Development of a benchmarking framework for pharmaceutical capital projects

Benchmarking is a proven technique for improving project performance and, as such, is a critical component of any mature project delivery system. Competitive benchmarking requires industry‐specific metrics in absolute terms since processes vary by industry, and any metrics used within a single industry must be attuned to its particular processes. A framework is developed for evaluating pharmaceutical capital facility projects using metrics specific to the characteristics of these unique projects. Establishment of the framework made possible the development of a set of industry‐specific metrics and a flexible data collection and reporting system for measuring project performance. Preliminary findings from an initial sample of 40 pharmaceutical projects confirm that meaningful industry‐specific metrics can be produced for pharmaceutical capital facilities benchmarking. Developing such a framework enables the industry to measure project performance more accurately, get meaningful project performance comparisons, and ultimately establish credible norms for project performance.     

A Quantitative Study of the Relationship between Project Performance and BIM Use on Commercial Construction Projects in the USA

This article reports the findings of a quantitative study on the relationship between various project performance outcomes and the use of Building Information Modeling (BIM), within the commercial construction industry. The literature review identified inconsistent results among prior qualitative and quantitative work concerning the relationships of key project performance measures and BIM use. Data on 13 variables from 93 completed construction projects were collected and examined through a causal comparative research design. Projects that used BIM (in design or construction) were not found to experience significant performance outcomes when controlling for the contribution of other independent variables and covariates at the 95% confidence level (CL). At the lower 90% CL, however, projects using BIM in construction experienced significantly higher levels of schedule growth than projects that did not use BIM in construction. Recommendations are made for training of construction management staff as a step to avoid unwanted schedule growth associated with BIM use during construction. This study is one of a very small group of rigorous quantitative analyses of BIM project performance outcomes conducted to date; additionally, it is the only study that has analyzed BIM in a multivariate context that controlled for the contribution of other project variables not directly related to BIM use.     

The project benefits of Building Information Modelling (BIM)

Theoretical developments in Building Information Modelling (BIM) suggest that not only is it useful for geometric modelling of a building's performance but also that it can assist in the management of construction projects. The purpose of this paper is to explore the extent to which the use of BIM has resulted in reported benefits on a cross-section of construction projects. This exploration is done by collecting secondary data from 35 construction projects that utilised BIM. A set of project success criteria were generated and content analysis was used to establish the extent to which each individual project met a criterion. The most frequently reported benefit related to the cost reduction and control through the project life cycle. Significant time savings were also reported. Negative benefits were mainly focused on the use of BIM software. Cost/benefit analysis, awareness raising and education and training are important activities to address the challenges of BIM usage.     

Impact of organization size and project type on BIM adoption in the Chinese construction market

Building Information Modelling (BIM) is perceived as an effective tool for improving the delivery and coordination of construction projects. The Chinese construction sector has demonstrated significant interest in implementing the 3-dimensional modelling-based process. BIM adoption is influenced by several factors which can either be operational or strategic related. Factors which can have a significant impact include the size of the construction organization and the type of projects that the organization has to deliver (i.e. building vs infrastructure projects). This study aims to evaluate the effect of project type and size on BIM adoption in the Chinese market, via an adoption model which analyses factors impacting the adoption decision. The study examines 200 samples collected from the Chinese construction industry, split equally between infrastructure and building construction data groups, as well as SMEs and large organizations. The collected data are first analyzed by principal component analysis and then through a Structural Equation Modelling-based multiple group analysis. Results demonstrate that essential factors such as operational risks are considered by small organization, whereas large organizations focus on implementation challenges. Implementation benefits and challenges are significant on the adoption decision in infrastructure organizations, but not in building organizations. In addition, the study reveals that “technical support” is an important factor when it comes to BIM adoption among all types of organizations, regardless of the organization’s size and project type delivered.     

