The Applications of Building Information Modelling in Facilities Management

2011 ◽  
pp. 1539-1553 ◽  
Author(s):  
Oluwole Alfred Olatunji ◽  
William David Sher
Keyword(s):  
Empirical Evidence ◽  
Information Flow ◽  
Project Teams ◽  
Integrated Analysis ◽  
Facilities Management ◽  
Building Information Modelling ◽  
Information Modelling ◽  
Management Processes ◽  
Building Information

Effective processes in facilities management are responsive to the quality of information flow across various levels and stages of design, procurement and construction processes. Considerable empirical evidence from industry reports shows how construction and facilities management processes could be jeopardized by some of the limitations of conventional design and procurement processes. To address these limitations, there are promising indications showing that the potential of Building Information Modelling (BIM) will trigger major improvements in both construction and facilities management systems. This study reviews some of the capabilities of BIM which may revolutionize conventional practices in facilities management processes. Specific platforms for this include, integrated analysis and simulation of project variables in virtual environments, effective communication between project stakeholders and project teams and multi-disciplinary collaboration. Others are interoperability, project visualization, value intelligence and other digital facilities management applications. In the study it is argued that BIM capabilities such as project visualization, simulation, auto-alert and value intelligence could stimulate major improvements in facilities management processes. Finally conclusions are drawn on the relationships between BIM and digital facilities management, including suggestions on areas of further studies.

The Applications of Building Information Modelling in Facilities Management

2010 ◽  
pp. 239-253 ◽  
Author(s):  
Oluwole Alfred Olatunji ◽  
William David Sher
Keyword(s):  
Empirical Evidence ◽  
Information Flow ◽  
Project Teams ◽  
Integrated Analysis ◽  
Facilities Management ◽  
Building Information Modelling ◽  
Information Modelling ◽  
Management Processes ◽  
Building Information

Effective processes in facilities management are responsive to the quality of information flow across various levels and stages of design, procurement and construction processes. Considerable empirical evidence from industry reports shows how construction and facilities management processes could be jeopardized by some of the limitations of conventional design and procurement processes. To address these limitations, there are promising indications showing that the potential of Building Information Modelling (BIM) will trigger major improvements in both construction and facilities management systems. This study reviews some of the capabilities of BIM which may revolutionize conventional practices in facilities management processes. Specific platforms for this include, integrated analysis and simulation of project variables in virtual environments, effective communication between project stakeholders and project teams and multi-disciplinary collaboration. Others are interoperability, project visualization, value intelligence and other digital facilities management applications. In the study it is argued that BIM capabilities such as project visualization, simulation, auto-alert and value intelligence could stimulate major improvements in facilities management processes. Finally conclusions are drawn on the relationships between BIM and digital facilities management, including suggestions on areas of further studies.

scholarly journals A Preliminary Implementation Framework of Building Information Modelling (BIM) in the Algerian AEC Industry

2020 ◽  
Vol 7 (3) ◽  
pp. 59-68
Author(s):  
Khalid Bouguerra ◽  
Lim Yaik-Wah ◽  
Kherun Nita Ali
Keyword(s):  
Construction Industry ◽  
Implementation Framework ◽  
Building Information Modelling ◽  
Information Modelling ◽  
Construction Market ◽  
Technology Process ◽  
Building Information ◽  
Upward Growth ◽  
Aec Industry

