semantic Similarity of Transport Infrastructure Ontology Concept Based on SHO-BP Algorithm

Semantic information interaction plays an important role in transportation infrastructure modeling and management. To ensure semantic consistency during information exchange and data integration, ontology technology is commonly employed to measure the semantic relevance between concepts. Ontology semantic similarity accurately expresses relationships among various concepts in the domain, and when combined with Building Information Modeling (BIM) technology, it improves the efficiency of information transmission and management in construction. However, the complex structure, diverse components, and strong attribute diversity of transportation infrastructure pose challenges for analysis and computation, leading to limited precision in existing ontology semantic similarity methods. Aimed at these issues, this paper proposes a transport infrastructure ontology concept semantic similarity measurement model based on the Back Propagation (BP) neural network algorithm improved by the Spotted Hyena Optimizer (SHO-BP). Firstly, a semantic network for transportation infrastructure is established, and an ontology-based semantic similarity calculation model is constructed with three approaches, including Edge-Counting method, Feature-based method, and Information-Content method. Then, the SHO-BP algorithm is employed to comprehensively weight the three similarity measure approaches above. Finally, using bridge BIM models as examples, the semantic similarity of transportation infrastructure concepts involved in the BIM models are computed based on the weighted model derived from the aforementioned processes. The experiments demonstrate that the SHO-BP algorithm achieves a higher Pearson correlation coefficient than other algorithms for the comprehensive semantic similarity results in the field of transportation infrastructure. This improvement effectively enhances the accuracy of ontology semantic similarity calculation, and it is conducive to the sharing and integration of BIM information in different systems.

BIM for FM: understanding information quality issues in terms of compliance with owner’s Building Information Modeling Requirements

The promise of Building Information Modeling (BIM) for Facilities Management (FM) is based upon building information models as reliable sources of information for decisions during a facility’s life cycle, from the planning to end of life. However, the premise of BIM as an enabler for the delivery of reliable information for FM has numerous challenges. Previous studies have shown that the quality of information provided through current design practices with BIM is inadequate for FM. These information quality (IQ) issues are mostly related to incomplete, inaccurate, inconsistent, and unintelligible facility information that ultimately reduce the usefulness of BIM-based information for FM purposes. In order to support BIM-enabled delivery of useful asset information for FM, certain IQ criteria must be met. Based on three ethnographic case studies, including the analysis of more than two thousand documented BIM for FM-related compliance issues, this research identifies ten key IQ criteria in design BIMs that must be considered to reliably support BIM use for FM, correlates these IQ criteria with key IQ dimensions identified in the literature to reflect their frequency of occurrence, and identifies sources of IQ issues in BIM for FM within design practice. A mixed-method approach for data collection from the case studies is adopted, including document analysis, semi-structured interviews, meeting observation, and a survey. The data collected are analyzed through an iterative coding process, in which the themes emerged are refined and tested as part of a grounded theory approach. This study contributes to the development of the theoretical concept of IQ in BIM for FM that is grounded in data from actual projects with stringent BIM requirements for FM and thorough compliance processes. As a practical contribution, the findings in this study should enable owners and designers to develop a more optimized asset information delivery process, increasing the value of the information in design BIMs for operations with minimal impact on current modeling practices.

Blockchain-Based Double-Layer Byzantine Fault Tolerance for Scalability Enhancement for Building Information Modeling Information Exchange

A Practical Byzantine Fault Tolerance (PBFT) is a consensus algorithm deployed in a consortium blockchain that connects a group of related participants. This type of blockchain suits the implementation of the Building Information Modeling (BIM) information exchange with few participants. However, when much more participants are involved in the BIM information exchange, the PBFT algorithm, which inherently requires intensive communications among participating nodes, has limitations in terms of scalability and performance. The proposed solution for a multi-layer BFT hypothesizes that multi-layer BFT reduces communication complexity. However, having more layers will introduce more latency. Therefore, in this paper, Double-Layer Byzantine Fault Tolerance (DLBFT) is proposed to improve the blockchain scalability and performance of BIM information exchange. This study shows a double-layer network structure of nodes that can be built with each node on the first layer, which connects and forms a group with several nodes on the second layer. This network runs the Byzantine Fault Tolerance algorithm to reach a consensus. Instead of having one node send messages to all the nodes in the peer-to-peer network, one node only sends messages to a limited number of nodes on Layer 1 and up to three nodes in each corresponding group in Layer 2 in a hierarchical network. The DLBFT algorithm has been shown to reduce the required number of messages exchanged among nodes by 84% and the time to reach a consensus by 70%, thus improving blockchain scalability. Further research is required if more than one party is involved in multi-BIM projects.

