Lee, Wonil; Lin, Ken-yu; Johnson, Peter W.; Seto, Edmund Y.w. (2022). Selection of Wearable Sensor Measurements for Monitoring and Managing Entry-level Construction Worker Fatigue: A Logistic Regression Approach. Engineering Construction & Architectural Management (09699988), 29(8), 2905-2923.
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Abstract
Purpose: The identification of fatigue status and early intervention to mitigate fatigue can reduce the risk of workplace injuries. Off-the-shelf wearable sensors capable of assessing multiple parameters are available. However, using numerous variables in the fatigue prediction model can elicit data issues. This study aimed at identifying the most relevant variables for measuring occupational fatigue among entry-level construction workers by using common wearable sensor technologies, such as electrocardiogram and actigraphy sensors. Design/methodology/approach: Twenty-two individuals were assigned different task workloads in repeated sessions. Stepwise logistic regression was used to identify the most parsimonious fatigue prediction model. Heart rate variability measurements, standard deviation of NN intervals and power in the low-frequency range (LF) were considered for fatigue prediction. Fast Fourier transform and autoregressive (AR) analysis were employed as frequency domain analysis methods. Findings: The log-transformed LF obtained using AR analysis is preferred for daily fatigue management, whereas the standard deviation of normal-to-normal NN is useful in weekly fatigue management. Research limitations/implications: This study was conducted with entry-level construction workers who are involved in manual material handling activities. The findings of this study are applicable to this group. Originality/value: This is the first study to investigate all major measures obtainable through electrocardiogram and actigraphy among current mainstream wearables for monitoring occupational fatigue in the construction industry. It contributes knowledge on the use of wearable technology for managing occupational fatigue among entry-level construction workers engaged in material handling activities. [ABSTRACT FROM AUTHOR]; Copyright of Engineering Construction & Architectural Management (09699988) is the property of Emerald Publishing Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Keywords
Construction Workers; Wearable Technology; Logistic Regression Analysis; Fatigue (physiology); Frequency-domain Analysis; Heart Beat; Lifting & Carrying (human Mechanics); Construction Safety; Information And Communication Technology (ict) Applications; Management; Technology
Lingzi Wu is an Assistant Professor with the Department of Construction Management (CM) at the University of Washington (UW). Prior to joining UW in September 2022, Dr. Wu served as a postdoctoral fellow in the Department of Civil and Environmental Engineering at University of Alberta, where she received her MSc and PhD in Construction Engineering and Management in 2013 and 2020 respectively. Prior to her PhD, Dr. Wu worked in the industrial construction sector as a project coordinator with PCL Industrial Management from 2013 to 2017.
An interdisciplinary scholar focused on advancing digital transformation in construction, Dr. Wu’s current research interests include (1) integration of advanced data analytics and complex system modeling to enhance construction practices and (2) development of human-in-the-loop decision support systems to improve construction performance (e.g., sustainability and safety). Dr. Wu has published 10 papers in top journals and conference proceedings, including the Journal of Construction Engineering and Management, Journal of Computing in Civil Engineering, and Automation in Construction. Her research and academic excellence has received notable recognition, including a “Best Paper Award” at the 17th International Conference on Modeling and Applied Simulation, and the outstanding reviewer award from the Journal of Construction Engineering and Management.
As an educator and mentor, Dr. Wu aims to create an inclusive, innovative, and interactive learning environment where students develop personal, technical, and transferable skills to grow today, tomorrow, and into the future.
Hsieh, Shang-hsien; Lin, Hsien-tang; Chi, Nai-wen; Chou, Kuang-wu; Lin, Ken-yu. (2011). Enabling The Development Of Base Domain Ontology Through Extraction Of Knowledge From Engineering Domain Handbooks. Advanced Engineering Informatics, 25(2), 288 – 296.
