Journal of Construction Engineering and Management

Rehabilitation projects often suffer from delays and escalating costs. This may be attributed to a high degree of uncertainty in defining the scope of work for these projects during the design stage. This is particularly true for rehabilitation work on structures that suffered a catastrophe such as fire or war damage. Reasons for these problems are reviewed with emphasis on the role of the architect/engineer (A/E) in avoiding underestimation of required work during the stages of the project. Many common problems could be avoided if a more thorough survey was conducted of the damaged building at the initial design stage. Changes to the scope of work during the construction stage may cause serious delays and cost overruns. Recommendations are given to minimize ambiguities in the scope of work and avoid disputes among the parties to the contract. This can be achieved by employing an experienced A/E and by making sound decisions throughout the project span.

The final negotiation in the competitive tender of a build, operate, and transfer (BOT) infrastructure project is concentrated on the financial and contractual elements associated with the concession agreement and financial package. This paper shows how there are several elements, in particular those related to tolls, that are regarded by governments and promoters as both important and difficult to negotiate during the final negotiation. The Competitive Tendering and Negotiation Model is therefore a useful process model for the government and promoters involved in a BOT tender to have a common understanding and to reach a successful conclusion at the final negotiation.

This paper focuses on the application of “combined simulation modeling” to achieve more accurate and flexible modeling of random processes affecting construction progress. In particular, a model is presented where a project schedule prepared using the critical path method (CPM) is transferred into a process interaction-discrete event simulation model and then combined with a continuous change weather process in the same model. The combined approach provides certain advantages to other methods. It is more effective than deterministically adding the expected delay due to weather to the expected duration of the project estimated from CPM, for example. It is also more accurate than using straight Monte Carlo-simulation of the CPM schedule or discrete event simulation modeling. The paper also provides an overview of the various aspects of implementing the combined model including use of mathematical and statistical methods to model weather processes and trained neural networks to estimate the effects of weather on productivity.

Steel silos are widespread around the world, and are used for storing different materials, including cement, fertilizers, grains, and raw materials. Building a new silo provides a fairly big storage capacity within a short period of time. There are many types of steel silos, including field-welded silos, bolted silos, bolted silos with corrugated steel sheets, and silos (with small capacities) completely fabricated in shops. This paper presents a new method of construction that has been used in Egypt to build bolted silos with corrugated steel sheets. This method mainly features inverting the traditional sequence of field tasks, such that the building operation starts with the uppermost part of the structure and proceeds to the lowermost part. The method requires that the completed parts of the structure be lifted up, using specially devised tripod-mounted hoists, so that building operations always take place at grade. The new method is described in this paper in detail, along with the problems encountered during field operations. In addition, the merits, in terms of the basics of construction management, are discussed. They are cost, schedule, quality, and safety. Finally, this paper presents a new method that offers substantial opportunity for enhancing constructability of steel silos during field operations.

The application of simulation in the construction industry has always been hindered by the complexities involved in constructing simulation models and the resultant time requirement. This paper presents a modeling method for construction simulation—resource-based modeling (RBM), in which operating processes of active resources are defined as atomic models (basic and unique description of a particular process) and are stored in a model library. These atomic models can be modified to form project-specific atomic models according to user-specified project information. Through defined linking structures, they can be assembled into a working simulation model for the project. Therefore, the user can construct a simulation model for a project by simply specifying required resources and project site conditions. The modeler does not have to be proficient with simulation theory and the selected simulation language. Our experience with implementing simulation in the construction industry shows that this is an effective approach. A sample application is used to illustrate the RBM concepts and its advantages.

The use of design-build project procurement is rapidly increasing in the public sector. Documented design-build success and imminent changes in federal procurement law are indicators of continued large-scale growth in the public sector. Rapid growth, combined with a lack of long-term experience among many public agencies, necessitates continued investigation of the underlying principles of design-build. Understanding which project characteristics are critical for success is fundamental for improved public agency implementation. To this end, a comprehensive research study was conducted on public-sector selection of design-build. This paper discusses results from a survey of 88 public-sector design-build personnel and structured interviews of federal agency representatives. Five primary project characteristics are discussed: well-defined scope, shared understanding of scope, owner construction sophistication, adequate owner staffing, and established budget. These suggest selection of design-build as an appropriate delivery strategy for successful project completion. Additionally, this paper addresses public-sector criteria of success; these include: staying on budget, conforming to user's expectations, and staying on schedule.

Many repetitive construction field operations exhibit a phenomenon known as the learning or experience effect. A learning curve is generated when the time or cost required to complete one cycle of an activity is plotted as a function of the cycle number. For practicing construction engineers and managers, the greatest potential value of learning curves lies in their ability to predict future performance, instead of fitting historical data. This paper presents a new method for using learning curves to predict the time or cost to complete the remaining cycles of an activity in progress, to assess the accuracy of this method, and to compare the accuracy of this method with the standard forecasting technique used in construction cost reporting. Using the proposed method, the accuracy of predicting the time or cost required to complete an ongoing activity improves dramatically for about the first 25–30% of the activity and then levels off to within 15–20% of the actual value. Compared to the standard method using the cumulative average, the new learning curve method is shown to be more accurate. The analysis quantifies the trade-off between accuracy of predicting future performance and the timeliness and potential value of such a prediction.