The advantages of information management through building information modelling

As building information modelling (BIM) is positioned by governments and construction professionals as a solution to the problems in the construction industry, research is needed into the benefits BIM actually confers. The focus here is on the effectiveness of BIM as a medium for communicating information within a construction team. A case study of an offsite precast concrete fabrication facility was conducted. At the time of the study, the facility was supplying precast units for four public sector projects, and using four information management systems: e-mail, a construction project extranet tool, an Enterprise Resource Planning system and a new BIM-based system. The flow of information through the four media was measured and visualized as the projects progressed. This quantitative measurement of information flow was combined with qualitative data from interviews with facility staff. It was found that the introduction of the BIM-based system diverted information flow through the building model and away from the extranet system. The use of e-mail was largely unaffected. BIM allowed considerably more accurate, on-time and appropriate exchange of information. It is concluded it is possible to quantify some of the benefits of BIM to information management. This research paves the way for future research into the management of more construction project information linked more closely to building models.     

BIM技术在空间网架建模与快速估价中的应用

网架结构因其空间性能良好使其在工程项目中的应用日益增多,但由于空间网架既要考虑外观造型又要分析结构受力,使得空间网架的工程量很难统计。针对上述问题,在介绍了空间网架的工程量计算和计价原则的基础上,以大连某项目的空间网架为例,阐述了如何利用BIM进行空间网架的建模和工程量统计,并利用BIM中的基础数据,使用符合本地规范要求的造价软件对空间网架的造价进行计算。从而明确了BIM技术在进行空间网架造价计算时的优势,为今后的空间网架快速估价提供便利。     

An optimisation process to motivate effective adoption of BIM for refurbishment of complex buildings in New Zealand

Despite the multidisciplinary networks involved in refurbishment of complex building projects, the lack of BIM adoption signifies lack of real BIM benefits towards acceptance of BIM within Architecture, Engineering and Construction (AEC).To this end, this study empirically examines the potential real benefits between traditional network and BIM network for a real-time refurbishment case study project, through agent-based simulation modelling. A social network analysis theory is adapted to model the project interaction networks and a BIM prototype network. An assessment of the main stakeholders for BIM perception is carried out. We offered three prototype interaction networks for comparison of real BIM benefit.An agent-based Bayesian network model is used to simulate the propagation of design error within the project networks. The result of the analysis show that BIM project diffuses error efficiently, while stakeholders recovers faster and nearly at the same time than traditional network. The optimised network shows better performance to the traditional network, when there is early involvement of subcontractors. The main contribution of this study is providing a novel approach to compare real benefits for traditional method to BIM method for refurbishment project and to provide avenue for project stakeholders to optimise their interaction through adoption of BIM.     

Integrated visualized time control system for repetitive construction projects

Construction control is an essential management function for successful delivery and achieving of construction projects’ goals. Considerable research efforts have been done regarding project control. However, literature suffers from a lack of visualizing the controlling process. With the growth of using visualization techniques in construction, Building Information Modeling (BIM) and Geographic Information System (GIS) have recently attained a widespread contribution in visualization of construction progress. BIM is a process of creating virtual models data that represents building facilities. In this research, BIM represents a platform for nD (n-Dimensional) visualization of construction progress. The advantages of this paper stems from three main contributions for construction projects control: 1) developing of a mathematical model for time control of repetitive construction projects; 2) an automated system to dynamically integrate project progress with BIM technique; and 3) a GIS-based tool to visualize the progress of distributed sites. The developed model provides abundant information to help decision makers take the appropriate corrective actions. An example application is presented to demonstrate the applicability of the developed system.     

Understanding the impact of BIM on collaboration: a Canadian case study

ABSTRACT

Facilitating collaboration amongst project stakeholders in the construction industry is one of the central tenants of building information modelling (BIM). While there is increasing evidence of the positive influence of BIM on project outcomes, ambiguity remains around BIM’s true impact on collaboration. The presented case study aims to develop insights into the impact of BIM on collaboration in the architecture, engineering and construction industry. A critical realist perspective was adopted and a systematic combining approach was employed to support data collection and analysis. Data were collected through a longitudinal case study of a large design–build project in Canada. The unit of analysis was the individual project team member. Five cognitive determinants identified from the analysis are seen to inform an individual’s framing of event patterns in the context of BIM-enabled collaboration: requirements, expectations, intentions, incentives and capabilities. From this perspective, the impact of BIM on collaboration is understood as a reshaping of an individual’s cognitive determinants, which influence a team member’s framing of event patterns enacted throughout project delivery. This shift is manifested by changing information landscapes, i.e. sources and flows of information, that are generated, shared and consumed within the project team.     

