Feasibility of Automated Monitoring of Lifting Equipment in Support of Project Control

One of the differences between industrial manufacturing or processing plants and construction sites is the temporary nature of the construction site, which has traditionally precluded installation of sophisticated production monitoring systems. Monitoring of production progress, cost, and quality is performed almost exclusively manually, with the result that it is expensive and approximate, and is commonly delivered with a time lag that does not allow for an effectively closed control loop. Automated monitoring of construction lifting equipment to provide useful feedback information for project management is a strong potential candidate; almost all components and materials must be transported by machines, and monitoring of machines is relatively straightforward. A system concept, employing a “black box” monitor and an electronic building information model, was developed. A field study was conducted to test the feasibility of the concept. The results indicate that the system is technically feasible, and offers the potential to deliver real-time, accurate project control information at very low cost.     

Contextual Information Requirements of Cost Estimators from Past Construction Projects

Past project data sources provide key information for construction cost estimators. Previous research studies show that relying only on one’s own experience during estimation results in estimators’ bias. Having and referring to historical databases, containing objective information on what happened in past projects, are essential for reducing estimators’ biases. The first step toward development of useful project history databases is to understand what information estimators require from past projects. The research described in this paper targets estimators’ information needs identified through interviews, brainstorming sessions, task analyses, and card games conducted with estimators with different experience levels and specialized in heavy/civil and commercial construction projects, and exploration of historical and standard databases available in companies to determine what is being currently represented. Findings show that estimators need contextual information, depicting the conditions under which specific production rates were achieved, so that they can identify which production rate would be more realistic to use during the production rate estimation of an activity in a new bid. Comparison of the contextual information needs identified in this research with information items available in historical data sources (such as company cost reports, RSMeans, previous studies) highlighted some gaps and important opportunities for improvements in those sources. The identified contextual information items are significant for practitioners in developing ways to augment their existing project history databases to make them more beneficial for estimators.     

Automated Collection of Mixer Truck Operations Data in Highly Dense Urban Areas

Our research has investigated the feasibility of directly sourcing autonomous operations data from a construction-vehicle positioning system, so as to enable productivity analysis and simulation modeling in the practical context of ready mixed concrete production and delivery. In this paper, we first review research efforts related to applying radio frequency identification tags and global positioning system for tracking construction resources and acquiring operations data in the field. We then describe the technical design and system components of an automated data collection (ADC) solution to accumulating concrete delivery operations data, which is extended from a construction-vehicle positioning system tailored for highly dense urban areas. We further elaborate on how our ADC system captures, transforms, and analyzes data of mixer truck operations. Truck-tracking experiment results based on field trials are presented to demonstrate the usefulness of data sourced from our ADC system with respect to: (1) analyzing truck-waiting time versus truck-unloading time on site; and (2) predicting truck’s plant-to-site travel time. In conclusion, the ADC solution resulting from this research not only allows sophisticated analysis of mixer truck resource utilization at concreting sites situated in highly dense urban areas, but also provides an accumulation of input data that will enable concrete plant operations simulation modeling.     

Interpretation of Automatically Monitored Lifting Equipment Data for Project Control

Interpretation of the data that can be collected by automated monitoring systems on construction sites is the most significant challenge to providing useful management information. Distinct construction operations must be identified and associated with construction activities, so that they can be related to construction plans. Earlier research has indicated that construction equipment can be monitored conveniently and that individual equipment operations can be isolated and characterized. In this work, an approach has been developed for unique association of isolated equipment operations with planned construction activities. The approach is based on comparison of the values of various characteristics, calculated for each equipment operation, against preset filters of characteristic values for all expected basic construction activities. The composition of the set of characteristics is different for each data stream monitored and is dependent on the nature of the construction activities. The method has the distinct advantage of ensuring the uniqueness of each filter within the collection of filters when the system is calibrated at the start of any project, rather than during online data processing. In this way, rapid and accurate interpretation of monitored data can be guaranteed. The method was tested using data collected during construction of a high-rise office tower.     

Framework for Providing Customized Data Representations for Effective and Efficient Interaction with Mobile Computing Solutions on Construction Sites

Conceptual representations of information contained in product and process models are often difficult to use for accessing data when performing engineering tasks. This is especially true if project-management information contained in product and process models needs to be made accessible on a mobile computer on construction sites. To make this information accessible, customized conceptual and visual information representations are needed. For the project-management tasks of progress monitoring and creating and administering punch lists, existing approaches that provide access to relevant project information are ineffective and inefficient in transforming information from product and process models into usable representations. As a result, these applications do not always provide information representations that are of the required structure, granularity, and type. In this paper, we describe a navigational model framework, which is an approach that effectively and efficiently creates and manages different views of information contained in product and process models. We validated this framework by implementing a prototype system and testing it through a designed set of experiments. The use cases for these experiments were established in an extensive study on the information and data collection needs on construction sites.     

