Many construction projects are becoming more complex and large in scale due to advances in technology and operations. These projects involve many stakeholders, with different geographical locations and working cultures, collaborating with one another throughout the project life cycle. Industry leaders believe that interface management systems can be created to improve alignment between stakeholders and reduce project issues and conflicts. However, identifying interfaces and monitoring interface states are significant challenges that creates a continues struggle for owners. Interfaces are generally considered as the links between different construction elements, stakeholders and project scopes. Poor management of interfaces may result in deficiencies in the project cost, time, and quality during the project life cycle execution, or may result in failures after the project has been delivered. Therefore, having systematic interface management to effectively handle the interfaces through the project life cycle is critical to project performance. In this paper, a process based approach is proposed for interface management of mega capital projects, starting with the definition and taxonomy of interfaces. Then, the main steps for implementing an Interface Management System (IMS) are introduced: (1) interface identification, (2) documentation, (3) issuing, (4) communication, and (5) closing.

Rail infrastructure renewal maintenance is capital intensive. As a contributor to rail deterioration, corrosion damage needs to be accurately analysed for renewal maintenance planning. The main contribution of this study is to introduce an information-dense forensic analysis method for characterizing rail corrosion damage in situ based on 3D imaging. Two state-of-the-art technologies, an arm laser scanner and handheld laser scanner, are employed for onsite digitization of the rail surface. Acquired 3D image data is analysed to characterize pitting corrosion in terms of volume, surface area coverage and average pit depth. Cyclic loading of the sampled rail is simulated using finite element analysis of the 3D image to establish risk potential for crack initiation. A case project was used to validate the feasibility of the developed approach. The results of this study demonstrate the usefulness of applying forensic methodology to renewal maintenance planning.

Purpose: This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach: This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings: Big data analysis in the world of construction management has become a necessity after the discovery of how much time, energy, and money can be preserved. By the investigation of big data in construction, the deduction was made that data analysis, data mining, and Building Information Modeling are the future for construction management. If properly applied to future construction management processes, big data analysis methodologies could eliminate mistakes, setbacks, and wasted resources for projects Practical implications: The paper provides strategic insights and practical thinking that have influenced some of the world’s leading organizations. Originality/value: The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

In large construction projects, optimally dividing, packaging, and awarding the work amongst contractors and suppliers can be challenging. Typically, this procurement process is executed in the pre-construction phase based on the experience and judgement of the project leadership team. Once procurement is completed, it is difficult to demonstrate whether the results of this process are optimal, or to explain the rationale behind decision making. An auditable and robust method is needed to address these issues, while still taking into account the expertise of the project leadership team. Thus, a comprehensive construction value packaging system (CVPS) is presented which serves as a computational and process environment for assisting project leaders by increasing the efficiency, auditability, and effectiveness of the procurement process. The development of this system requires a new concept to be defined, the construction value unit (VU), whose scope covers value-added work defined by type of activity, its stage in the value chain, and its specifications. Construction value packages are composed of VUs. Research findings demonstrate that the VPS has the potential to improve the contract management of an enterprise-wide construction supply chain.

Modularization and preassembly are parts of a trend toward staged fabrication that has been developing in the construction industry in many parts of the world over the past few decades. Successful delivery and transportation of materials in staged fabrication processes always has been a key challenge. Although substantial advances in modularization and prefabrication have been achieved recently, there is still a significant rate of damages and defects occurring during transportation and shipment. In addition, there are inaccuracies in staged-fabricated assemblies because of manually intensive quality control during the fabrication process. Thus, there is a significant need to monitor the fabrication processes continuously to avoid significant rework costs and delays. This paper presents an automated approach to register laser scanned data, which represents as-built status, with 3D CAD models for prefabricated steel assemblies. Moreover, automated registration enhances 3D tolerance analysis for automated quality control of prefabricated assemblies. An iterative closest point (ICP)-based model is used for automated registration in the presented paper. An experimental study is conducted to validate the proposed model for monitoring the fabrication and installation processes. Experimental results show that the presented approach can be used to detect defected parts or fabrication inaccuracies precisely and quickly.