Effects of Applying BIM on Facility Management for Existing Buildings

Building Information Modelling (BIM) is increasingly being used construction projects, and it demonstrates its ability to improve the construction industry's performance, However, its application in facility management still moderate and has not yet reached the potential and expected full use. The most common problem facing facility managers is the ability to access and manage the information. Information is the key to operate existing buildings and most importantly is the ability to collect, analyze, and handle it in an appropriate manner to be used for the facility management phase and the entire building life. However, there is insufficient understanding of the correct standards, processes and policies to be followed in the submission and management of such data, a significant lack of professionals and lack of knowledge of their software. This study aims to explore the value of BIM and the challenges affecting its application in FM, as well as address the information required for effective facilities management in existing buildings and the challenges to maintain a continuous update of BIM information in FM. The research methodology is based on analytical method: Using a questionnaire to a sample of staff and engineers in facilities management to detect the effects of applying BIM to facility management. The research demonstrated the importance of creating a BIM model for existing buildings and its effects to improve operations and maintenance, the need to increase BIM practices in engineering organizations. and indicated the most important benefits of the BIM for facility management application as: increase the efficiency of operation and maintenance staff's access to data, improve future operation design and preventive maintenance, facilitate decision-making throughout the operation and maintenance phase, and finally reduce costs and time while increase the quality of procedures.

Production and construction quality management system of prefabricated buildings based on BIM technology

In order to improve the efficiency of quality management of prefabricated building production and construction, a quality management model and system design method of prefabricated building production and construction based on building information modelling (BIM) technology are proposed. The BIM big data of prefabricated building production and construction quality management is collected by using internet of things technology to build BIM information database. The method of fuzzy parameter fusion and performance tracking recognition is used to realise BIM data scheduling and feature distributed fusion. Through rough set feature matching and autocorrelation feature fusion, the model information is optimised and analysed by big data, and the optimal control and convergence judgment of prefabricated component production and construction quality management are realised. The simulation results show that this method has high degree of information fusion and strong resource scheduling ability in the production and construction quality management of prefabricated components.

Justifying the Effective Use of Building Information Modelling (BIM) with Business Intelligence

Although building information modelling (BIM) is a widely acknowledged information and communication technology (ICT) in the architecture, engineering, construction, and operation (AECO) industry, its implementation is hindered by the hybrid practice of BIM and non-BIM information processing, and sometimes, it fails to add value to the AECO business. It is crucial to define, on a scientific base, how to ensure the effective use of BIM regarding the various conditions in which to apply BIM in AECO practices. Although several studies have investigated similar topics, very few have focused on the adoption of distinct BIM applications over the conventional practice from the perspective of business intelligence (BI) as a theoretical framework to justify the effective value of BIM use in the AECO. This study proposes a framework relying on BI principles to justify effective BIM use and explicates the contextual factors in AECO practices. The data were acquired from a three-round Delphi survey. The framework suggests that effective BIM use in AECO practices should follow the two principles of BI: achieving technical effectiveness and realizing business value. The pursuit of technical effectiveness should consider business objectives, business issues, business sustainability and regulatory eligibility, and the realization of business value involves willingness to adopt BIM, human-computer interoperability, visualization-based data quality and sources, data processing and system integration, and application maturity. This study provides a new perspective by which to address the issue of the technological iteration in the current hybrid BIM and non-BIM practice and could help to improve BIM implementation in the AECO industry.

BIM guidance to optimise the operational phase: defining information requirements based on ISO 19650

PurposeThis paper aims to describe the development of guidance to help clients and operational teams to clearly define information requirements for projects using building information modelling (BIM). ISO 19650 standards highlight this as a critical first step to ensure adequate information is available to optimise built assets over their whole life cycle.Design/methodology/approachA document analysis of existing BIM guidance supported by literature was undertaken to answer the research questions: “What guidance already exists specific to clients? and Would additional guidance help clients to better fulfil their role as the ‘appointing party’ in line with ISO 19650?”FindingsA research gap was established highlighting a lack of guidance specifically aimed to help clients formulate information requirements as the appointing party. This research makes recommendations for an approach to define the requirements and support successful outcomes for BIM projects.Practical implicationsThis paper provides a standardised approach and a starting point for an appointing party to gather and structure information requirements in line with ISO 19650.Originality/valueThis paper considers BIM information requirements specifically from an operations perspective with a focus on the client and facility management team.

