Journal of Construction Engineering and Management

The paper presents a review of the need for the planning and monitoring of construction work, a description of the characteristics of site construction work, particularly the degree of task repetition required for project execution, a review of two planning models comprising the critical path model, which is based on the concept that a project consists of a series of discrete activities, and the linear scheduling‐flow line model, which is based on the concept that a project consists of a series of repetitive activities. The practices of contractors when confronted with a construction scheduling problem and the use of the techniques derived from the models are examined. Six successful case studies are included, including two renovation projects and four commercial office buildings, two based on the critical path method, two based on the flow line method, and two that use both models in appropriate sections. The paper concludes with the general observations that: Few contractors use planning techniques to their full potential; critical path methods are best suited to nonrepetitive projects; flow line is best suited to repetitive projects; and as most contracts have dual characteristics, no single system can meet all a contractor's requirements for planning and monitoring construction work.

This paper describes a visual interactive procedure for fitting beta distributions to activity times in a simulation model when sample data are not available for statistical analysis of the model's input processes. Using subjective information about a given activity time the modeler specifies the activity's minimum and maximum times together with two of the following characteristics: mode, mean, variance, or selected percentiles. The fitting procedure includes efficient methods for computing the shape parameters of the beta distribution that most nearly matches the specified characteristics. The user can manipulate the fitted distribution by either revising the specified characteristics or directly altering a visual display of the density. This fitting procedure was implemented in a public‐domain microcomputer‐based software system called VIBES (visual interactive beta estimation system). An example from construction engineering illustrates the operation of VIBES.

The competitive and risk‐averse nature of the construction industry and its heuristic problem‐solving needs, among other reasons, have contributed to the development of nontraditional decision‐making tools. Research in artificial intelligence (AI), a branch of computer science, has provided more suitable tools to the construction industry. Expert systems have steadily been introduced for different applications in the industry. However, the performance of these systems during the last decade, is far from ideal. Neural networks research in AI has recently provided powerful systems that work as a supplement or a complement to such conventional expert systems. In this paper, neural networks are introduced as a promising management tool that can enhance current automation efforts in the construction industry, including expert systems applications. Basic neural network architectures are described, and their potential applications in construction engineering and management discussed. A neural network application is developed for optimum markup estimation. Future possibilities of integrating neural networks and expert systems as a basis for developing efficient intelligent systems are described.

Past studies of masonry‐labor productivity fail to accurately identify the factors that most affect masonry productivity and to quantify the factors' effects. This paper describes a methodology to identify and quantify the project‐related factors that significantly affect masonry productivity. Standardized data‐collection techniques are used to collect and consolidate data from 11 central Pennsylvania masonry projects. Exploratory analyses are performed to determine which factors most affect productivity. The factors identified are the work type, building element, construction methods, design requirements, and weather. More detailed analyses indicate that: (1) Data from multiple projects can be consolidated to obtain statistically valid results; (2) repetitive designs can effect a 30% improvement in productivity; (3) designs that require extensive layout and cutting can negatively affect productivity by as much as 40%; and (4) the effects of weather on masonry productivity are not well understood and deserve additional research.

It has been generally recognized that the construction industry needs to improve its efforts in managing the construction material. Studies have shown that the lack or mishandling of construction material can cause loss in productivity, resulting in money wasted. Such unnecessary expenses could be drastically reduced if more emphasis were given on properly managing the consumable and nonconsumable material from the design stage to its final use in the building process. A crucial step in any construction project is the acquisition of the needed material, both bulk and engineered. The quality of the delivered material, the timeliness of the shipments, etc., can far outweigh the importance of the purchasing price. Poor quality may require extensive rework, while late shipments may delay activities on the critical path. Thus, the selection of the proper vendor is very important for the overall performance on the construction site. This paper presents a vendor analysis system that is based on the best‐buy concept. It is demonstrated how the purchasing department's perception of a best buy differs from the priorities of a construction manager. A detailed comparison highlights these differences.

Contractors add significant premiums, on the order of 3%, to their bids when they have a low need for work or projects have high risk. An empirical study of the effect of need‐for‐work and project risk on contractor bid markups was conducted by assessing and analyzing utility functions obtained from construction contractors in a bid‐simulation exercise. Thirty New England contractors participated in the study. The statistical analysis of utility data indicates, with a high level of confidence, that need for work and risk significantly affect contractor bid markups. A revised model of bidding is presented. The paper also discusses the implications of these need‐for‐work and risk premiums for owners, contractors, and the insurance industry. Specifically, project managers should seriously consider investing at least 1% of the project cost in studies that reduce the risk perceived by contractors.

Construction‐engineering problems in the application of automation to soft‐ground tunneling, especially shield tunneling, are discussed. A concept for decision support in the selection of a type of shield‐tunneling machine and of an appropriate construction technology under given site conditions is presented. Corresponding engineering problems involved in an entire tunneling project from preplanning to excavation practice are also discussed. As an illustration of the discussed issues, the history of an earth‐pressure‐balanced shield‐tunnel project in Osaka, Japan, suggests an effective application of construction automation in similar future works.

