Browsing by Author "Wang, Kun-Chi"

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Applying building information modeling to integrate schedule and cost for establishing construction progress curves
(2016-12)
Wang, Kun-Chi
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Wang, Wei-Chih
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Wang, Han-Hsiang
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Hsu, Pei-Yuan
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Wu, Wei-Hao
A cost-based progress curve (called S-curve) is often used to control construction project schedules. To establish a progress curve, the costs that are associated with each scheduling activity must be determined. However, the distributions of the quantities (costs) of cost items among various activities are time-consuming to obtain and error prone, yielding an unreliable S-curve. This work proposes the use of three-dimensional building information model (BIM) objects to integrate schedule and cost by using the powerful BIM for data acquisition and storage. BIM objects are incorporated into a proposed four-step model to establish construction progress curves. The proposed model defines search criteria (cost item, object, floor, and zone) that precisely identify takeoff objects for extracting the quantities of cost items associated with each activity. The BIM uses keynote, assembly code, and family type catalog functions to provide pop-up menus for the efficient identification of cost items that are associated with each object to preventing errors in the manual typing of cost-item names. Finally, this work demonstrates that uploading the cost items and unit prices into cost estimation software in advance is critical to automating cost estimations in BIM. (C) 2016 Elsevier B.V. All rights reserved.
Applying building information modeling to support fire safety management
(2015-11-01)
Wang, Shih-Hsu
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Wang, Wei-Chih
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Wang, Kun-Chi
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Shih, Shih-Yu
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土木工程學系
Building information modeling (BIM) is useful in three-dimensional (3D) visualization and data/information storage for planning and maintaining building projects. Recently, researchers globally have been exploring the applications of BIM. In this work, a BIM-based model is designed to support fire safety management of buildings. The model comprises four modules evacuation assessment, escape route planning, safety education, and equipment maintenance. The evacuation assessment module integrates BIM with a Fire Dynamics Simulator to calculate the required safety egress time and the available safety egress time to evaluate the ability to evacuate in case of fire. The escape route planning module utilizes BIM to determine whether the distance of an escape route is acceptable. The safety education module presents hazardous areas, videos of escape routes and directional maps, all in three dimensions, to educate the occupants of the building about fire safety. The equipment maintenance module is implemented in a web-based prototype to support maintenance tasks in a remote management manner. The results of applying BIM have demonstrated that BIM can effectively provide 3D geometric data to support the assessment and planning of fire safety (using the first three modules), and it can store information in support of safety management and property management in a web-based environment (using the equipment maintenance module). (C) 2015 Elsevier B.V. All rights reserved.
CONCEPTUAL COST ESTIMATIONS USING NEURO-FUZZY AND MULTI-FACTOR EVALUATION METHODS FOR BUILDING PROJECTS
(2017)
Wang, Wei-Chih
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Bilozerov, Tymur
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Dzeng, Ren-Jye
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Hsiao, Fan-Yi
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Wang, Kun-Chi
During the conceptual phase of a construction project, numerous uncertainties make accurate cost estimation challenging. This work develops a new model to calculate conceptual costs of building projects for effective cost control. The proposed model integrates four mathematical techniques (sub-models), namely, (1) the component ratios sub-model, fuzzy adaptive learning control network (FALCON) and fast messy genetic algorithm (fmGA) based sub-model, (2) regression sub-model, and (4) multi-factor evaluation sub-model. While the FALCON- and fmGA-based sub-model trains the historical cost data, three other sub-models assess the inputs systematically to estimate the cost of a new project. This study also closely examines the behavior of the proposed model by evaluating two modified models without considering fmGA and undertaking sensitivity analysis. Evaluation results indicate that, with the ability to more thoroughly respond to the project characteristics, the proposed model has a high probability of increasing estimation accuracies more than the three conventional methods, i.e., average unit cost, component ratios, and linear regression methods.
Establishing Construction Scheduling Progress Curve based on Buidling Information Modeling Quantity Takeoffs
(2015-01-01)
Wang, Kun-Chi
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Wu, Wei-Hao
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Hsu, Pei-Yuan
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Gansonre, Abdoul-Aziz
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Wang, Wei-Chih
A cost cumulative progress curve (called S-curve) is often used as a basis for effective schedule control which is a key to the success of construction projects. In establishing a planned S-curve of a construction project, the cost of each scheduling activity must be determined. Furthermore, the contractual costs associated with the cost items should be fully distributed to all scheduling activities. However, the relationships between scheduling activities and cost items are complex because these relationships may be 1-to-1, many-to-1 or many-to-many relations. This research proposes a searching algorithm to conduct quantity takeoffs in Revit and QTO to facilitate the establishment of the planned S-curve. The proposed search algorithm defines different search steps (using various searching parameters, such as "floor", "physical object", "cost item", and "area") to identify corresponding cost items associated with different types of activities. The benefits of the proposed algorithm is demonstrated by applying it to a high-tech facility building in northern Taiwan.
ESTABLISHING ENGINEERING S-CURVES TO EVALUATE SUPERVISION ENGINEER ALLOCATIONS FOR HIGHWAY CONSTRUCTION PROJECTS
(2016)
Wang, Shih-Hsu
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Wang, Wei-Chih
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Hsu, Pei-Yuan
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Chen, Ci-Hao
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Wang, Kun-Chi
An engineering consultant firm needs to allocate engineers to supervise a highway construction project in each month during the construction phase. Properly assigning the supervision engineers under a cost-plus-fixed-fee contract has been a key factor affecting the profitability of the firm and the quality assurance of the project. Assigning too many engineers will be a waste, while allocating too few engineers may harm the supervision quality. This work proposes a two-stage model to develop engineering S-curves (called ES-curves) for planning and controlling the engineering supervision schedule. In the planning stage, a predictive ES-curve model is established based on historical ES-curves. In the controlling stage, an ES-curve is built according to the relationships between the engineering progress and construction progress. A cluster analysis and regression analysis are applied to the model development. A case study demonstrates that the produced ES-curves can help management in planning and evaluating when to increase or decrease the number of supervision engineers assigned to a project.