Cost Information Model for Managing Multiple Projects

Construction companies must deal with several projects at once, but a system to manage multiple projects is not fully developed yet. The first step towards developing such system is to design an information model that is suitable for managing multiple projects. This paper presents the cost-based project modeling (CBPM) method in contrast to the traditional activity-based project modeling methods. The CBPM uses cost as a core of the model along with other project information organized around it. The CBPM serves as a platform for integrating project information from multiple projects. Various types of construction costs are hierarchically modeled to generate corporate-wide information such as project performances, cash flows, and other predictive indicators. Based on the information model, an object-oriented database was developed to contain cost data across several projects. In the model, a module that connects to external systems is built into the model to enhance interactivity with the legacy systems and the industry standards. A prototype system was developed and tested with actual project data to validate the information processing capabilities of the model. The findings from the test indicate construction cost can be an excellent medium that can organize various types of information of multiple projects.     

Sensing and Field Data Capture for Construction and Facility Operations

Collection of accurate, complete, and reliable field data is not only essential for active management of construction projects involving various tasks, such as material tracking, progress monitoring, and quality assurance, but also for facility and infrastructure management during the service lives of facilities and infrastructure systems. Limitations of current manual data collection approaches in terms of speed, completeness, and accuracy render these approaches ineffective for decision support in highly dynamic environments, such as construction and facility operations. Hence, a need exists to leverage the advancements in automated field data capture technologies to support decisions during construction and facility operations. These technologies can be used not only for acquiring data about the various operations being carried out at construction and facility sites but also for gathering information about the context surrounding these operations and monitoring the workflow of activities during these operations. With this, it is possible for project and facility managers to better understand the effect of environmental conditions on construction and facility operations and also to identify inefficient processes in these operations. This paper presents an overview of the various applications of automated field data capture technologies in construction and facility fieldwork. These technologies include image capture technologies, such as laser scanners and video cameras; automated identification technologies, such as barcodes and Radio Frequency Identification (RFID) tags; tracking technologies, such as Global Positioning System (GPS) and wireless local area network (LAN); and process monitoring technologies, such as on-board instruments (OBI). The authors observe that although applications exist for capturing construction and facility fieldwork data, these technologies have been underutilized for capturing the context at the fieldwork sites as well as for monitoring the workflow of construction and facility operations.     

Tunnel-Boring Machine Positioning during Microtunneling Operations through Integrating Automated Data Collection with Real-Time Computing

This research aims to develop an automated and cost-effective solution to guide the advance of a tunnel-boring machine (TBM) during microtunneling and pipe jacking operations. Pros and cons of currently available TBM guidance systems are evaluated. A simplified TBM guidance system is proposed based on integration of automated data collection with real-time computing. The TBM’s position in terms of point coordinates is continuously and automatically surveyed by a robotic total station, thus making it feasible to derive any line and level deviations from as-designed tunnel alignment in real time. Furthermore, given the coordinates of three observation points on the TBM, the attitudes of the TBM, which are described by three rotation angles of yaw, pitch, and roll, can be determined by a vector observation algorithm. Monte Carlo simulation was conducted to assess errors of point positioning and attitude determination by the proposed solution. For concept proving and application demonstration, a hardware-software integrated prototype system was developed in house and validation experiments were successfully conducted in terms of: (1) automated surveying of multiple targets; (2) attitude determination for a moving object that mimicked a working TBM; and (3) field installation and testing based on an ongoing project.     

Java Inspection Framework: Developing Field Inspection Support Systems for Civil Systems Inspection

In order to provide useful and practical computing support for inspectors in the field performing inspection activities, computer systems have to be designed and customized to recognize the specific task and context of the inspection. Unfortunately, the development of field inspection support systems is difficult and still suffers from a lack of more general design knowledge. Effort is wasted when implementing different applications that share some common aspects. This paper presents a partial solution to the difficult problem of developing field inspection support systems—a modular and customizable software environment to facilitate the construction of such applications.     

