Ho, Chung; Kim, Yong-woo; Zabinsky, Zelda B. (2022). Prefabrication Supply Chains With Multiple Shops: Optimization For Job Allocation. Automation In Construction, 136.
View Publication
Abstract
Prefabrication or off-site construction is a growing trend contributing to productivity improvements. It motivates specialty contractors and suppliers to operate multiple fabrication shops close to market regions, where a shop can produce and delivery prefabricated components in a timely fashion and at a minimal cost. Few quantitative models are available to assist companies with scheduling and allocation questions. This research utilizes optimization to answer these questions supporting the production planning in prefabrication supply chains. The paper presents an optimization model that seeks minimal cost while considering job demands and shop capacities. Computational results suggest that the model generates a lower-cost production schedule than the early due date (EDD) method. It also indicates that varying due dates cause changes in total cost. Moreover, this research supports decision-makers by analyzing the impacts of changing shop capacities regarding available machines. It provides further insight into construction supply chain management with multiple shops.
Keywords
Supply Chains; Job Shops; Supply Chain Management; Production Scheduling; Production Planning; Warehouses; Construction; Modularization; Optimization; Prefabrication; Scheduling; Off-site Construction; Modular Buildings; Scheduling Model; Precast; Management; Transportation; Performance; Decisions
Neff, Gina; Fiore-Silfvast, Brittany; Dossick, Carrie Sturts. (2010). A Case Study of the Failure of Digital Communication to Cross Knowledge Boundaries in Virtual Construction. Information Communication & Society, 13(4), 556 – 573.
View Publication
Abstract
When can digital artefacts serve to bridge knowledge barriers across epistemic communities? There have been many studies of the roles new information and communication technologies play within organizations. In our study, we compare digital and non-digital methods of inter-organizational collaboration. Based on ethnographic fieldwork on three construction projects and interviews with 65 architects, engineers, and builders across the USA, we find that IT tools designed to increase collaboration in this setting instead solidify and make explicit organizational and cultural differences between project participants. Our study suggests that deeply embedded disciplinary thinking is not easily overcome by digital representations of knowledge and that collaboration may be hindered through the exposure of previously implicit distinctions among the team members' skills and organizational status. The tool that we study, building information modelling, reflects and amplifies disciplinary representations of the building by architects, engineers, and builders instead of supporting increased collaboration among them. We argue that people sometimes have a difficult time overcoming the lack of interpretive flexibility in digital coordinating tools, even when those tools are built to encourage interdisciplinary collaboration.
Keywords
Digital Communications; Data Transmission Systems; Communication & Technology; Digital Electronics; System Analysis; Building Information Modelling; Collaboration; Qualitative Methods; Teams; Civil Engineering Computing; Digital Communication; Groupware; Knowledge Representation; Organisational Aspects; Virtual Reality; Case Study; Virtual Construction; Knowledge Barriers; Epistemic Community; Interorganizational Collaboration; Ethnographic Fieldwork; Interpretive Flexibility; Digital Coordinating Tool; Digital Collaboration; Technology; Objects; Design; Representations; Organizations
Migliaccio, Giovanni C.; Guindani, Michele; D’Incognito, Maria; Zhang, Linlin. (2013). Empirical Assessment of Spatial Prediction Methods for Location Cost-Adjustment Factors. Journal Of Construction Engineering & Management, 139(7), 858 – 869.
View Publication
Abstract
In the feasibility stage of a project, location cost-adjustment factors (LCAFs) are commonly used to perform quick order-of-magnitude estimates. Nowadays, numerous LCAF data sets are available in North America, but they do not include all locations. Hence, LCAFs for unsampled locations need to be inferred through spatial interpolation or prediction methods. Using a commonly used set of LCAFs, this paper aims to test the accuracy of various spatial prediction methods and spatial interpolation methods in estimating LCAF values for unsampled locations. Between the two regression-based prediction models selected for the study, geographically weighted regression analysis (GWR) resulted the most appropriate way to model the city cost index as a function of multiple covariates. As a direct consequence of its spatial nonstationarity, the influence of each single covariate differed from state to state. In addition, this paper includes a first attempt to determine if the observed variability in cost index values could be at least partially explained by independent socioeconomic variables. (C) 2013 American Society of Civil Engineers.
Keywords
Construction Industry; Interpolation; Regression Analysis; Socio-economic Effects; Spatial Prediction Methods; Location Cost-adjustment Factors; Empirical Assessment; Lcaf; Order-of-magnitude Estimates; North America; Unsampled Locations; Spatial Interpolation Methods; Geographically Weighted Regression Analysis; Gwr; Independent Socioeconomic Variables; Inflation; Indexes; Estimation; Geostatistics; Construction Costs; Planning; Budgeting
Migliaccio, G. C.; Bogus, Susan M.; Cordova-Alvidrez, A. A. (2014). Techniques for Continuous Improvement of Quality of Data Collection in Systems of Capital Infrastructure Management. Journal Of Construction Engineering And Management, 140(4).
