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Dive into the research topics where Jack Chin Pang Cheng is active.

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Featured researches published by Jack Chin Pang Cheng.


Waste Management | 2013

A BIM-based system for demolition and renovation waste estimation and planning.

Jack Chin Pang Cheng; Lauren Y.H. Ma

Due to the rising worldwide awareness of green environment, both government and contractors have to consider effective construction and demolition (C&D) waste management practices. The last two decades have witnessed the growing importance of demolition and renovation (D&R) works and the growing amount of D&R waste disposed to landfills every day, especially in developed cities like Hong Kong. Quantitative waste prediction is crucial for waste management. It can enable contractors to pinpoint critical waste generation processes and to plan waste control strategies. In addition, waste estimation could also facilitate some government waste management policies, such as the waste disposal charging scheme in Hong Kong. Currently, tools that can accurately and conveniently estimate the amount of waste from construction, renovation, and demolition projects are lacking. In the light of this research gap, this paper presents a building information modeling (BIM) based system that we have developed for estimation and planning of D&R waste. BIM allows multi-disciplinary information to be superimposed within one digital building model. Our system can extract material and volume information through the BIM model and integrate the information for detailed waste estimation and planning. Waste recycling and reuse are also considered in our system. Extracted material information can be provided to recyclers before demolition or renovation to make recycling stage more cooperative and more efficient. Pick-up truck requirements and waste disposal charging fee for different waste facilities will also be predicted through our system. The results could provide alerts to contractors ahead of time at project planning stage. This paper also presents an example scenario with a 47-floor residential building in Hong Kong to demonstrate our D&R waste estimation and planning system. As the BIM technology has been increasingly adopted in the architectural, engineering and construction industry and digital building information models will likely to be available for most buildings (including historical buildings) in the future, our system can be used in various demolition and renovation projects and be extended to facilitate project control.


Advanced Engineering Informatics | 2010

Modeling and monitoring of construction supply chains

Jack Chin Pang Cheng; Kincho H. Law; Hans J. Bjornsson; Albert T. Jones; Ram D. Sriram

The planning and management of supply chains require properly specifying the participating members and the relationships among them. Construction supply chains usually consist of numerous participants and are complex in structure. Representing construction supply chains using a network model can help understand the complexity, support re-configuration, identify the bottlenecks, and prioritize companys resources, as well as add values to the management of construction projects. Using a case example on the mechanical, electrical and plumbing (MEP) processes in a construction project, this paper demonstrates the modeling of construction supply chains using the Supply Chain Operations Reference (SCOR) framework developed by the Supply Chain Council (SCC). The SCOR modeling framework provides a structured and systematic way to model and decompose a supply chain from conceptual representation to process element specification. The SCOR framework is commonly used by corporations for strategic planning of their supply chains. This paper further presents a model-based service oriented framework that leverages the SCOR models for performance monitoring of construction supply chains. In the supply chain management and monitoring framework each supply chain process element is implemented as a discrete web service component. The framework is built on a service oriented collaborative system, namely SC Collaborator, that we have developed using web service technology, open standards, and open source technologies.


ISPRS international journal of geo-information | 2017

A State-of-the-Art Review on the Integration of Building Information Modeling (BIM) and Geographic Information System (GIS)

Xin Liu; Xiangyu Wang; Graeme Wright; Jack Chin Pang Cheng; Xiao Li; Rui Liu

The integration of Building Information Modeling (BIM) and Geographic Information System (GIS) has been identified as a promising but challenging topic to transform information towards the generation of knowledge and intelligence. Achievement of integrating these two concepts and enabling technologies will have a significant impact on solving problems in the civil, building and infrastructure sectors. However, since GIS and BIM were originally developed for different purposes, numerous challenges are being encountered for the integration. To better understand these two different domains, this paper reviews the development and dissimilarities of GIS and BIM, the existing integration methods, and investigates their potential in various applications. This study shows that the integration methods are developed for various reasons and aim to solve different problems. The parameters influencing the choice can be summarized and named as “EEEF” criteria: effectiveness, extensibility, effort, and flexibility. Compared with other methods, semantic web technologies provide a promising and generalized integration solution. However, the biggest challenges of this method are the large efforts required at early stage and the isolated development of ontologies within one particular domain. The isolation problem also applies to other methods. Therefore, openness is the key of the success of BIM and GIS integration.


