System reliability optimization problems have been widely discussed to maximize system reliability with resource constraints. Birnbaum importance is a well-known method for evaluating the effect of component reliability on system reliability. Many importance measures (IMs) are extended for binary, multistate, and continuous systems from different aspects based on the Birnbaum importance. Recently, these IMs have been applied in allocating limited resources to the component to maximize system performance. Therefore, the significance of Birnbaum importance is illustrated from the perspective of probability principle and gradient geometrical sense. Furthermore, the equations of various extended IMs are provided subsequently. The rules for simple optimization problems are summarized to enhance system reliability by using ranking or heuristic methods based on IMs. The importance-based optimization algorithms for complex or large-scale systems are generalized to obtain remarkable solutions by using IM-based local search or simplification methods. Furthermore, a general framework driven by IM is developed to solve optimization problems. Finally, some challenges in system reliability optimization that need to be solved in the future are presented.

Shubin SI ,   Jiangbin ZHAO   et al.
Performance measurement (PM) generates useful data for process control, facilitates communication between different sectors, and helps to align efforts on the most important aspects of the business. Thus, PM plays a key role in the management of projects and organizations. PM is also important in the implementation of lean production principles and methods, such as reducing the share of nonvalue-adding activities, increasing process transparency, building continuous improvement into the process, and benchmarking. Moreover, the adoption of the lean production philosophy requires changes in PM. Despite its importance, limited studies have been conducted on the use of PM systems for assessing the impact of lean production programs in construction projects. In addition, studies on how lean companies (or projects) use performance measurement and to what extent the indicators adopted reflect the result of actions that have been undertaken are limited. This study proposes a set of requirements in PM systems of construction projects from the perspective of lean production and a taxonomy of performance metrics for lean production systems. Five empirical studies have been carried out on construction companies from South America involved in the implementation of lean production systems. The scope of this investigation is limited to the construction projects as production systems rather than PM at the level of construction organizations.

Synchronous collaboration sessions within the context of 4D BIM position construction professionals into a complex socio–technical system. This system includes hardware, software, people, and broader community aspects. This article strictly focuses on the ontology representation of synchronous collaboration sessions with collocated collective decision-making. The model is designed by considering various 4D BIM model uses while a digital multiuser touch table facilitates the collaboration between actors. The outlined ontological model aims to improve interoperability and to move toward a knowledge-driven, smart-built environment paradigm. A knowledge engineering methodology is outlined, by virtue of which the semantics of the presented model are defined and discussed. Concepts from nearby knowledge fields, especially from the Industry Foundation Classes, are reused. Several examples on querying the knowledge base according to the project meeting requirements are outlined to demonstrate the benefits of using the model. Although 4D BIM model data can be imported by using standard formats, capturing data about the social context remains a challenge in the future. This is expected to change the ontology model structure by considering user ergonomics, data modeling requirements, as well as technical implementation constraints.

Blockchain, a peer-to-peer, controlled, distributed database structure, has the potential to profoundly affect current business transactions in the construction industry through smart contracts, cryptocurrencies, and reliable asset tracking. The construction industry is often criticized for being slow in embracing emerging technologies and not effectively diffusing them through its supply chains. Often, the extensive fragmentation, traditional procurement structures, destructive competition, lack of collaboration and transparency, low-profit margins, and human resources are shown as the main culprits for this. As blockchain technology makes its presence felt strongly in many other industries like finance and banking, this study investigates the preparation of construction supply chains for blockchain technology through an explorative analysis. Empirical data for the study were collected through semi-structured interviews with 17 subject experts. Alongside presenting a strengths, weaknesses, opportunities, and threats analysis (SWOT), the study exhibits the requirements for and steps toward a construction supply structure facilitated by blockchain technology.

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