View Publication
Abstract
oLa infraestructura del transporte es una de las mas grandes inversiones que realizan los gobiernos. Las agencias gubernamentales de transporte administran este capital y utilizan la informacion de las condiciones de este para decidir la programacion y tipo de mantenimiento y recursos a ejercer. Para recolectar la informacion pertinente, las agencias emplean evaluadores adiestrados para evaluar la infraestructura, ya sea en sitio o analizando fotografias y/o videos. Las evaluaciones visuales son empleadas para inspeccionar las condiciones de la infraestructura, incluyendo el desgaste de la superficie de los caminos y carreteras. Este articulo describe un Data Quality Assessment & Improvement Framework (DQAIF) (Sistema de Evaluacion y Mejora de la Calidad de la Informacion) para medir y controlar los datos de los evaluadores del deterioro de carreteras, al controlar el criterio de estos. El DQAIF es en un proceso ciclico de Mejora Continua de Calidad compuesto por: a)la evaluacion del nivel de acuerdo entre evaluadores -por medio del analisis estadistico (inter-rater agreement analysis), b)la evaluacion de la consistencia a traves del tiempo -mediante analisis de regresion lineal, y c)la implementacion de practicas gerenciales para mejorar los resultados mostrados en las evaluaciones anteriores. Se llevo a cabo un estudio de caso para validar el sistema propuesto. Los resultados mostraron que el DQAIF es efectivo para identificar y resolver problemas de la calidad de los datos obtenidos en las inspecciones de infraestructura. Con este sistema se garantiza la reduccion del riesgo de la subjetividad y asi aplicar acciones de mantenimiento mas oportunas. El DQAIF puede ser empleado en un programa de gerencia de infraestructura o en cualquier programa de ingenieria en donde la informacion esta sujeta al juicio o criterio personal de los individuos que realizan la evaluacion. Este proceso puede ser adaptado, incluso, para evaluar el desempeno de sistemas automatizados de evaluacion de pavimentos.
Keywords
Manual Pavement Distress; Quality Control; Pavement Management; Inspection; Quantitative Analysis; Data Collection; Assets; Reliability; Construction Materials And Methods
El-Anwar, Omar; Ye, Jin; Orabi, Wallied. (2016). Efficient Optimization of Post-Disaster Reconstruction of Transportation Networks. Journal Of Computing In Civil Engineering, 30(3).
View Publication
Abstract
Catastrophes, such as hurricanes, earthquakes, and tsunamis often cause large-scale damage to transportation systems. In the aftermath of these disasters, there is a present challenge to quickly analyze various reconstruction plans and assess their impacts on restoring transportation services. This paper presents a new methodology for optimizing post-disaster reconstruction plans for transportation networks with superior computational efficiency employing mixed-integer linear programming (MILP). The model is capable of optimizing transportation recovery projects prioritization and contractors assignment in order to simultaneously: (1)accelerate networks recovery; and (2)minimize public expenditures. The full methodology is presented in two companion publications, where the focus of this paper is to propose new methods for (1)decomposing traffic analysis; (2)assessing the traffic and cost performance of reconstruction plans; (3)reducing the massive solution search space; and (4)phasing the use of mixed-integer linear programming to optimize the problem. An illustrative example is presented throughout the paper to demonstrate the implementation phases. (C) 2015 American Society of Civil Engineers.
Keywords
Cost Reduction; Disasters; Emergency Management; Integer Programming; Linear Programming; Project Management; Public Finance; Search Problems; Town And Country Planning; Transportation; Solution Search Space Reduction; Cost Performance Assessment; Traffic Performance Assessment; Traffic Analysis; Public Expenditure Minimization; Network Recovery Acceleration; Contractor Assignment; Transportation Recovery Project Prioritization; Milp; Mixed-integer Linear Programming; Post-disaster Reconstruction Plan Optimization; Transportation Service Restoration; Reconstruction Plans; Transportation System Large-scale Damage; Tsunami; Earthquake; Hurricane; Catastrophe; Transportation Network; Post-disaster Reconstruction Optimization; Optimizing Resource Utilization; Natural Disasters; Housing Projects; Construction; Performance; Robustness; Recovery; Plans; Transportation Network Reconstruction; Post-disaster Recovery; Multi-objective Optimization; Computational Cost; Contractors Assignment; Search Space
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.
View Publication
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).
View Publication
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.
View Publication
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.
View Publication
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
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.
View Publication
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