Su-Ling Fan

This study proposes an interpretable framework that combines K nearest neighbors (kNN) regression with a case-based reasoning (CBR) scheme to quantify the benefits of Building Information Modeling (BIM) at the project level. A database of 256 completed public building projects from four major cities in Taiwan, including 28 BIM-enabled projects, is used to implement and validate the approach. For each query project, the system retrieves comparable cases, computes weighted similarities, and estimates cost-, schedule-, and quality-related outcomes. Statistical analyses indicate that BIM adoption can substantially reduce cost (up to about 40\% in the examined scenarios) and is associated with measurable quality improvements, particularly for high-rise buildings. The results demonstrate how a similarity-based, nonparametric estimator can be embedded into BIM decision support workflows under limited data conditions.

With manual update, progress monitoring of a construction project is notably challenging due to its labor-intensive and time-consuming nature. The issue of manual update has been proposed to be alleviated by automatic update, but most existing AI-based progress tracking approaches are based on counting the elements finished. As a result, they cannot accurately reflect actual progress status to the project management. This research aims to develop a system that updates the progress of the construction project by effectively identifying both the construction category and operational stage. It is achieved by systematically integrating the techniques of Augmented Reality (AR) and deep learning–based image classification with convolutional neural networks (CNNs). The proposed scheme enables real-time data capture, facilitating comprehensive progress evaluation across multiple project locations. Its effectiveness is demonstrated using a case study of an interior finishing project for a building in Tamkang University, Taiwan. It reveals that the proposed system accurately identifies the construction category and operational stage based on the materials applied, enabling precise tracking of the progress. The results confirm that the proposed scheme significantly enhances the accuracy in construction progress monitoring, avoiding manual inspection and minimizing discrepancies between the planned and actual progress.

The purpose of this paper is to address the problems of the current facilities maintenance management (FMM) system in finding necessary information, identifying defective facilities and prioritizing maintenance work orders. In this paper, in conjunction with building information modeling, a system is proposed to perform a preliminary inspection of each maintenance request, provide FMM staff with the location of the faulty facility and its associated details and provide recommendations for prioritizing repair work orders. Unity and Revit are used to implement the proposed system and a case study is conducted to demonstrate its effectiveness. An augmented reality (AR)-FMM system was developed using the AR technique in this paper. This system provides the related information even if the FMM receives a problem report without facility information from the occupant and performs a preliminary inspection so that the faulty facility and the route to it are identified. In addition, a work order sequence of pending requests was provided. The visualization of the facility using AR technology has brought great convenience and ease to FMM staff. This paper addresses the problems encountered in the current facility maintenance management system concerning AR technology.

Sponsored by the Construction Institute

The duration of a construction project is a key factor to consider before starting a new project. It needs to be accurately estimated from an early stage. Many researchers demonstrated the applicability of regression analysis (RA) in preliminary duration estimation for construction projects; however, RA and similar models fail to simulate the complex behavior of problems in estimating. In contrast, artificial neural networks (ANNs) have several significant benefits that make them powerful and practical for solving complex problems in the field of construction engineering and modeling nonlinearity in the data. Nevertheless, ANNs have constraints because of the absence of structured methodology to decide on various control features and their “black box” nature, which does not explain the underlying input–output process. Moreover, unlike construction cost, construction duration is not determined by the summation of all activities, but only by critical activities. Given these factors, this work presents a feature selection method while applying ANNs for estimating construction duration in the preliminary stage, and proposes a two-stage ANN to take into account the specific nature of construction duration. The results confirm the potential of two-stage ANNs and feature selection by sensitivity analysis to provide a more accurate estimate of construction duration and unlock potential knowledge in the network system to increase user confidence in ANN use.

The benefits of Building Information Modeling(BIM)-enabled construction projects have been identified and have attracted significant recent attention. However, BIM-based contract administration and legal issues have become essential concerns for all stakeholders during practical adoption and there is still a lack of effective contractual frameworks and detailed investigations. This study aims to identify the legal aspects and potential contract provisions for BIM-enabled projects as well as to evaluate the difference of such considerations between Taiwan and China. Different countries have shown different trajectories in BIM promotion, adoption, and legal system development, which can be potential factors in developing an effective and flexible contractual framework. A questionnaire survey method and comparison were applied to responses collected from experts in Taiwan and China, analyzed and discussed. Further suggestions in response to the current extent of understanding of BIM legal issues have also been provided. It is expected that this comparative study can contribute to further development of a robust contractual framework for BIM-enabled projects.

Although there are many discussions of the legal implications of BIM, none of the studies provides a comprehensive review of the legal issues associated with BIM; nor do they evaluate the solutions currently available to address the issues. This paper aims to provide a critical review of the legal issues arising from using BIM and of their associated solutions. A systematic review was conducted of fifty-five (55) journal articles and conference papers published from 2007 to 2017 to identify the legal issues. The identified legal issues were then analysed in relation to the solutions provided by the construction industry. The results of the study revealed that (1) an alternative project delivery approach that does not modify the original orientation of the design-bid-build procurement structure is required to deliver BIM effectively. (2) The potential change in the standard of care for project participants due to additional roles required in delivering BIM needs further investigation. (3) The roles for auditing a BIM delivery system must be included in the contracts to ensure the quality and compliance of BIM deliverables. The study not only reviews the legal issues associated with BIM, but more importantly, it also offers significant insights for future research.

Building information modeling (BIM) has entered into another phase of maturity, especially in countries that have been actively adopting and using BIM including in Taiwan, Republic of China. An effective management in BIM has increasingly become one of the demanding features in Taiwanese architecture, engineering, construction, and operation industries, particularly in dealing with the legal issues associated with BIM implementation. Therefore, the research aims to develop a preliminary contractual framework for BIM-based contract administration. Two objectives underpin the research, namely, (1) to identify the potential legal aspects that need to be considered in BIM-enabled projects, and (2) to determine the related contract provisions required in BIM contracts. The questionnaire survey method was adopted through a selective sampling approach in Taiwan. Thirty-six valid and completed questionnaires were analyzed. The results identify 21 related contract provisions that could potentially be used in BIM contracts. Following a thorough analytical discussion, these contract provisions were then incorporated into the developed contractual framework. While paving the way for a robust contractual mechanism for BIM-enabled projects in the future, the research contributes to the body of knowledge for BIM-based contract administration.