Data-driven simulation-based model for planning roadway operation and maintenance projects

Mohamed, Emad; Jafari, Parinaz; Siu, Ming-Fung Francis; AbouRizk, Simaan

doi:10.1109/wsc.2017.8248049

Cited by 7 publications

(5 citation statements)

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“…Building Information Modelling (BIM) as a high-tech tool has arisen in the Architecture, Engineering, and Construction (AEC) industry since its origin in the 1980s (Eastman, Teicholz, Sacks, & Liston, 2008). Together with emerging information technologies, such as cloud computing, the Internet of Things, Artificial Intelligence, it has penetrated into different life cycle stages of the building and take an essential role in construction management (Chen et al, 2020;Mohamed et al, 2017). It can be explained as a threedimension representation whose function is sharing, exchanging, and storing the digital information of the project by some related software (Miettinen & Paavola, 2014).…”

Section: Introductionmentioning

confidence: 99%

Barriers and strategies for building information modelling implementation: a comparative study between New Zealand and China

Lovreglio

et al. 2022

International Journal of Construction Management

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Building Information Modelling (BIM) is a sharing platform that can present a parametric 3D model with various project information in the form of a digital display. In recent years, BIM adoption has become increasing globally as the Architectural, Engineering, Construction (AEC) industry has recognised its benefits. Meanwhile, many challenges of BIM adoption in different countries have been well documented. To address the gap in literature, this study examines the differences and similarities of BIM adoption between New Zealand and China. A questionnaire was conducted across the two countries to investigate the barriers and strategies for the implementation of BIM. Data from 146 respondents was collected in New Zealand and China. The result shows that there is a difference in the perception of Knowledge Barrier, Technology Barrier, Internal Strategy and External Strategy (Legal/Technology viewpoint) between New Zealand professionals and Chinese professionals. The differences identified offer important implications for government agencies to promote BIM implementation and for BIM service providers to better target the end-users.

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Section: Introductionmentioning

confidence: 99%

Barriers and strategies for building information modelling implementation: a comparative study between New Zealand and China

Lovreglio

et al. 2022

International Journal of Construction Management

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“…A further great development was introduced in the computer simulation world by developing Simphony.NET 3.5 (AbouRizk 2010). Simphony.NET was utilized by (Mohamed, Jafari, et al 2017) in Snow removal operations, for example. They used sensor data of weather, truck speed, and other data to simulate fame work for real-time planning of snow removal operations.…”

Section: Literature Reviewmentioning

confidence: 99%

Utilizing simulation to predict optimum number of projects

Ahmed¹,

Yaroslav²,

Hammad³

et al. 2022

Proceedings of the 2022 European Conference on Computing in Construction

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Contractors strive to generate profit from utilizing the available resources. This paper introduces a hybrid model of Discrete Event and Monte Carlo Simulations using SIMPHONY Software to model the operational interdependencies of the construction projects at the work packages level using the common pool of resources. The developed model considers organizational financial and equipment resources to help contractors forecast the optimum number of projects to bid for at the planning phase. A case of Bid/No-Bid in building houses is used to validate the model. The main contribution is in the methodology of applying operational techniques in making strategic decisions.

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“…IoT devices have the capability to enable this with ease. A simulation-based What-if scenario is generated to simulate, predict, optimize, project, and measure resource performance [52]. Global positioning system (GPS) based IoT devices are capable of collecting a large amount of data that were not fully utilized to optimize reaction times, a stochastic truck traveling speed previously.…”

Section: Applications Of Digital Twin In Macro Logisticsmentioning

confidence: 99%

Digital Twin Integrated Reinforced Learning in Supply Chain and Logistics

et al. 2021

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Background: As the Internet of Things (IoT) has become more prevalent in recent years, digital twins have attracted a lot of attention. A digital twin is a virtual representation that replicates a physical object or process over a period of time. These tools directly assist in reducing the manufacturing and supply chain lead time to produce a lean, flexible, and smart production and supply chain setting. Recently, reinforced machine learning has been introduced in production and logistics systems to build prescriptive decision support platforms to create a combination of lean, smart, and agile production setup. Therefore, there is a need to cumulatively arrange and systematize the past research done in this area to get a better understanding of the current trend and future research directions from the perspective of Industry 4.0. Methods: Strict keyword selection, search strategy, and exclusion criteria were applied in the Scopus database (2010 to 2021) to systematize the literature. Results: The findings are snowballed as a systematic review and later the final data set has been conducted to understand the intensity and relevance of research work done in different subsections related to the context of the research agenda proposed. Conclusion: A framework for data-driven digital twin generation and reinforced learning has been proposed at the end of the paper along with a research paradigm.

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Data-driven simulation-based model for planning roadway operation and maintenance projects

Cited by 7 publications

References 0 publications

Barriers and strategies for building information modelling implementation: a comparative study between New Zealand and China

Barriers and strategies for building information modelling implementation: a comparative study between New Zealand and China

Utilizing simulation to predict optimum number of projects

Digital Twin Integrated Reinforced Learning in Supply Chain and Logistics

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