BIM-based indoor mobile robot initialization for construction automation using object detection

In recent years, there has been increasing interest in robotic solutions to revolutionize the conventional construction industry. Despite various advances in developing mobile robotic solutions for construction automation. One key bottleneck towards a fully automated robotic solution in construction is the initialization of the mobile robot. Currently, most of the commercialized mobile construction robots are manually initialized before autonomous navigation can be performed at the construction sites for automated tasks. Even if the robot is initialized, the location information can be lost while navigating and re-initialization is required to resume the navigation. Any wrong initialization can cause failure in robot pose tracking and thus prevent the robot from performing the planned tasks. However, in indoor construction sites, GPS is not accessible, and indoor infrastructures, such as beacon devices are not available for robot initialization. In addition, construction environments are dynamic with significant change in scenes and structures for different construction blocks and floors, making pre-scanning of the environments and map matching difficult and time-consuming. An infrastructure-free and environment-independent robot initialization method is therefore required. In this paper, we propose an integrated Building Information Model (BIM)-based indoor robot initialization system using an object detector to automatically initialize the mobile robot when it is deployed at an unknown location. Convolutional neural network (CNN)-based object detection technique is used to detect and locate the visual features, which are widely distributed building components at construction sites. A feature matching algorithm is developed to correlate the acquired online information of detected features with geometric and semantic information retrieved from BIM. The robot location in the BIM coordinate frame is then estimated based on the feature association. Moreover, the proposed system aggregates the BIM information and the sensory information to supervise the online robot decision making, making the entire system fully automatic. The proposed system is validated through experiments in various environments including a university building and ongoing construction sites.

Defining a Digital Strategy in a BIM Environment to Manage Existing Reinforced Concrete Bridges in the Context of Italian Regulation

Regulatory activity concerning the management of existing bridges has recently been affected by updates, for instance, in Italy, which calls for a speedy and pragmatic approach based on new technologies such as building information modeling (BIM), when dealing with the survey and risk classification as well as the evaluation and monitoring of structural safety. This paper focuses on the development and integration of a digital solution, based principally on the specific framework developed by the authors, which supports BIM modeling and information management activities, in the structural setting under investigation, through the use of several technologies and tools, namely BIM-authoring, CDE platform and visual programming, in addition to programming in Python. Starting from the organization of a specific BIM object library and the initial data, inserted by means of a custom-made input environment, it was possible to reproduce digital models of bridges in accordance with specific information requirements following the new Level of Information Need setting. The applicability of the proposal is tested on two judiciously chosen real-life cases with different characteristics. Through this implementation, a series of advantages emerge, including expediting traditional procedures for BIM modeling, accessibility and traceability of information—which are constantly updated to support the monitoring of structural safety over time—and the decision-making process related to the bridge management context.

METODE IDENTIFIKASI KERUSAKAN ELEMEN FISIK BANGUNAN HERITAGE DENGAN BUILDING INFORMATION MODELING (BIM) STUDI KASUS ISTANA ALWATZIKHOEBILLAH SAMBAS

Heritage buildings as architectural heritage assets that describe the identity of a region and the architecture of the past are important to be conserved and maintained. One of the cultural heritage buildings in Indonesia is Alwatzikhoebillah Sambas Palace. This building was built with wood construction. The condition of wood with age will experience changes in characteristics due to its interaction with various factors, especially biological and non-biological factors. Changes in any form cannot be underestimated, so documentation of cultural heritage buildings is needed. One way of documenting cultural heritage buildings is Building Information Modeling (BIM). BIM documentation can record various building information that is inputted in it. This research aim was to mapping and assessing the damage to the physical elements of wood on one of the accompanying buildings on the north side of the Alwatzikhoebillah Palace using BIM. BIM information contains the color code, mapping code, and the extent of the damage that occurs in the 2D view. The variables of this study were limited to biological damage caused by fungi and moss, also non-biological factors due to mechanical, weather, and chemical factors. The results of this research is the wall elements are dominantly damaged caused by wood staining fungus or mechanical erosion and weather changes of 1,64% with the effect of gray stains left on the elements.