Integrating Neurofuzzy System with Conceptual Cost Estimation to Discover Cost-Related Knowledge from Residential Construction Projects

Cost estimation during early stage of a building construction project plays an important role for feasibility analysis in the planning and design phase. Traditional knowledge-based approaches suffer an essential difficulty due to resource price fluctuation in the market. This paper presents a hybrid method that integrates the principal items ratio estimation method with the adaptive neurofuzzy inference system for mining of cost estimation data. The proposed method provides exceptional capability for mining estimation knowledge that is difficult to be discovered by traditional knowledge-based approaches. A case study of residential building projects in China is conducted to demonstrate the proposed method. The testing results show that the proposed method does not only achieve high estimation accuracy, but also provide desirable features for estimators, such as explicit fuzzy decision rules and graphical presentations.     

Web-Vacuum: Web-Based Environment for Automated Assessment of Civil Infrastructure Data

Data quality is extremely important where information dramatically influences the decisions being made. In the context of civil infrastructure systems, planning and management activities are critically dependent on data to support the efficient allocation of resources, detailed cost-benefit analysis, and informed decision-making. A Web-based tool, called Web-Vacuum, which employs data-mining (DM) techniques and partially implements a two-level data-quality assessment procedure, was developed to support the general purpose of data-quality assessment. The algorithms, workflow, and interfaces used in Web-Vacuum are presented. A data-quality assessment case study using a bridge management system data set is used to demonstrate that the application of Web-Vacuum can be used to assist in determining the quality of a data set.     

Improving Cost Estimates of Construction Projects Using Phased Cost Factors

Central to cost-based competition is the capability to accurately predict the cost of delivering a project. Most literature on cost estimation focuses on specific estimation methods as generic techniques and little attention has been paid to the unique requirements at each project stage. This note attempts to identify the critical factors for effective estimation at various stages of typical construction projects. Drawing from organization control theory and cost estimating literature, this note develops a theoretical framework that identifies the critical factors for effective cost estimation during each project phase of a conventional construction project. The underlying logic is that as a cost estimating effort progresses, both task programmability and output measurability improve. As a result, control effort will shift from input-oriented control to a combination of output and behavior control.     

Automated Generation of Work Spaces Required by Construction Activities

To provide a safe and productive environment, project managers need to plan for the work spaces required by construction activities. Work space planning involves representing various types of spaces required by construction activities in three dimensions and across time. Since a construction schedule consists of hundreds of activities requiring multiple types of spaces, it is practically impossible to expect project managers to specify manually the spatiotemporal data necessary to represent work spaces in four dimensions. This paper presents mechanisms that automatically generate project-specific work spaces from a generic work space ontology and a project-specific IFC (industry foundation class) based 4D production model. The generation of these work spaces leads to a space-loaded production model. Within this model, work spaces are represented as being related to the relevant construction activities and methods and as having attributes that describe when, where, and how long they exist, and how much volume they occupy. These space-loaded production models enable richer 4D CAD simulations, time-space conflict analysis, and proactive work space planning prior to construction.     

Local Information Access for Search and Rescue Using Wireless Data Storage Mediums

After a natural disaster strikes buildings, it is vital to immediately retrieve the related local information for efficient search and rescue (S&R) operations. Although it seems convenient to store the required local information (e.g., information about neighborhood, buildings) in a centralized database, S&R teams usually cannot access centralized databases because the information infrastructure is usually damaged or overloaded immediately after a disaster. This paper describes the search and rescue data access point (SR-DAP) system that was designed for storing and retrieving the required local information in/from data storage units that are deployed at buildings. In the paper, the developed approach is presented, and two key technologies (i.e., radio-frequency identification (RFID) tags and wireless sensor nodes) that are used as local storage mediums in SR-DAP are empirically evaluated. The results of the field experiments show that current technologies can be effectively utilized in the developed system. However, comparison of the technologies highlights the fact that the current wireless sensor technology is advantageous over RFID technology.     

Three-Stage Least-Squares Analysis of Time and Cost Overruns in Construction Contracts

Construction cost overrun and time overrun (delay) are a significant problem in highway-construction project delivery. Previous research studies have provided insight into the factors that affect overruns; however the findings may have been limited because they do not explicitly consider the simultaneous relationship between cost and time overruns. In this paper, we use data from Indiana highway projects to provide empirical evidence that a simultaneous relationship exists between cost and time overruns and that analysis of these two contractual outputs need to take due cognizance of such simultaneity. Using the three-stage least-squares technique, we identify a number of factors that significantly affect cost overrun and time overrun and we show how the effect of these variables vary by attributes such as project type and results of the bidding process. The models developed in this paper can help agencies enhance the estimation of the expected overruns of final cost and the delay in completion time for their planned projects.     