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Abstract
Domain ontology, encompassing both concepts and instances, along with their relations and properties, is a new medium for the storage and propagation of domain specific knowledge. A significant problem remains the effort which must be expended during ontology construction. This involves collecting the domain-related vocabularies, developing the domain concept hierarchy, and defining the properties of each concept and the relationships between concepts. Recently several engineering handbooks have described detailed domain knowledge by organizing the knowledge into categories, sections, and chapters with indices in the appendix. This paper proposes the extraction of concepts, instances, and relationships from a handbook of a specific domain to quickly construct base domain ontology as a good starting point for expediting the development process of more comprehensive domain ontology. The extracted information can also be reorganized and converted into web ontology language format to represent the base domain ontology. The generation of a base domain ontology from an Earthquake Engineering Handbook is used to illustrate the proposed approach. In addition, quality evaluation of the extracted base ontology is performed and discussed. (C) 2010 Elsevier Ltd. All rights reserved.
Keywords
Ontology; Earthquake Engineering; World Wide Web; Theory Of Knowledge; Vocabulary; Programming Languages; Domain Handbook; Domain Ontology; Owl; Web Ontology Language; Knowledge Representation Languages; Ontologies (artificial Intelligence); Base Domain Ontology; Knowledge Extraction; Engineering Domain Handbooks; Domain Specific Knowledge Storage; Domain Specific Knowledge Propagation; Domain-related Vocabularies; Domain Concept Hierarchy; Development Process; Web Ontology Language Format; Earthquake Engineering Handbook; Semantic Web; Management; Design
Won, Jongsung; Lee, Ghang; Dossick, Carrie; Messner, John. (2013). Where to Focus for Successful Adoption of Building Information Modeling within Organization. Journal Of Construction Engineering And Management, 139(11).
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Abstract
Suggestions abound for successful adoption of building information modeling (BIM); however, a company with limited resources cannot adopt them all. The factors that have top management priority for successful accomplishment of a task are termed critical success factors (CSFs). This paper aims to derive the CSFs for four questions commonly asked by companies in the first wave of BIM adoption: (1)What are the CSFs for adopting BIM in a company? (2)What are the CSFs for selecting projects to deploy BIM? (3)What are the CSFs for selecting BIM services? (4)What are the CSFs for selecting company-appropriate BIM software applications? A list of consideration factors was collected for each question, based on a literature review, and then refined through face-to-face interviews based on experiences of BIM experts. An international survey was conducted with leading BIM experts. From the 206 distributed surveys, 52 responses from four continents were collected. This study used quantitative data analysis to derive a manageable number (4-10) of CSFs for each category from dozens of anecdotal consideration factors. The derived CSFs are expected to be used as efficient metrics for evaluating and managing the level of BIM adoption and as a basis for developing BIM evaluation models in the future.
Keywords
Architectural Cad; Building Information Modeling; Bim; Critical Success Factors; Csf; Management; Building Information Models; Organizations; Computer Software; Building Information Modeling (bim); Critical Success Factor (csf); Organizational Strategy; Bim Software Application; Bim Service; Bim-assisted Project; Information Technologies
Zhang, Su; Migliaccio, Giovanni C.; Zandbergen, Paul A.; Guindani, Michele. (2014). Empirical Assessment of Geographically Based Surface Interpolation Methods for Adjusting Construction Cost Estimates by Project Location. Journal Of Construction Engineering And Management, 140(6).
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Keywords
Construction; Interpolation; Project Management; Geographically Based Surface Interpolation Methods; Construction Cost Estimates; Project Location; Construction Projects; Proximity-based Interpolation; Location Factor; Proximity-based Method; Global Spatial Autocorrelation; Cost Index Databases; Cost Estimators; Spatial Interpolation Techniques; Conditional Nearest Neighbor; Cnn; Inverse Distance Weighted; Idw Methods; Spatial Prediction Models; Distance Weighted Interpolation; Spatial Interpolation; Kriging Method; Precipitation; Temperature
El-Anwar, Omar; Ye, Jin; Orabi, Wallied. (2016). Innovative Linear Formulation for Transportation Reconstruction Planning. Journal Of Computing In Civil Engineering, 30(3).