Assessing the implementation of BIM – an information systems approach

Much attention has been paid to measuring the perceived benefits of Building Information Modelling (BIM). Yet despite an increase its adoption throughout the construction industry, important links between implementation, support and benefits are yet to be explored. We examine the constitutive elements of the BIM implementation process of two case studies implementing and using BIM: the first is a large urban regeneration project, and the second is a healthcare project. A well-recognised model of system success is mobilized from the field of information systems (ISs) to reveal that irrespective of project size and type, BIM benefits are confined to technically discrete productivity and efficiency gains when there is limited focus on the organizational aspects of BIM adoption. This paper focuses on the disconnections between organizational and project level BIM implementation using the DeLone and McLean Model as an analytical framework to systematically examine the benefits of BIM to each project in relation to the implementation approach employed. This study highlights the significance of these interdependencies and argues for a more comprehensive approach to BIM benefits capture that recognises this to usefully inform implementation strategy development.     

A Natural‐Language‐Based Approach to Intelligent Data Retrieval and Representation for Cloud BIM

As the information from diverse disciplines continues to integrate during the whole life cycle of an Architecture, Engineering, and Construction (AEC) project, the BIM (Building Information Model/Modeling) becomes increasingly large. This condition will cause users difficulty in acquiring the information they truly desire on a mobile device with limited space for interaction. The situation will be even worse for personnel without extensive knowledge of Industry Foundation Classes (IFC) or for nonexperts of the BIM software. To improve the value of the big data of BIM, an approach to intelligent data retrieval and representation for cloud BIM applications based on natural language processing was proposed. First, strategies for data storage and query acceleration based on the popular cloud‐based database were explored to handle the large amount of BIM data. Then, the concepts “keyword” and “constraint” were proposed to capture the key objects and their specifications in a natural‐language‐based sentence that expresses the requirements of the user. Keywords and constraints can be mapped to IFC entities or properties through the International Framework for Dictionaries (IFD). The relationship between the user's requirement and the IFC‐based data model was established by path finding in a graph generated from the IFC schema, enabling data retrieval and analysis. Finally, the analyzed and summarized results of BIM data were represented based on the structure of the retrieved data. A prototype application was developed to validate the proposed approach on the data collected during the construction of the terminal of Kunming Airport, the largest single building in China. The case study illustrated the following: (1) relationships between the user requirements and the data users concerned are established, (2) user‐concerned data can be automatically retrieved and aggregated based on the cloud for BIM, and (3) the data are represented in a proper form for a visual view and a comprehensive report. With this approach, users can significantly benefit from requesting for information and the value of BIM will be enhanced.     

基于 DEA 的 BIM-IPD 项目利益协同系统研究

综合项目交付（IPD）由于其相对传统交付模式的优势正得到愈加广泛的应用。建筑信息模型（BIM）的工程数据存取、分享功能与 IPD 模式高度匹配,能有效提升项目表现。但不成熟的利益分配机制却阻碍了 BIM-IPD 的推行。因此,本文在分析当前 IPD 工作模式的基础上,充分考虑项目表现指标及 BIM 应用水平,利用数据包络算法（DEA）,计算参与方投入产出效率,作为收益分配主要依据,提出了 BIM-IPD 项目的利益协同系统框架,为未来 IPD 项目的合同拟定提供了参考     

Building Information Modeling (BIM) outsourcing among general contractors

Building Information Modeling (BIM) is a process used by Architecture Engineering Construction (AEC) stakeholders which simulates a construction project in a multi-dimensional digital model and provides multitudes of project benefits from project inception to its occupancy. However, a variety of barriers impede a holistic BIM implementation. Due to these barriers, some general contractors outsource the creation and use of BIM models to specialized Information Technology (IT) firms. Since limited literature currently exists for BIM outsourcing, this study aims to identify BIM outsourcing patterns among the general contractors across the US and the perceived impacts it has on construction projects. Analysis of two-hundred and fifty-two complete responses from general contracting firms determines that 45% of responding companies have outsourced BIM, this signifies that outsourcing has become an important facet of BIM implementation. Data was also collected on company demographics, BIM outsourcing locations, strategic reasons for outsourcing, and various other aspects related to BIM outsourcing. The results indicate that respondents perceive BIM outsourcing as less efficient than in-house BIM implementation. However, continued use of outsourcing for BIM functions also displays the adaptability of the industry in meeting challenges and embracing new technology through alternative methods, despite the potential risks.     