The construction industry is one of the most growing sectors worldwide, it plays a great role in boosting the economy. The construction sector in Algeria has recently witnessed an upward growth, due to the Algerian government’s vision to develop economic activity and boost the residential construction market. On the other hand, the Algerian construction market is suffering from the lack of efficiency; projects delay and less quality of projects delivery. It becomes very necessary to find a way to improve these inefficiencies by adopting new approaches and technologies. Building Information Modelling (BIM) is becoming a widespread and common approach in the design, construction and maintenance of building facilities as BIM reduces waste, improves construction quality and enhance collaboration among the construction stakeholders. Hence, it becomes necessary to start gradually introducing BIM to the Algerian construction industry in order to improve its productivity. This paper addresses BIM implementation in the Algerian AEC industry and proposes a preliminary framework towards its implementation. Through a questionnaire survey, we explored the BIM capabilities, BIM awareness and BIM maturity of the Algerian AEC players. Based on the questionnaire findings and literature review, this paper proposes an effective BIM implementation based on both levels of macro-adoption and micro-adoption. The framework developed is based on three main aspects comprise of technology, process and policy. This study is considered as the first implementation framework of Building information modelling in the Algerian AEC industry. The framework proposed will be used as a reference for the Algerian researchers and professionals.

scholarly journals The use of building information modelling by quantity surveyors in facilities management roles

2020 ◽  
Vol 27 (8) ◽  
pp. 1795-1812
Author(s):  
Melanie Stride ◽  
Carol K.H. Hon ◽  
Rui Liu ◽  
Bo Xia
Keyword(s):  
Resistance To Change ◽  
Facilities Management ◽  
Building Information Modelling ◽  
Content Type ◽  
Information Platform ◽  
Information Modelling ◽  
Building Information ◽  
Management Roles ◽  
Operation Phase ◽  
Asset Data

PurposeAdoption of building information modelling (BIM) in facilities management (FM) provides an information platform to store and exchange asset data. Quantity Surveyors, with cost management expertise, are increasingly involved in FM roles in the operation phase. However, no study has been conducted on how BIM may assist Quantity Surveyors when contracted in FM roles. This study aims to identify the potential benefits and challenges of using BIM by Quantity Surveyors in FM roles.Design/methodology/approachInterviews were conducted with eight professionals from an international built and natural asset design and management company and its FM business partner in Australia.FindingsLack of complete and accurate data was the main issue faced by Quantity Surveyors in FM. The benefits of BIM in FM were digitizing and storing asset information and developing a cost database that would be useful for Quantity Surveyors, whereas challenges included keeping model data up to date, cost, industry resistance to change and contractors' lack of model use.Originality/valueThis study contributes to revealing the niche adoption of BIM by Quantity Surveyors in FM and identifying the issues faced by Quantity Surveyors in FM roles using BIM. It contributes to the knowledge of BIM adoption in post-construction. Findings will be useful to develop strategies for adopting BIM in FM and supporting Quantity Surveyors' roles in FM.

scholarly journals Building information modelling and building sustainability assessment: a review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Annelise Nairne Schamne ◽  
André Nagalli ◽  
Alfredo Augusto Vieira Soeiro
Keyword(s):  
Sustainability Assessment ◽  
Complete Analysis ◽  
Integrated Analysis ◽  
Rating Systems ◽  
Building Information Modelling ◽  
Content Type ◽  
Information Modelling ◽  
Sustainability Analysis ◽  
Building Information ◽  
Number Of Publications

PurposeThe construction sector is increasingly engaged to explore the potential application of building information modelling (BIM) for the sustainability of the buildings. BIM can be applied conjugated to certification methods to evaluate the sustainability of the buildings, and it is known as building sustainability assessment (BSA). This article aims to explore applications of BIM in the sustainability analysis of buildings, including five types of BSA.Design/methodology/approachA literature review from 2009 to 2020 considering a combination of search terms related to BIM and BSA complemented the analysis. The bibliometric analysis indicates an increase in the number of publications on this topic of study in the last five years. A peak occurred in 2015 and 2020, with 51 and 66 publications, respectively.FindingsThe results showed that BIM contributes to achieving part of the sustainability requirements from BSA, especially quantitative requirements that are related to material and resources. However, a complete analysis between BIM and BSA is still a challenge since part of BSA's have a lack information in their requirements and BIM softwares present interoperability problems that difficult an integrated analysis to extract information directly from the software to attend BSA's requirements.Originality/valueThe results contribute to analysing the evolution of studies about BIM and to understand the limitation in the applicability with sustainability rating systems. Future directions of research indicate the necessity to improve the use of BIM in the sustainability analysis of the buildings, but with a good perspective regarding the application of BIM in material and resources requirements, and waste management in construction sites.