COMPARISON OF THE EFFECTIVENESS OF BUILDING INFORMATION MODELING BASED COST ESTIMATION AGAINST THE CONTRACTOR'S COST BUDGET PLAN IN DEVELOPMENT PROJECT OF BANJARBARU BAUNTUNG MARKET

This study focuses on the use of Building Information Modeling (BIM) which begins with creating a 3D digital model (virtual building) which serves as a means for planning, designing, implementing development, and maintaining the building and its infrastructure for all parties involved in the project. Unlike other studies that use concrete structures, this study refers to the Bauntung Banjarbaru Market building with a steel structure. BIM software program is specific and correct. Specific is within the use of BIM information is taken and adapted to real conditions within the area. Correct is a constructible model, that is, the model that is created is the same as the model that was constructed. Besides, when there is a change in the model, the resulting cost estimate can change automatically.Modeling of building structures includes modeling of reinforced concrete structures and steel structures. The modeling is done using a software called Tekla Structures with a South-East Asia environment that refers to the plan drawing. After the modeling is complete, the work unit price is inputted into the software. The output of this modeling is direct cost estimation for structural work. For manual cost estimation using cost budget plan that has been obtained from the contractor in the form of a Microsoft Excel file.From the results of the analysis of the two cost estimates, the resulting comparison of the cost difference is quite scanty. The difference between manual cost estimation and BIM based cost estimation is 0.26%. So, it can be concluded that the use of BIM based cost estimation can be used because it produces cost estimates that are faster than using manual calculations made by contractors.The use of BIM can reduce costs and inaccuracies in the calculation of estimates in projects because it can be done more thoroughly. Keywords: BIM-based cost estimation, Tekla Structures, building structures

INDOOR MAPPING WITH AN OMNIDIRECTIONAL CAMERA SYSTEM: PERFORMANCE ANALYSIS

Abstract. The use of BIM (Building Information Modeling), a component of the Digital Twin concept, is on the rise, and the need for indoor data is rapidly growing. BIM information is not only used for management purposes, but it is essential to support navigation indoors. Observing building interiors by optical sensors, such as cameras and laser scanners, has challenges as the image scale changes over a broad range in rooms and floors, and then complete coverage is required, requiring images taken from several locations with various camera orientations. Using 360° imaging sensors partially addresses the need for efficient wide FOV observations. In this study, we investigate the feasibility of using a 6-sensor omnidirectional/fisheye camera system and report about its performance.

NLP-Based Query-Answering System for Information Extraction from Building Information Models

The construction industry is information-intensive, and building information modeling (BIM) has been proposed as an information source for supporting decision making by construction project team members in the architecture, engineering, construction, and operation (AECO) industry. Because building information models contain more building data, further use of the aggregated building information to support construction and operation activities has become important. In Industry 4.0, similar-to-real-life virtual assistants, e.g., Apple’s Siri and Google Assistant, are becoming ever more popular. This research developed a query-answering (QA) system for BIM information extraction (IE) by using natural language processing (NLP) methods to build a virtual assistant for construction project team members. The architecture of the developed QA system for BIM IE consists of three major modules: natural language understanding, IE, and natural language generation. A Python-based prototype application was developed based on the architecture of the QA system for BIM IE to evaluate functionalities of the developed QA system using several BIM/industry foundation classes (IFC) models. Seven building information models and 127 test queries were utilized to evaluate the accuracy of the developed QA system for BIM IE. The experimental results indicated that the developed QA system for BIM IE achieved an 81.9 accuracy score. The developed NLP-based QA system for BIM is valid to provide relatively accurate answers based on natural language queries. The contributions of this research facilitate the development of virtual assistants in the AECO industry, and the architecture of the developed QA system can be extended to queries in other areas.

BIM Information Integration Based VR Modeling in Digital Twins in Industry 5.0

This study aims to improve the efficiency of construction efficiency to ensure the infrastructure needs of urban development. Targeting at realizing the intelligent manufacturing of buildings, the digital twins are applied to all stages of building construction, and the three-dimensional (3D) modeling is implemented. A digital twins framework in the construction field is constructed based on the building information modeling (BIM). From physical construction site entity modeling (PCSE modeling) and digital twins virtual body modeling (DTVB modeling) to virtual and real interaction modeling (VRI modeling), the digital twins process is fully applied to the various stages of building construction. The performance of the method proposed is further verified through the analysis of specific data. It is found that the model proposed shows better performance on the same platform and node compared with other models, and it shows the best scalability in the iterative calculation test on the Flink platform through efficient memory management and incremental iteration mechanism. In addition, the model has a delay of less than 100 milliseconds: in the Sleep scenario, the system delay of the latest model is about 5 times that of on the Flink, and the system interruption probability will firstly decrease and then increase when the time division factor (TDF) is increased. This study provides important reference value for the intelligent development of the construction industry and the high-quality development of buildings.

