Effective management of engineering productivity is critical to achieving overall project success (CII 2001). Although engineering cost has approached to the level of 20 percent of a project’s total cost on some industrial projects, engineering productivity is not well understood. For these reasons, the Construction Industry Institute (CII) developed an Engineering Productivity Measurement System (EPMS) that consists of quantity-based metrics to directly measure engineering productivity, and drive continuous performance improvement. However, barriers to system implementation exist. Productivity metrics in the EPMS are measured for various disciplines and thus evaluating overall productivity was initially difficult because of the lack of a summary metric. Because the EPMS is still new to the industry, limited understanding of its metrics has presented a challenge to gaining acceptance for its use in benchmarking. This has inhibited the realization of its potential for supporting improvement. Now that a dataset for the EPMS has been compiled, however, analyses can be performed to support research and the resulting findings will help to overcome implementation barriers of the EPMS. The author developed this research with data from the EPMS and input from industry. Feedback was collected in CII training sessions, committee meetings, and industry forums. The researcher undertook quantitative analyses using the EPMS data. The results will assist industry practitioners to effectively monitor and manage engineering process to reach project success. Four main objectives were achieved in this study: 1) discipline and project level indices to summarize engineering productivity were constructed; 2) influence factors as a foundation of engineering productivity improvement were identified; 3) discipline information dependencies were measured quantitatively; and 4) the associations between engineering productivity and project performance were documented. / text

Not available / text

M.Ing.(Engineering Management) / Delays are a major problem faced by construction companies. The majority of the leading delays factors found from reviewing other studies were avoidable delay factors. The avoidable delay factors are factors caused only by the contractor. The reviewed studies gave recommendations for addressing the delay factors; however this study found that projects nevertheless still failing in South African construction industry and other countries even after the various studies made recommendations on how to avoid the delay factors. The objectives of this study were to establish the top ten avoidable delay factors and their mitigation measures in various countries and also to establish which of the proposed mitigation measures for each of the top ten avoidable delay factors were believed to be the answer in South African construction industry. A questionnaire was developed with questions that will probe the respondents to select the mitigation measures that will address each of the ten avoidable delay factors. The option answers were specifically designed to be close-ended. The size of the sample required was 80 and this study managed to get 82 responses. The survey was launched using SurveyMonkey which is an online survey platform. The data received was analysed for reliability and validity. The reliability was determined using Pearson Correlation Coefficient and was applied using the testretest approach. All questions had a coefficient greater than 0.6 which meant that the responses were reliable (strong). The validity was established using face validity. The responses were analysed to establish which mitigation measures have more frequency of selection. Some of the questions had some mitigation measures receiving more than 80% of the selection and some questions had some mitigation measures getting almost the same percentage selection. Most (60%) of the provinces of South Africa agreed on which mitigation measure must be used for addressing the avoidable delay factors.

Construction productivity lags behind most industries. In general, the process of construction is carried out in several smaller processes. For the overall construction process to be successful, continuity between these smaller processes must be achieved. This has been the persistent goal of construction productivity improvement for decades now. Waste is generated between the continuing activities by the unpredicted release of work and the arrival of resources. However, in recent decades the construction industry has a great need to improve its productivity, quality and incorporate new technologies to the industry due to increased foreign competition. In the late 1980s, researchers started looking at solving this problem in a more general and structured way based on the philosophy and ideology of lean production. In lean, adopting waste identification/reduction, or meeting the client's needs with minimal resources addresses the performance improvement. With recent developments in the construction industry, introduction of building information modeling (BIM) has had a significant influence on leaner construction. They are both complementary in several important ways. Various studies conducted exhibit that BIM is very crucial in reducing the project cost, site conflicts, project duration, error reduction, better and faster design development, and so on. This brings the question; can BIM be used as a tool for leaner construction? The objective of this thesis is to determine how BIM is helping achieve a leaner construction. More and more companies are adopting BIM as an acceptable waste reduction tool. A comprehensive study of lean theory and BIM was conducted, underscoring ways for BIM to help achieve leaner construction. The research was broadly conducted in three different parts. In the first part, a synthesis is drawn from a literature study to show that BIM helps reduce waste, helps in implementing lean techniques, and achieves lean principles. The second part focuses on the data acquired from a construction company to show that BIM helps reduce project cost, duration and conflicts. The third and the last part focused on getting the perspective view of different professionals in the construction industry on BIM by conducting focus interviews. A comprehensive conclusion was derived based on the findings from the three methods adopted.