Journal of Construction Engineering and Management

Downtime resulting from machine breakdown invariably has a considerable impact on the performance of construction projects and companies as a whole, especially to contractors with heavy investment in equipment. Attempts to investigate the causes and consequences of downtime are rarely found. The aim of this paper is to characterize and quantify factors that influence downtime consequences (consequential problems resulting from downtime) of highway construction equipment based on the structural equation modeling (SEM) approach. A questionnaire survey was conducted to collect data on equipment management practices and downtime consequences among highway contractors in Thailand. The SEM model proposed is of value for both researchers and practitioners to facilitate a better understanding of the relationships among acquisition condition, operational practice, maintenance quality, disposal practice, and downtime consequence of heavy equipment. The model also helps contractors to manage equipment more efficiently by concentrating on several practices that can convey the greatest benefit in minimizing downtime consequences at each particular stage of a machine’s life cycle, rather than considering all practices simultaneously where the benefits gained are perhaps not proportional to the effort.

The residential construction industry is an important contributor to the Australian economy; the industry employs a very large component of the national workforce, and yet the industry is plagued by defective work and poor quality. Previous research has revealed that defects and rework are endemic in the residential sector. In an attempt to quantify the degree of defects being experienced in new residential construction this paper provides an analysis of defects that were recorded by a government-owned housing insurance organization, the Housing Guarantee Fund. This research represents one of the most comprehensive research studies of building defects undertaken to date in Australia. The data used were not based on a sample like previous studies but instead represent all new houses constructed in Victoria, Australia between 1982 and 1997. An analysis of the data revealed that one house in eight reported defects, and that the cost of rectification was 4% of the construction contract value. The paper discusses the nature of the most important defects and investigates the impact of contractor type and building type.

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.

Tower cranes are the centerpiece of production on today’s typical building construction sites. Tower cranes hoist and transport a variety of loads near and above people, working under crowded conditions, occasionally with overlapping work zones, and often under time, budget, and labor constraints. This work regime further increases the safety risk on sites that are inherently hazardous workplaces. This paper presents the results of a study that identified the major factors affecting safety in tower-crane environments and evaluated the degree to which each factor influences ongoing safety on site. Use of statistical data on accidents was ruled out as a source of information due to the countless number of incidents that go unreported, the common inability of statistics to provide root causes, and the questionability of statistics as a predictor of accidents. The research methodology was therefore based on comprehensive questioning of an expert team that included the safety managers and equipment managers of leading construction companies. With the limited resources available for safety improvement and accident prevention, greater attention must be paid by all parties involved to those factors evaluated as highly affecting site safety due to tower-crane work.

Although the number of environment-related disputes is increasing, no risk management approach exists to minimize such disputes at construction sites. The purpose of this study was to develop an environmental risk index model for general contractors to minimize third-party environmental disputes at construction sites. The analytic hierarchy process is used to weigh and calculate an environmental risk index. A case study demonstrated how to apply this model for risk evaluation, on-site monitoring, and environmental management, whereas a comparative analysis revealed that the model decreased the number of disputes to some degree at sites where it was used. This model makes it possible to minimize environmental disputes in the field effectively.

Time-cost trade-off analysis represents a challenging task because the activity duration and cost have uncertainty associated with them, which should be considered when performing schedule optimization. This study proposes a hybrid technique that combines genetic algorithms (GAs) with dynamic programming to solve construction projects time-cost trade-off problems under uncertainty. The technique is formulated to apply to project schedules with repetitive nonserial subprojects that are common in the construction industry such as multiunit housing projects and retail network development projects. A generalized mathematical model is derived to account for factors affecting cost and duration relationships at both the activity and project levels. First, a genetic algorithm is utilized to find optimum and near optimum solutions from the complicated hyperplane formed by the coding system. Then, a dynamic programming procedure is utilized to search the vicinity of each of the near optima found by the GA, and converges on the global optima. The entire optimization process is conducted using a custom developed computer code. The validation and implementation of the proposed techniques is done over three axes. Mathematical correctness is validated through function optimization of test functions with known optima. Applicability to scheduling problems is validated through optimization of a 14 activity miniproject found in the literature for results comparison. Finally implementation to a case study is done over a gas station development program to produce optimum schedules and corresponding trade-off curves. Results show that genetic algorithms can be integrated with dynamic programming techniques to provide an effective means of solving for optimal project schedules in an enhanced realistic approach.

The method for quantifying qualitative information on risks (QQIR) bridges the gap between qualitative and quantitative risk assessment methods. It employs fuzzy set theory and results in deriving customized probability density functions (PDFs) for stochastic applications in risk assessment and financial modeling. The QQIR method uses fuzzy sets for capturing expert opinions on uncertain information and it uses the fuzzy weighted average method for aggregating that information. The aggregated opinion then is converted proportionally into a PDF with respect to the possibility–probability consistency principle and the uncertainty–invariance principle. This paper describes the construction of the proposed QQIR method and explains the underlying operations and principles used. The different competing possible methods and principles that exist in fuzzy set theory and could have been chosen for designing the QQIR method will be introduced and numerically tested in detail to determine which method best fits the purposes of making the QQIR method work. The paper refers to possible applications of the method that have been published by the writers and concludes with a summary and limitations of the QQIR method. The QQIR method is generic and has been successfully validated and applied to the impact of political risks on infrastructure projects.