Building Information Modelling Maturity Matrix

2010 ◽  
pp. 65-103 ◽  
Author(s):  
Bilal Succar
Keyword(s):  
Project Teams ◽  
Building Information Modelling ◽  
Engineering Construction ◽  
Information Modelling ◽  
Capability Maturity ◽  
Performance Figure ◽  
Building Information ◽  
Definition Of ◽  
Active Implementation ◽  
Different Levels

Building Information Modelling (BIM) is an expanding collection of concepts and tools which have been attributed with transformative capabilities within the Architecture, Engineering, Construction and Operations (AECO) industry. BIM discussions have grown to accommodate increasing software capabilities, infinitely varied deliverables, and competing standards emanating from an abundance of overlapping definitions attempting to delineate the BIM term. This chapter will steer away from providing its own definition of BIM yet concurs with those identifying it as a catalyst for change (Bernstein, 2005) poised to reduce industry’s fragmentation (CWIC, 2004), improve its efficiency (Hampson & Brandon, 2004) and lower its high costs of inadequate interoperability (NIST, 2004). In essence, BIM represents an array of possibilities and challenges which need to be understood and met respectively through a measurable and repeatable approach. This chapter briefly explores the multi-dimensional nature of the BIM domain and then introduces a knowledge tool to assist individuals, organisations and project teams to assess their BIM capability, maturity and improve their performance (Figure 1). The first section introduces BIM Fields and Stages which lay the foundations for measuring capability and maturity. Section 2 introduces BIM Competencies which can be used as active implementation steps or as performance assessment areas. Section 3 introduces an Organisational Hierarchy/Scale suitable for tailoring capability and maturity assessments according to markets, industries, disciplines and organisational sizes. Section 4 explores the concepts behind ‘capability maturity models’ and then adopts a five-level BIM-specific Maturity Index (BIMMI). Section 5 introduces the BIM Maturity Matrix (BIm³), a performance measurement and improvement tool which identifies the correlation between BIM Stages, Competency Sets, Maturity Levels and Organisational Scales. Finally, Section 6 introduces a Competency Granularity Filter which enables the tailoring of BIM tools, guides and reports according to four different levels of assessment granularity.

scholarly journals A Review and Scientometric Analysis of Global Building Information Modelling (BIM) Research in the Architecture, Engineering and Construction (AEC) Industry

2019 ◽  
Author(s):  
Ziwen Liu ◽  
Yujie Lu ◽  
Lu Chang Peh
Keyword(s):  
Green Building ◽  
Recent Decade ◽  
Research Field ◽  
Future Research ◽  
Scientometric Analysis ◽  
Facilities Management ◽  
Building Information Modelling ◽  
Information Modelling ◽  
Building Information ◽  
Aec Industry

In the recent decade, Building Information Modelling (BIM) has widely been adopted in the Architecture, Engineering and Construction (AEC) industry and completely upended the way we build. While BIM continues gain momentum in the industry, it has also attracted increasing attentions from researchers. However, most of the current study focuses on reviewing BIM for management, BIM for green building, BIM for infrastructure and BIM for Facilities Management (FM). There are few studies about Global BIM review and to discuss their complex inter-connections. In this study, we adopted a scientometric analysis method to review global BIM research from 2004-2019. A total of 1455 scholarly bibliographic records obtained from Web of Science Core Collection databased were established for the analysis. This study has identified the top productive and influential researchers, research institutes, regions/countries, subject categories and journals in the BIM field. In addition, 11 clusters of Global BIM research were also identified including construction project, green BIM, construction safety planning, automated IFC-based workflow and so on. Authors distinguished 11 clusters of global BIM research into 3 stages, namely formulating stage, accelerating stage and transforming stage. Furthermore, authors reviewed the BIM policy of Singapore and observed there is a co-production relationship between evolution of BIM policy and global BIM research. These findings provide valuable information for researchers, practitioners and policy makers by visualizing the current progress in the research field of BIM and highlighting future research needs.