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Abstract
Following disasters, the pace of restoring transportation networks can have a significant impact on economic and societal recovery. However, reconstruction and repair efforts are typically faced by budget constraints that require careful selection among competing contractors. This paper presents an innovative formulation to optimize this complex planning problem in order to maximize the rate of transportation network recovery while minimizing the associated reconstruction costs. This study first contributes to the body of knowledge by offering an effective and efficient means of identifying the optimal schedules for reconstruction projects and the optimal contractor assignments. This is achieved by solving the problem using a new mixed-integer linear programming model. However, there are four main formulation challenges to represent this problem using linear equations because of the need to use logical operators. As such, the second contribution of this study is in offering innovative solutions to overcome these formulation challenges, which are generalizable to other construction scheduling and planning problems. This paper is companion to another paper that describes a holistic optimization and traffic assessment methodology for post-disaster reconstruction planning for damaged transportation networks. (C) 2015 American Society of Civil Engineers.
Keywords
Integer Programming; Linear Programming; Transportation; Innovative Linear Formulation; Transportation Reconstruction Planning; Economic Recovery; Societal Recovery; Complex Planning Problem; Transportation Network Recovery; Mixed-integer Linear Programming Model; Traffic Assessment Methodology; Postdisaster Reconstruction Planning; Natural Disasters; Housing Projects; Construction; Optimization; Performance; Robustness; Earthquake; Efficiency; Recovery; Plans; Transportation Network Reconstruction; Post-disaster Recovery; Multi-objective Optimization; Mixed-integer Linear Programming; Contractors Assignment; Linear Formulation; Reconstruction Costs
Wang, Guangbin; Song, Jiule. (2017). The Relation of Perceived Benefits and Organizational Supports to User Satisfaction with Building Information Model (BIM). Computers In Human Behavior, 68, 493 – 500.
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Abstract
In recent years, building information model (BIM) is becoming increasing popularity in architecture, engineering and construction (AEC) industry, many researchers and practitioners have verified the benefits of BIM as compared to traditional information technology, for example Autodesk CAD. As one of the key drivers of BIM adopt, BIM users are significantly impact on the success level of BIM implementation. As a factor leading to information system success and indicating the continuance intention after their initial adoption, BIM user satisfaction is studied in this work. Based on the data collected from 118 BIM engineers, this study examined the influence of five potential variables (such as attitude, perceived ease of use, perceived usefulness, top management support and management by objective) on BIM user satisfaction in AEC industry. The result from PLS (partial least square) showed that the perceived usefulness, top management support and management by objective are significantly associated with BIM user satisfaction, and the influence of management by objective on BIM user satisfaction is much stronger than top management support and perceived usefulness. Besides, perceived ease of use and attitude have a significant influence on perceived usefulness. Moreover, top management support is found to be positive associated with management by objective. Finally, the discussion of these results was presented. (C) 2016 Elsevier Ltd. All rights reserved.
Keywords
Personal-computer Utilization; Technology; Acceptance; Management; Success; Systems; Pls; Attributes; Objectives; Variables; Bim User Satisfaction; Perceived Ease Of Use; Perceived Usefulness; Top Management Support; Management By Objective
Kim, Jonghyeob; Han, Sangwon; Hyun, Chang-taek. (2019). Identification and Reduction of Synchronous Replacements in Life-Cycle Cost Analysis of Equipment. Journal Of Management In Engineering, 35(1).
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Abstract
Life-cycle cost analysis (LCCA) is a methodology used to calculate the total cost of a project from initial planning to final disposal. In conventional approaches, LCCA assumes that regular and preventive maintenance will be performed according to each replacement cycle for individual components, and replacement for each component is considered independently. However, because the components of equipment used in buildings are installed systemically, replacements of major components may cause unexpected replacements of dependent minor components. Therefore, it is necessary to identify additional replacements based on the associations among these related replacement components to achieve a more reliable LCCA. In response, this study proposes an LCCA model that comprehensively considers the relationships among the maintenance components. The development of the model involves identifying relationships among components using social network analysis (SNA), arranging individual replacement timings of the components that reflect these relationships, and analyzing the life-cycle cost (LCC) based on the arranged timing. To validate the model, its applicability and effectiveness was illustrated and tested using 19 components of a rainwater reuse system. This study makes a theoretical contribution to the body of knowledge by suggesting concepts of synchronous relationships and replacements based on SNA. In addition, the use of the model proposed in this study enables practitioners to analyze LCCs that reflect synchronous replacements, which allows more reasonable decision-making considering hidden costs in conventional LCC. (C) 2018 American Society of Civil Engineers.