A methodology for predicting the severity of environmental impacts related to the construction process of residential buildings

This paper introduces a systematic approach for dealing with potential adverse environmental impacts at the pre-construction stage. The proposed methodology serves as an assessment tool for construction projects to measure the environmental performance of their construction activities. It also provides a consistent basis for comparisons and for future eco-labelling and environmental benchmarking among construction companies and construction sites. Within the methodological framework, nine categories of environmental aspects are proposed: atmospheric emissions; water emissions; waste generation; soil alteration; resource consumption; local issues; transport issues; effects on biodiversity; and incidents, accidents and potential emergency situations. The methodology includes 20 performance indicators developed with the help of a panel of experts. In order to avoid a typical shortcoming in environmental assessments methods, these environmental indicators, both direct and indirect, are always based on quantitative data available in the project documents. Significance limits for environmental aspects are also developed based on a statistical analysis of 55 new-start construction projects. Four case studies are provided to illustrate the practical use of the proposed methodology.     

Automated performance measurement for 3D building modeling decisions

Building information modeling (BIM) is instrumental in documenting design, enhancing customer experience, and improving product functionality in capital projects. However, high-quality building models do not happen by accident, but rather because of a managed process that involves several participants from different disciplines and backgrounds. Throughout this process, the different priorities of design modelers often result in conflicts that can negatively impact project outcomes. To prevent such unwanted outcomes from occurring, the modeling process needs to be effectively managed. This effective management requires an ability to closely monitor the modeling process and correctly measure the modelers' performance. Nevertheless, existing methods of performance monitoring in building design practices lack an objective measurement system to quantify modeling progress. The widespread utilization of BIM tools presents a unique opportunity to retrieve granular design process data and conduct accurate performance measurements. This research improves upon previous efforts by presenting a novel application programming interface (API)-enabled approach to (a) automatically collect detailed model development data directly from BIM software packages in real-time, and (b) efficiently calculate several modeling performance measures during schematic and design development phases of building projects. These indicators can be used to properly arrange modeling teams in the quest for high-quality building models. The specific objectives of this study to examine the feasibility of a proposed automated design performance measurement framework, and to identify optimal modeling team configurations using empirical performance information. A passive data recording approach allows for the real-time capture of comprehensive user interface (UI) interaction and model element modification events. The proposed framework is implemented as an Autodesk Revit plugin. Next, an experiment is conducted to capture data using the developed Revit plugin. Experiment participants' individual production rates are estimated to establish the validity of the proposed approach to identify the optimal design team configuration. The presented approach uses the earliest due date (EDD) sequencing rule in combination with the critical path method (CPM) to calculate the maximum lateness for different design team arrangements.     

Logic for ensuring the data exchange integrity of building information models

Industry domains require distinct data and structures of building information models developed and tailored for their disciplines. To seamlessly exchange the building information models, Industry Foundation Classes (IFC), which is one of neutral formats, has been broadly used in the architecture, engineering and construction, and facility management industries. Model view definition (MVD), which is one of the IFC sub-schemas used by domain experts and BIM software vendors, consists of IFC-mapped data exchange requirements of each domain and helps software vendors develop IFC import and export features that allow project participants share and exchange BIM model information. Because of the heterogeneous translation processes and structures of IFC interfaces according to model views, their validation is imperative to ensure the integrity of BIM data and maintain a consistent data exchange environment. To accomplish this objective, this paper suggests the new approach to evaluating BIM data in accordance with diverse requirements of MVD. Since MVD entails various types of data exchange specifications, this research study examines their embedded checking rule types and categorizes corresponding implementation scenarios. In addition, this paper involves rule logic and IfcDoc-based BIM data validation developed based on the logical rule compositions of identified rules types and checking scenarios. This approach is expected to support sharing consistent BIM data sets and confirming the quality of received data pertaining to a syntax and semantics of a targeted model view.     

