Leaks in resource transmission pipelines is a growing concern for the water transmission industry. This creates a need to prevent the threat of leaks and minimize their damages through extensive research in leak detection technology. This research work provides a thorough investigation into the history of leak detection in pipelines by surveying the web of knowledge database and visualizing the outputs using visualization software VOSviewer and CiteNetExplorer. The analysis of the web of knowledge output presents a set of the ten most used keywords in the field of leak detection in pipelines that are further described and analyzed. Additionally, in-depth analysis of a randomly selected sample of papers was conducted to draw a sense of the progress in the industry over the past four decades. This article also defines a novel approach to define the leak detection phases, i.e., the identify-localize-pinpoint approach. Furthermore, two classes of leak detection systems are identified, static leak detection systems and dynamic leak detection systems. The two systems are defined as well as their differentiative capabilities. Finally, this article provides a summary of popular leak detection technologies to provide a broad sense of understanding for the leak detection field of research.

No abstract

No abstract

No abstract

Modular integrated construction (MiC) is a revolutionary construction method. However, the logistics management of MiC has always been a major barrier to the wider adoption of MiC. Nonetheless, this challenge can be tackled by the application of lean techniques, namely, just-in-time (JIT). Numerous studies have identified and evaluated the critical factors (CFs) required to implement JIT; however, there is no consensus among the previous studies on these CFs and their level of importance. Therefore, this research, for the first time, provides a systematic review and meta-analysis of these CFs. The systematic review identifies 42 CFs. To further provide a synthesis analysis of previous studies, a meta-analysis approach is used. This analysis is conducted on the identified CFs to evaluate their importance level and hence rank them. The results indicate that all the 42 CFs are important for applying JIT, of which seven are highly significant for successfully implementing JIT in MiC. Although the ranking obtained by meta-analysis is much more reliable than that provided in the individual studies, however, there is still a high heterogeneity in the results, which depicts the uncertain nature of the construction field. Therefore, sub-group analysis is conducted to investigate this heterogeneity and uncover the hidden patterns in the literature. This is achieved by studying the influence of predictive factors (moderators) on the importance level of CFs. This analysis shows that the economy of a country and the type of project executed are influential factors. The results further indicate that developing economies, in contrast to advanced economies, should pay more attention to three CFs. Also, the results show that seven CFs are much more important in MiC projects than the other project types. This research work is highly beneficial for theory development and for practitioners by identification of significant CFs that warrant management dedication to best apply JIT. Researchers, in particular, can consider the recommendations given here for implementing future meta-analysis studies.