Statistical Analysis on the Cost and Duration of Public Building Projects

A probabilistic model is proposed to predict the risk effects on time and cost of public building projects. The research goal is to utilize a real history data in estimating project cost and duration. The model results can be used to adjust floats and budgets of the planning schedule before project commencement. Statistical regression models and sample tests are developed using real data of 113 public projects. The model outputs can be used by project managers in the planning phase to validate the schedule critical path time and project budget. The comparison of means analysis for project cost and time performance indicated that the sample projects tend to finish over budget and almost on schedule. Regression models were developed to model project cost and time. The regression analysis showed that the project budgeted cost and planned project duration provide a good basis for estimating the cost and duration. The regression model results were validated by estimating the prediction error in percent and through conducting out-of-sample tests. In conclusion, the models were validated at a probability of 95%, at which the proposed models predict the project cost and duration at an error margin of ±0.035% of the actual cost and time.     

Highway Construction Data Collection and Treatment in Preparation for Statistical Regression Analysis

Currently, there is not an understanding of the project factors having a statistically significant relationship with highway construction duration. Other industry sectors have successfully used statistical regression analysis to identify and model the project parameters related to construction duration. While the need is seen for such work in highway construction, there are very few studies which attempt to identify duration-influential parameters and their relationship with the highway construction duration. The purpose of this work is to describe the highway construction data needed for such a study, identify a data source, collect early-design project data, and prepare the data for statistical regression analysis. The Virginia Department of Transportation is identified as the optimal data source. The data collected include historical contract and project level parameters. To prepare for statistical regression analysis, the contract duration collected is converted to construction duration by a seasonal adjustment process which removes historically typical nonworking days.     

Effectiveness of ICT for Construction Information Exchange among Multidisciplinary Project Teams

The use of information and communication technology (ICT) has been commonplace in the construction industry, with the increased functionalities of intranets and extranets in a web-based environment. Yet, human and organizational hindrances bring about consequences which affect the effectiveness of these online collaboration tools. Through a cross-sectional study of six construction-related organizations via interviews with ICT developers and users, these hindrances and consequences are highlighted against contextual backgrounds which depict a wide spectrum of ICT use in the construction industry. The results underpin a questionnaire survey which identified the most frequently encountered hindrances, such as self-discipline, technical support, and system capacity, both for internal and external information exchanges. These hindrances, together with undesirable behaviors such as the tendency to forward information to irrelevant parties and ignore information, would result in double handling and missing of time targets. Results also show that public organizations seem to be less prone to the discipline problems. While ICT advances, it is imperative that users make the best use of it by understanding and avoiding the pitfalls.     

Quantiative Methodology for Determination of Cost Contingency in International Projects

This paper presents a quantitative methodology to determine financial impacts of the risk factors during the bidding stages of international construction projects. Project and country data of 26 construction projects from 21 countries were collected for evaluation of the international risk factors. The factors impacting cost contingency were identified using correlation and regression analysis techniques. The results indicated that four factors had major contributions for explaining the variations in the contingency levels. A regression model including the significant factors was developed to support bidding contingency decisions. The methodology presented provides a robust and practical statistical approach for determination of contingency by focusing on important risk factors. Details regarding model development and validation are presented along with a discussion on study limitations.     

Developing an ARIS-House-Based Method from Existing Information Systems to Project-Based Enterprise Resource Planning for General Contractor

In recent years, general contractors in the construction industry have gradually begun to implement a system called enterprise resource planning (ERP). During the ERP implementation process, contractors performed required analyses on daily operation functions demanded by the enterprise. The analyses focused on function mapping to ensure that ERP satisfies all the requirements, including the functions of existing information systems, and meets future requirements. The process of function mapping in the construction industry typically involves a series of lengthy and time-consuming meetings, and face-to-face discussions; systematic analysis procedure was lacking. This research will propose a novel function mapping approach, the Architecture of Integrated Information Systems (ARIS)-house-based (AHB) method, to enhance the effectiveness of meetings and improve the efficiency of discussions. In addition, AHB method will use the structure of ARIS-house diagram to guide the function mapping process, streamline existing information systems, meet future requirements, and successfully implement ERP. Finally, this research will use a case study to verify the effectiveness of the AHB method for contractor to implement ERP.