A computerized model for measuring and benchmarking the partnering performance of construction projects

Research into partnering performance measures for building and construction projects becomes crucial because a growing trend of client organizations has been observed to adopt partnering approach to procure their projects worldwide over the past decade. Although there are some related research studies and papers documented on this research area, few, if any, comprehensive and systematic research studies focus on developing a comprehensive, objective, reliable and practical performance evaluation model for partnering projects in construction. A Partnering Performance Index (PPI), which is composed of seven weighted Key Performance Indicators (KPIs), has been developed to measure, monitor, improve, and benchmark the partnering performance of construction projects in Hong Kong. A set of Quantitative Indicators (QIs) and well-defined ranges of Quantitative Requirements (QRs) for each QI have been further established using the Delphi survey technique and Fuzzy Set Theory. Evaluation of partnering success can now be based on quantitative evidences, thus tackling the subjectivity of performance evaluation. By making use of the Internet and database technology, PPI can be monitored on-line, thus saving much time, cost and efforts on data collection and retrieval than if they are done manually. As such, an Internet-based computerized partnering monitoring and benchmarking tool, namely the Computerized Partnering Performance Index System (CPPIS) has been developed. The Internet-based CPPIS enables project participants to input data at any time and location and the project administrators could perform data analysis via the Internet. The CPPIS also enables project managers to measure, monitor, improve and benchmark their partnering performances against those already stored in the database. Graphical presentations of data and various performance measures are also built in to assist various end-users to identify problematic areas and critical success factors for achieving partnering excellence.     

Modeling and evaluating construction project competencies and their relationship to project performance

In contemporary construction environments, construction organizations measure their performance against a set of predefined performance measures. These performance measures are governed by the ability of the organization to maintain necessary sets of “competencies” that assist in the successful execution of its construction projects. Competencies are often difficult to define and measure due to the multidimensional and subjective nature of their assessment. This paper identifies 41 project competencies with a total of 248 criteria for evaluating the different project competencies. This paper also identifies seven performance categories with 46 project key performance indicators. A systematic framework and methodology are presented in this paper to measure project competencies and project key performance indicators. A new modeling approach considering prioritized fuzzy aggregation, factor analysis, and fuzzy neural networks is presented to identify the relationship between project competencies and project key performance indicators. Data collected from seven construction projects are first aggregated using prioritized fuzzy aggregation to measure the different construction project competencies. The different project competencies are then analyzed using factor analysis. The factor analysis results are used with the prioritized fuzzy aggregation results to calculate inputs for the fuzzy neural networks. The fuzzy neural networks are then trained and tested using the data collected from the seven construction projects to identify and quantify the relationship between the different project competencies and project key performance indicators. This paper contributes to the current body of knowledge in project competencies and performance by establishing a standardized framework and methodology for evaluating the impact of construction project competencies on project key performance indicators. Furthermore, this paper incorporates advanced modeling techniques through the application of fuzzy set theory and neural networks to identify the relationship between the different project competencies and project key performance indicators. Identifying the relationship between construction project competencies and project key performance indicators allows construction organizations to improve their overall construction project performance by enhancing their projects competencies.     

Building information modeling as a risk transformer: An evolutionary insight into the project uncertainty

Building information modeling (BIM) is a promising technology for the construction sector, as it addresses multiple risks, supports decision-making and enhances value. However, its technological and contractual novelties introduce some new risks. To observe the BIM-driven risk transformation, this paper performs a thorough analysis involving international experts and practitioners. Data is collected in the form of open-ended interviews and typeset questionnaire along with case studies of running projects. Results reveal that BIM eliminates a majority of significant risks. Further, the findings fuel a new research problem; the lack of a dedicated BIM plugin for risk management. Responding to it, a theoretical framework is developed to automate the risk management process and improve overall project management practice. It is concluded that construction projects can greatly benefit from an automated risk management system and investment in developing a dedicated plugin is recommended, ensuring an effective penetration of BIM in the construction industry.     

Can project monitoring and control be fully automated?

An extended research programme has examined over the past two decades how productivity in construction projects can be improved through the development of models for project monitoring and control, which process automatically collected data on the actual project performance. Tests that were conducted with these models demonstrate that this approach can help overcome some of the limitations of existing manual methods. However, they also indicate that certain manually obtained data are still required in addition to the automatically collected data. A framework for semi-automated project monitoring and control is proposed, in which both manually and automatically collected data can be incorporated. This framework integrates the monitoring of projects with their control by taking into account the impact on productivity of existing deviations from the planned performance, and of the controlling actions that are proposed to deal with these deviations.