Mathematical learning curve models can be used to predict the time or cost required to perform future cycles in a repetitive construction activity. The analyst has a choice of several methods of representing the data, usually trading off between response and stability of forecasting information. Traditionally, learning curve data has been evaluated using either unit data or cumulative-average data. This paper evaluates those two methods and two other techniques: the moving average and the exponentially weighted average. For the 54 construction activities evaluated, unit data gives the most accurate prediction of the time or cost to complete the remaining cycles of the activity. Cumulative-average data gives the least accurate prediction. Compared to unit data, the exponentially weighted average can predict future performance with only a slight loss of accuracy early in the activity, but equal accuracy later in the activity. The exponentially weighted average may offer an improved combination of stability and response, depending on the smoothing parameter chosen.

Location and scale estimates calculated from project bid data measures the consensus value from among the bidders along with their collective uncertainty about that value. Five robust statistical location and scale estimators are evaluated for their relative performance under competitive bidding conditions-small sample sizes with a high potential for spurious bids. Estimates are made for standard normal samples of three, five, seven, and nine observations using each estimator. Within each sample, one observation is systematically varied in a range of five standard deviations above and below the mean and the other observations are assigned their expected rank-order values. Sensitivity curves are used to illustrate the bias in each estimator caused by the placement of the errant observation. The median and normalized median absolute deviation were found to be the most effective of the five procedures analyzed for location and scale estimators, respectively. Applications of these robust procedures have use in improving legal guidance provided to the courts, enhancing procurement procedures, and providing more accurate bid evaluations. One application describes how robust statistics can be used to reconcile project bids.

Project managers for owners, designers, and contractors need real-time information to assist them in managing projects. This paper describes a process whereby owner, engineer, and construction contractor organizations can use continuous or time-dependent variables (e.g., owner expenditures, construction effort hours expended) to predict project outcomes from start of detailed design through construction completion. Continuous variable data were collected on 54 construction projects. S-curves were developed for two project outcome categories: (1) “successful” (meeting or exceeding budget and schedule expectations); and (2) “less-than-successful” (not meeting budget and/or schedule expectations of the owner). Statistical analysis was performed to identify those variables showing a statistically significant difference between the two project outcome categories. Variables exhibiting a significant difference between the S-curves for “successful” and “less-than-successful” projects can be used as predictors of project outcome. Results show that different variables were predictors of success at different points of time during the project life cycle. Practical applications of these results along with limitations and future research are described.

Construction technology innovation is becoming an increasingly important factor for the growth of many large Japanese firms. It has become essential that new construction technologies be identified, obtained on the most reasonable terms, and transferred smoothly to the construction site. This paper describes the four major factors that contribute to the development of innovative construction technology in Japan: (1) strategic alliances; (2) effective information gathering capability; (3) reputation through innovation; and (4) technology fusion. The paper also illustrates the technology evaluation process used by a typical large general contractor in Japan. It is concluded that global technology information gathering has increased the awareness of the large construction firms in Japan to outside technology. To implement synthesis of technology, these companies have participated in cross-industry research projects. The crucial link between innovation and business strategy in a large construction firm in Japan was found to be the long-range technology forecasting that integrates action of today with the vision of tomorrow.

The cast-in-place segmental cantilever construction method, further to its well-known advantages for long span bridge construction in general, does provide appropriate means to satisfy local needs for relatively long spans in an urban environment, practically without infringing on traffic or property below. Detailed are the structural considerations and construction challenges in the use of segmental cantilever bridges in two such urban environment cases for the Los Angeles County Metropolitan Transit Authority Metro Rail System. The Kramer Bridge is a continuous four-span box girder bridge 189 m (620 ft) long spanning over what previously was a hazardous-waste site. The Rosecrans Bridge is a continuous three-span box girder bridge 204 m (670 ft) long spanning diagonally over a busy city intersection. Despite difficulties experienced in the piling, cantilever, alignment, and closure operations, the cast-in-place segmental cantilever construction method allowed fast and economically competitive construction of two aesthetically pleasing structures.

This paper presents a rational approach for evaluating a tractor dozer's capability to excavate a given soil type. A number of empirical charts exist for equipment selection, and a complex formulation based on soil mechanics theory can be applied to predict dislodgement forces. However, there is no current method to compute dislodgement forces based on soil properties and uses the results as a basis for equipment selection. This paper proposes a simplified model based on Coulomb lateral earth pressure theory to predict dislodgement forces for a dozer blade geometry. The results from the simplified model analyses are verified using the more complex existing theory. Based on the results, a set of practical decision charts are developed that can be used by the practitioner to estimate the tractor dozer's ability to excavate various types of soils. I provide an example of how the charts are used to select equipment given a set of natural soil conditions. The methodology proposed, if verified in field tests, could be used to develop a comprehensive series of charts for various equipment models and soil types.

Modeling construction is a critical step for understanding it and improving its performance. The thrust of this research paper is the need for the development of valid credible models as a logical precursor to automation. This article reviews the key models used to represent construction. Through this examination, it makes an important distinction between process and system modeling concepts. This distinction is the basis for concluding that no single tool, by itself, is accurately capable of fully modeling both construction system and construction work processes. Thus an integrated approach to modeling is required. Accordingly, the research conducted by the writers utilized a new integrated modeling approach that combines a set of descriptive tools to allow the development of various perspectives of construction. This article presents one of these tools as a new system modeling concept that overcomes deficiencies in current system modeling approaches. The power of this new model is illustrated in a detailed comparison among key current system modeling concepts.