The current generation of project‐control systems provides useful information, but has several problems that limit the effectiveness and efficiency in controlling projects. The current generation of project‐control systems has focused on the increased use of the microcomputer for sorting, computing, and storing data. This increased use of the microcomputer has not been without the introduction of difficulties to the process. The problems include input inefficiencies (e.g., multiple input of the same data) and output problems (e.g., extensive tabular listings of data). These problems lead to wasted or ineffective use of time to support the project‐control systems. Potential opportunities and advancements to address these deficiencies are presented. These opportunities include input technologies, analysis techniques, and systems integration. Specific examples discussed include scanning and digitizing technology, holography, artificial intelligence, remote‐sensing technologies, voice‐recognition systems, and enhanced software‐systems development. The areas discussed in this paper are intended to provide direction for future research and development of project‐control software for the next generation of project‐control systems for the construction industry.

Effective management of construction projects depends on good access to and control of data, especially data pertaining to cost and schedule control functions. Long recognizing the need to integrate these interrelated functions, researchers have proposed conceptual models to achieve this purpose. However, the proper design of an automated solution that would support the needs of integrated cost and schedule control and provide distributed access to data for different processing needs has been lacking. The purpose of this paper is to show how such an automated solution (represented by a data storage model) was properly designed and developed. The data storage model is developed using the first three steps of the process used to model engineering problems. The first step, problem definition, was accomplished using the work packaging model to solve the integration problem and by using data collection forms developed by R. S. Means Company to identify what data items are collected in cost and schedule control. The second step, conceptual modeling, utilizes Nijssen's information analysis methodology (NIAM) for data modeling. For the third step, computational modeling, the relational data model is selected. Each of the foregoing steps is described in detail in this paper.

Total float is a by‐product of critical‐path‐method calculations. It represents the length of time that an activity's finish date may be delayed without affecting the completion date of the entire project. Disputes over the existence of total float and its ownership are at the core of most claims involving change‐order work. While some tribunals have ruled in favor of contractors, others have held for owners on very similar facts. This paper is motivated by practical experience with problems concerning float. The paper acknowledges the fact that total float is beneficial to both owners and contractors. It does so by proposing ways of making its commercial trade‐in‐opportunity value explicit. Contract language is also introduced that will allow the trading of total float as a commodity. Such contract language grants the contractor the right to administer total float, imposes on the contractor the obligation to disclose its value and trade it on demand.

This paper describes an approach for probabilistic analysis of construction operations in which nonstationary cycle times have a major impact on production. A nonstationary cycle time is defined as a cycle time that varies with the passage of time and project progress. Examples of projects in which non‐stationary cycle times affect production include linear operations such as highway construction and tunneling operations. As the project progresses the haul time of the earth‐moving equipment increases. Although the proposed approach is sufficiently general to be used with various types of construction operations, the specific model presented was developed for tunneling operations. The model predicts the muck‐handling requirements of the tunneling operation at the desired level of confidence. Application of the model is shown through a numerical example, and the results are compared with the results of a conventional deterministic analysis.

Increased complexity of facilities, owners' changing needs, inadequate construction methods, and international competition have created strong demands for advanced construction technology. Recent developments in computer‐aided design and expert systems provide the architecture‐engineering‐construction (AEC) industry with significant potential for innovation. However, adoption of these computer technologies by a majority of AEC firms faces many hurdles. This paper describes, refines, and expands the process of technology transfer in an organization. The process focuses on the transfer of expert‐systems technology and is based on the models of innovation developed by Rogers, Shaffer, and Tatum, and on case studies of expert systems technology adoption in several industries. Understanding the technology transfer process, recognizing its players, and identifying the critical factors affecting it will lead to practical recommendations for increasing the rate of construction innovation and technology transfer.

The Center for Infrastructure Studies in the School of Engineering at Columbia University and Stone & Webster Engineering Corporation are conducting multidisciplinary research in the integration of three‐dimensional computer models in the construction process. This research has the potential to improve the productivity of the construction industry significantly. Whereas manufacturing productivity has increased over the past several decades, construction productivity has declined. Litigation is up, and delays are common and increasingly expensive. Large computer data bases and three‐dimensional models of construction projects are now feasible. Computer technology has the potential to revolutionize the methods used by the construction industry: Material quantities are immediately available from the computer model; the constructibility of the design is tested before actual construction; workers build the project on the computer screen before building it in the field; trades are coordinated visually; and progress is reported graphically. Columbia University and Stone & Webster are investigating the employment of this technology by using the construction of Columbia's new $108,000,000 Center for Engineering and Physical Science Research as a field laboratory. Graduate students in civil, mechanical, electrical, and industrial engineering are working with the construction managers to use this technology on the construction site and to document savings due to its use.

The European Community is scheduled to complete its market integration by the year 1992. When completed, the market will combine the separate European economies into a vast market capable of large economies of scale throughout industry. Businesses operating within or without the European community must prepare themselves for a dramatically different operating environment. Heretofore, protectionist practices of the member nations have kept the European community fragmented into 12 separate economies. Although protectionist barriers are falling, their influence will still be felt. Within the construction industry, the 1992 implementation of an integrated European market is expected to affect four major areas: public works construction, technical regulations and standards, subcontracting, and corporate taxation. This paper discusses the implications of these four areas on construction firms who anticipate doing business within the European community. Also discussed are opportunities presented by recent openings into eastern Europe. Whether or not American construction companies decide to enter the Europe market, they need to appreciate the possible impact of European companies emerging as large, global competitors.