Structure and Infrastructure Engineering | 2016

A framework for 3D traffic noise mapping using data from BIM and GIS integration

Yichuan Deng; Jack Chin Pang Cheng; Chimay J. Anumba

Abstract Traffic noise is a major health concern for people living in urban environments. Noise mapping can help evaluating the noise level for certain areas in a city. Traditionally, noise mapping is performed in 2D geographic information system (GIS). The use of 3D GIS is also emerging in noise mapping in recent years. However, the current noise-mapping platforms can only conduct noise evaluation for the outdoor environment and the indoor environment separately. In addition, related information about absorption coefficient and transmission loss (TL) in noise calculation is not properly retrieved and is often replaced with a single value. In this research, building information modelling (BIM) and 3D GIS are integrated in order to combine traffic noise evaluation in both outdoor environments and indoor environments in a single platform. In our developed BIM–GIS integration platform, the built environment is represented in a 3D GIS model that contains information at a high level of detail from BIM. With the integration with BIM, the 3D GIS model now has access to detailed indoor features such as interior walls and interior rooms. Noise evaluation could therefore be performed at a room level in the developed platform. Essential parameters such as absorption coefficient and TL can be extracted directly from BIM for noise calculation. The 3D GIS model is connected with detailed BIM so that any changes in the indoor and outdoor features can be reflected to each other. The Italian C.N.R model is modified and applied in the platform to conduct noise calculation. This paper presents the details for the development of the noise-mapping BIM–GIS platform based on ArcGIS. Two use cases were analysed to show the role of such platform in the decision-making process of both urban planning and interior design.


Waste Management | 2016

Quantification of construction waste prevented by BIM-based design validation: Case studies in South Korea

Jongsung Won; Jack Chin Pang Cheng; Ghang Lee

Waste generated in construction and demolition processes comprised around 50% of the solid waste in South Korea in 2013. Many cases show that design validation based on building information modeling (BIM) is an effective means to reduce the amount of construction waste since construction waste is mainly generated due to improper design and unexpected changes in the design and construction phases. However, the amount of construction waste that could be avoided by adopting BIM-based design validation has been unknown. This paper aims to estimate the amount of construction waste prevented by a BIM-based design validation process based on the amount of construction waste that might be generated due to design errors. Two project cases in South Korea were studied in this paper, with 381 and 136 design errors detected, respectively during the BIM-based design validation. Each design error was categorized according to its cause and the likelihood of detection before construction. The case studies show that BIM-based design validation could prevent 4.3-15.2% of construction waste that might have been generated without using BIM.


Advanced Engineering Informatics | 2015

Formulation and analysis of dynamic supply chain of backfill in construction waste management using agent-based modeling

Vincent J.L. Gan; Jack Chin Pang Cheng

This paper proposes two optimization models to solve a dynamic supply chain issue.The outcomes help reuse and recycle backfill, a major type of construction waste.The models are based on mathematical programming and agent-based modeling.The comparative study illustrates the performance of both approaches.Agent-based modeling is more capable of analyzing the dynamic supply chain. Backfill is the excavated material from earthworks, which constitutes over 50% of the construction wastes in Hong Kong. This paper considers a supply chain that consists of construction sites, landfills and commercial sources in which operators seek cooperation to maximize backfill reuse and improve waste recovery efficiency. Unlike the ordinary material supply chain in manufacturing industries, the supply chain for backfill involves many dynamic processes, which increases the complexity of analyzing and solving the logistic issue. Therefore, this study attempts to identify an appropriate methodology to analyze the dynamic supply chain, for facilitating the backfill reuse. A centralized optimization model and a distributed agent-based model are proposed and implemented in comparing their performances. The centralized optimization model can obtain a global optimum but requires sharing of complete information from all supply chain entities, resulting in barriers for implementation. In addition, whenever the backfill supply chain changes, the centralized optimization model needs to reconfigure the network structure and recompute the optimum. The distributed agent-based model focuses on task distribution and cooperation between business entities in the backfill supply chain. In the agent-based model, decision making and communication between construction sites, landfills, and commercial sources are emulated by a number of autonomous agents. They perform together through a negotiation algorithm for optimizing the supply chain configuration that reduces the backfill shipment cost. A comparative study indicates that the agent-based model is more capable of studying the dynamic backfill supply chain due to its decentralization of optimization and fast reaction to unexpected disturbances.


Giscience & Remote Sensing | 2018

Spatial and temporal variations of spatial population accessibility to public hospitals: a case study of rural–urban comparison

Yongze Song; Yi Tan; Yimeng Song; Peng Wu; Jack Chin Pang Cheng; Mi Jeong Kim; Xiangyu Wang