Keywords
Decision Making; Life Cycle Costing; Preventive Maintenance; Synchronous Replacements; Life-cycle Cost Analysis; Lcca Model; Maintenance Components; Social Network Analysis; Painted Surfaces; Decision-making; Prediction; Model; Risk; Maintenance; Replacement; Synchronous Replacement; Synchronous Relationship; Life-cycle Cost Analysis (lcca); Social Network Analysis (sna)
Shang, Luming; Lee, Hyun Woo; Dermisi, Sofia; Choe, Youngjun. (2020). Impact of Energy Benchmarking and Disclosure Policy on Office Buildings. Journal Of Cleaner Production, 250.
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Abstract
Building energy benchmarking policies require owners to publicly disclose their building's energy performance. In the US, the adoption of such policies is contributing to an increased awareness among tenants and buyers and is expected to motivate the owners of less efficient buildings to invest in energy efficiency improvements. However, there is a lack of studies specifically aimed at investigating the impact of such policies on office buildings among major cities through quantitative analyses. In response, this study evaluated the effectiveness of the benchmarking policy on energy efficiency improvements decision-making and on real estate performances, by applying two interrupted time series analyses to office buildings in downtown Chicago. The initial results indicate a lack of statistically strong evidence that the policy affected the annual vacancy trend of the energy efficient buildings (represented by ENERGY STAR labeled buildings). However, the use of interrupted time series in a more in-depth analysis shows that the policy is associated with a 6.7% decrease in vacancy among energy efficient buildings. The study proposed a method to quantitatively evaluate the impact of energy policies on the real estate performance of office buildings, and the result confirms the positive impact of energy-efficient retrofits on the real estate performance. The study findings support the reasoning behind the owners' decision in implementing energy efficiency improvements in their office buildings to remain competitive in the market. (C) 2019 Elsevier Ltd. All rights reserved.
Keywords
Office Buildings; Building Failures; Time Series Analysis; Real Property; Energy Consumption; Metropolis; Building Performance; Chicago (ill.); Building Energy Benchmarking And Disclosure Policies; Building Energy Efficiency; Time Series Modeling; Energy Star (program); Building Management Systems; Buildings (structures); Decision Making; Energy Conservation; Maintenance Engineering; Time Series; Disclosure Policy; Energy Benchmarking Policies; Building; Benchmarking Policy; Energy Efficiency Improvements Decision-making; Estate Performance; Energy Efficient Buildings; Energy Star; Energy Policies; Energy-efficient Retrofits; Interrupted Time-series; Regression; Behavior; Designs; Building Energy Benchmarking And; Disclosure Policies; Buildings; Cities; Energy Efficiency; Energy Policy; Markets; Quantitative Analysis; United States
Kim, Taehoon; Kim, Yong-woo; Lee, Dongmin; Kim, Minju. (2022). Reinforcement Learning Approach To Scheduling Of Precast Concrete Production. Journal Of Cleaner Production, 336.
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Abstract
The production scheduling of precast concrete (PC) is essential for successfully completing PC construction projects. The dispatching rules, widely used in practice, have the limitation that the best rule differs according to the shop conditions. In addition, mathematical programming and the metaheuristic approach, which would improve performance, entail more computational time with increasing problem size, let alone its models being revised as the problem size changes. This study proposes a PC production scheduling model based on a reinforcement learning approach, which has the advantages of a general capacity to solve various problem conditions with fast computation time and good performance in real-time. The experimental study shows that the proposed model outperformed other methods by 4-12% of the total tardiness and showed an average winning rate of 77.0%. The proposed model could contribute to the successful completion of off-site construction projects by supporting the stable progress of PC construction.
Keywords
Precast Concrete; Reinforcement Learning; Deep Q -network; Production Scheduling; Minimize; Model