Barriers to Achieving the Benefits of BIM

2019 ◽  
pp. 814-832
Author(s):  
Heikki Halttula ◽  
Harri Haapasalo ◽  
Maila Herva
Keyword(s):  
Focus Group ◽  
Literature Review ◽  
Information Flow ◽  
Cost Savings ◽  
Focus Group Interviews ◽  
Building Information Modelling ◽  
Information Modelling ◽  
Building Information ◽  
Practical Guidelines ◽  
Group Interviews

The purpose of this paper is to study the benefits of building information modelling (BIM) and determine the barriers to achieving these benefits. The use of BIM is not yet at a level where known benefits can be realised. This study consists of a literature review of the benefits of BIM and an empirical review, where focus group interviews were used to discover barriers. The major benefits of BIM include cost savings, better information flow, shorter project timelines and better quality. The greatest barrier is the lack of practical guidelines for BIM implementation in projects. Successful BIM implementation requires technology, people and processes to be in proper shape. Earlier studies identify the theoretical requirements of BIM implementation, but practical solutions are still not at an adequate level.

scholarly journals Evaluation of Classical Operators and Fuzzy Logic Algorithms for Edge Detection of Panels at Exterior Cladding of Buildings

Buildings ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 40 ◽  
Author(s):  
Chang Liu ◽  
Sara Shirowzhan ◽  
Samad M. E. Sepasgozar ◽  
Ali Kaboli
Keyword(s):  
Fuzzy Logic ◽  
Edge Detection ◽  
Similarity Index ◽  
Computational Error ◽  
Construction Sites ◽  
Building Information Modelling ◽  
Information Modelling ◽  
Building Information ◽  
Accuracy Indices

The automated process of construction defect detection using non-contact methods provides vital information for quality control and updating building information modelling. The external cladding in modular construction should be regularly controlled in terms of the quality of panels and proper installation because its appearance is very important for clients. However, there are limited computational methods for examining the installation issues of external cladding remotely in an automated manner. These issues could be the incorrect sitting of a panel, unequal joints in an elevation, scratches or cracks on the face of a panel or dimensions of different elements of external cladding. This paper aims to present seven algorithms to detect panel edges and statistically compare their performance through application on two scenarios of buildings in construction sites. Two different scenarios are selected, where the building façades are available to the public, and a sample of 100 images is taken using a  state-of-the-art 3D camera for edge detection analysis. The experimentation results are validated by using a series of computational error and accuracy analyses and statistical methods including Mean Square Error, Peak Signal to Noise Ratio and Structural Similarity Index. The performance of an image processing algorithm depends on the quality of images and the algorithm utilised. The results show better performance of the fuzzy logic algorithm because it detects clear edges for installed panels. The applications of classical operators including Sobel, Canny, LoG, Prewitt and Roberts algorithms give similar results and show similarities in terms of the average of errors and accuracy. In addition, the results show that the minor difference of the average of the error and accuracy indices for Sobel, Canny, LoG, Prewitt and Roberts methods between both scenarios are not statistically significant, while the difference in the average of the error and accuracy indices for RGB-Sobel and Fuzzy methods between both scenarios are statistically significant. The accuracy of the algorithms can be improved by removing unwanted items such as vegetation and clouds in the sky. The evaluated algorithms assist practitioners to analyse their images collected day to day from construction sites, and to update building information modelling and the project digital drawings. Future work may need to focus on the combination of the evaluated algorithms using new data sets including colour edge detection for automatic defect identification using RGB and 360-degree images.

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