BIM Education in Higher Learning Institutions: A Scientometric Review and the Malaysia Perspective

Over the last decade, digital applications and Building Information Modelling (BIM) have been introduced in the construction industry to realize a smart construction ecosystem. However, the construction industry has not completely accepted BIM as a standard, and the concept of using BIM applications in universities has not been thoroughly researched. This paper addresses the first scientometric study of BIM education in universities, identifying the state of BIM education practices, skillsets, and the level of BIM education in universities. The paper used scientometric analysis and the VOSviewer mapping technique to assess the most impactful publication sources with the most important impact on BIM education by searching “BIM Education” and using 250 bibliographic data extracted from the Scopus database from 2011-2020 to identify the existing research gaps and research direction. Second, a structured questionnaire was distributed to 343 Year 2 and Year 3 students from two public and two private Malaysian universities that use BIM in their learning. Descriptive data analysis using cross-tabulation in SPSS and relative importance index (RII) were used to analyze the data. The paper revealed two stages of BIM education research; and identified research gaps in the fields of BIM education, architectural education, e-learning, curriculum and information management. The paper also revealed Revit, Cost X and the Glodon Cubicost software as the most used applications, while the common skillsets are design authoring, modelling, and cost estimation. However, both public and private university students mainly design 3D models at BIM Stage 1. The study recommends that institutions and other stakeholders provide continuous BIM training, purchase BIM software, and integrate BIM into the curriculum of Built Environment higher learning institutions for the next generation to be the generation that uses virtual collaborative platforms

Engineering project management based on multiple regression equation and building information modelling technology

Abstract To realise the optimisation of Building Information Modelling (BIM) technical engineering project management, the paper conducts data investigation and analysis of the technical problem which deals with a specific power grid tunnel construction. This article uses BIM to sample considerable data information for the construction and management of power grid tunnels. According to the geological factors of rock strength in construction, the fuzzy information fusion method is used to carry out the feature fusion and adaptive scheduling of management information. We will extract the characteristics of each surrounding rock category's geological BIM information association rules and use the multiple regression analysis methods to carry out the BIM information fusion and adaptive scheduling of the tunnel construction project management. The study results confirm the conclusion that the predicted scores are in good agreement with the geological scores on site.

Literature Review on Digitalization in Facilities Management and Facilities Management Performance Measurement: Contribution of Industry 4.0 in the Global Era

In this study, our aim is to present a comprehensive systematic review on digitalization (DT) in facility management (FM) and FM performance management (PM). Past research on these themes indicated that either research articles on DT in FM or research studies on FM PM are separately dealt with. However, in contrast, in our literature review, we try to present a holistic literature review by integrating both research streams on DT applications for FM and FM PM. A total 130 academic journal articles published on these subjects, between 1990 and 2021, from Web of Science and Google Scholars, were reviewed in this article. Moreover, this article identified a number of possibilities for future research on DT and FM PM, including the interoperability enhancement of building information modeling (BIM) methodology, the test and implementation of BIM concept for smart transportation infrastructure, usage of the integration of 3D analysis algorithms, the perfect cross integration of BIM and geographic information system (GIS) and systematic research efforts with new methodologies and theoretical constructs. We hope that this article will help researchers determine the areas where further research must be conducted and what kind of future directions would be valuable for DT and PM in FM.

Robot-Assisted Object Detection for Construction Automation: Data and Information-Driven Approach

In construction automation, robotic solution is becoming an emerging technology with the advent of artificial intelligence and advancement in mechatronic systems. In construction buildings, regular inspections are carried out to ensure project completion as per approved plans and quality standards. Currently, expert human inspectors are deployed onsite to perform inspection tasks with the naked eye and conventional tools. This process is time-consuming, labor-intensive, dangerous, and repetitive and may yield subjective results. In this article, we propose a robotic system equipped with perception sensors and intelligent algorithms to help construction supervisors remotely identify the construction materials, detect component installations and defects, and generate report of their status and location information. The building information model (BIM) is used for mobile robot navigation and to retrieve building component’s location information. Unlike the current deep learning-based object detection, which depends heavily on training data, this article proposes a data and information-driven approach, which incorporates offline training data, sensor data, and BIM information to achieve BIM-based object coverage navigation, BIM-based false detection filtering, and a fine maneuver technique to improve on object detections during real-time automated task execution by robots. This allows the user to select building components to be inspected, and the mobile robot navigates autonomously to the target components using the BIM-generated navigation map. An object detector then detects the building components and materials and generates an inspection report. The proposed system is verified through laboratory and onsite experiments.