Quantification and assessment of nationwide population access to health-care services is a critical undertaking for improving population health and optimizing the performance of national health systems. Rural–urban unbalance of population access to health-care services is widely involved in most of the nations. This unbalance is also potentially affected by varied weather and road conditions. This study investigates the rural and urban performances of public health system by quantifying the spatiotemporal variations of accessibility and assessing the impacts of potential factors. Australian health-care system is used as a case study for the rural–urban comparison of population accessibility. A nationwide travel time-based modified kernel density two-step floating catchment area (MKD2SFCA) model is utilized to compute accessibility of travel time within 30, 60, 120, and 240 min to all public hospitals, hospitals that provide emergency care, and hospitals that provide surgery service, respectively. Results show that accessibility is varied both temporally and spatially, and the rural–urban unbalance is distinct for different types of hospitals. In Australia, from the perspective of spatial distributions of health-care resources, spatial accessibility to all public hospitals in remote and very remote areas is not lower (and may even higher) than that in major cities, but the accessibility to hospitals that provide emergency and surgery services is much higher in major cities than other areas. From the angle of temporal variation of accessibility to public hospitals, reduction of traffic speed is 1.00–3.57% due to precipitation and heavy rain, but it leads to 18–23% and 31–50% of reduction of accessibility in hot-spot and cold-spot regions, respectively, and the impact is severe in New South Wales, Queensland, and Northern Territory during wet seasons. Spatiotemporal analysis for the variations of accessibility can provide quantitative and accurate evidence for geographically local and dynamic strategies of allocation decision-making of medical resources and optimizing health-care systems both locally and nationally.


Engineering, Construction and Architectural Management | 2015

An ontology-based web service framework for construction supply chain collaboration and management

Moumita Das; Jack Chin Pang Cheng; Kincho H. Law

Purpose – The purpose of this paper is to present a framework for integrating construction supply chain in order to resolve the data heterogeneity and data sharing problems in the construction industry. Design/methodology/approach – Standardized web service technology is used in the proposed framework for data specification, transfer, and integration. Open standard SAWSDL is used to annotate web service descriptions with pointers to concepts defined in ontologies. NoSQL database Cassandra is used for distributed data storage among construction supply chain stakeholders. Findings – Ontology can be used to support heterogeneous data transfer and integration through web services. Distributed data storage facilitates data sharing and enhances data control. Practical implications – This paper presents examples of two ontologies for expressing construction supply chain information – ontology for material and ontology for purchase order. An example scenario is presented to demonstrate the proposed web service fr...


Computing in Civil and Building Engineering - Proceedings of the 2014 International Conference on Computing in Civil and Building Engineering | 2014

BIMCloud: A Distributed Cloud-Based Social BIM Framework for Project Collaboration

Moumita Das; Jack Chin Pang Cheng; Srinath Shiv Kumar

Building information modeling (BIM) aims to facilitate information management and collaboration among stakeholders in different domains over the building life cycle. BIM models are increasingly used as an object-based information hub for storing, integrating and managing building information in different aspects. Over the building life cycle, stakeholders like the owner, designers and subcontractors keep reviewing and commenting on different building components, but these social interactions are often not recorded and managed in a structured manner. This paper presents a distributed cloud-based BIM framework that was designed to support collaboration among project participants and information sharing. The framework, namely BIMCloud, was developed based on Apache Cassandra which can be deployed on public cloud servers like Amazon EC2 or private cloud servers hosted in own infrastructures. A schematic data structure was also developed to capture the building component-based social interactions, which could be used for mining and post-processing to generate knowledge in the future. The BIMCloud framework stores BIM models based on the IFC schema and the developed schema for Social BIM. Therefore, people can make changes to the BIM models in the BIMCloud framework by transferring only a partial BIM model. An example scenario is presented in this paper.


Coastal Management | 2010

MINOE: A Software Tool to Analyze Ocean Management Efforts in the Context of Ecosystems

Julia A. Ekstrom; Gloria T. Lau; Daniel J. Spiteri; Jack Chin Pang Cheng; Kincho H. Law

Transitioning ocean governance into an integrated ecosystem-based approach requires improved knowledge of existing governance arrangements. This article presents a software tool, MINOE, to assist policymakers, scientists, and others involved in ecosystem-based management initiatives to navigate through management documents as they relate to a user-defined ecosystem. The tool uses a conceptually modeled ecosystem, defined by the user, and text analysis of a set of management-related documents to determine which ecosystem linkages are potentially acknowledged in the documents. For illustration, the set of documents included with MINOE currently (and used to demonstrate the software in this article) are laws and regulations from four geopolitical jurisdictions for the year 2006; however, users may also import other documents for a more tailored application. Features include an interactive matrix containing results about the set of management documents within the users scope and scale of interest. In addition, MINOE includes metrics and visualization tools to synthesize information derived from the documents. The article presents the software tool, describes potential uses for the tool, and ends with a discussion of future work to expand the program.

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Irene M.C. Lo

Hong Kong University of Science and Technology

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Yichuan Deng

Hong Kong University of Science and Technology

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Moumita Das

Hong Kong University of Science and Technology

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Yi Tan

Hong Kong University of Science and Technology

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Qian Wang

Hong Kong University of Science and Technology

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Vincent J.L. Gan

Hong Kong University of Science and Technology

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Vignesh Venkataraman

Hong Kong University of Science and Technology

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