Makarand Hastak

Advanced automation or conventional construction process

Abstract The rapidly developing area of construction automation leads construction managers to critically evaluate the feasibility of replacing conventional construction processes by automated systems. This decision requires careful analysis of tangible and intangible factors such as need-based criteria, economic criteria, technological criteria, project specific criteria, and safety/risk criteria. This paper presents a decision making model and a decision support system (DSS) to assist construction managers in systematically evaluating whether to opt for a conventional construction process or an automated system for a given project. The proposed DSS, called AUTOCOP (AUTomation Option evaluation for COnstruction Processes), utilizes the Analytical Hierarchy Method (AHP) to analyze the tangible and the intangible set of criteria involved in the decision problem.

Systems analysis of project cash flow management strategies

Cash flow management is one of the most important determinants of the success of construction project management. Overdraft, retainage, financing, payment and billing policies constitute the most significant financial issues that contractors must plan, control and manage for the successful completion of construction jobs. Particularly, in an attempt to reduce project costs, contractors must balance cost savings of material discounts due to early payments and extra interest expenses because of additional overdraft. Through identifying feedback loops in project cash flows, a system dynamics model is developed for project cash flow management. The model is flexible to incorporate typical front‐end and back‐end loading cash flow management strategies and provides an interactive predication of project cash flows. A warehouse project is discussed to demonstrate how various cash flow strategies improve overdraft financing requirements and profitability. Especially, the analysis shows an 11% reduction on overdraft requirements while using an overbilling strategy, and 30% reduction if the trade credit strategy is implemented.

Modeling Social Opposition to Infrastructure Development

Social and political dynamics increasingly determine the fate of infrastructure development around the world. Decision makers involved with projects such as the Keystone XL pipeline in North America, the Belo Monte Dam in Brazil, and the Bujagali Dam in Uganda have been forced to substantially change their plans as a result of opposition. This study looks at such emergent dynamics to provide a quantitative assessment of risks associated with social sustainability in infrastructure development. An interactional model is proposed to analyze emergent risks in a complex system of systems and it is applied to emergent risks in infrastructure development. The analysis is based on the game-theoretic equilibria for an interaction between two actors, namely, the developer and the opposition. Using simulation the structural and contextual variations were investigated in the context of the project along with consequent emergent patterns of outcomes and associated risk profiles. The model comprises informal and formal interactional stages to investigate the impact of alternative mitigation strategies on project risk. The application of the proposed methodology is showcased in an analysis of informal and formal strategies to deliver socially sustainable projects.

A Framework for Life-Cycle Cost Assessment of Composites in Construction

The slow acceptance of composite materials in construction could be attributed to the high initial cost of composites compared to conventional materials and the limited information on life-cycle cost. This paper presents a unique framework for a probable life-cycle cost assessment model for composite materials in construction. The proposed model utilizes the historical life-cycle performance data for conventional materials, knowledge about material properties, and deterioration characteristics for new and conventional materials to effectively assess the life-cycle cost and behavior of composite materials in construction. The proposed model integrates deterioration characteristics of structural components under different environmental and loading conditions to establish performance envelopes. Monte Carlo simulation models are generated to evaluate various maintenance, repair, and rehabilitation (MR and R) strategies possible over the life-cycle. The life-cycle cost associated with each scenario is computed, at different discount factors, to obtain the optimum life-cycle cost for various material options. The specifics of the model are illustrated through an example.

Impact of flood damaged critical infrastructure on communities and industries

Purpose – The purpose of this paper is to assess the severity of social and economic impact of floods on the communities and industries with respect to their reliance on the flood impacted critical infrastructure. This paper illustrates a severity assessment tool to determine the reduced serviceability level of critical infrastructure after a disaster, how the change in serviceability impacts activities of associated communities and industries, and the resulting social and economic impact.Design/methodology/approach – The results presented in this paper are a part of a larger research designed to develop a decision support system for disaster impact mitigation. This research evaluated the impact of floods as a natural hazard on infrastructure and the related industries and communities in terms of criticality and vulnerability of infrastructure and the severity of social and economic impact if the critical infrastructure were to be affected. The overall research focused on the 2008 Midwest floods for the r...

Exploratory Framework for Application of Analytics in the Construction Industry

AbstractThe complex dynamics inherent to the context of decision-making in the construction industry requires more rigorous application of analytics. However, effective frameworks to facilitate such data-driven decision-making are noticeably lacking in the construction industry. To address this lack, the Purdue Index for Construction (Pi-C) is introduced in this paper as a collaborative effort to facilitate and promote data-driven decision-making in the construction industry. As a preliminary step, a hierarchical definition for health of the construction industry is explored based on the results of a literature review, survey, and interviews. The developed hierarchical definition is then used to propose a framework to benchmark, interpret, and analyze data associated with the status of the health of the industry. The proposed framework is tested with existing publicly-available data to explore its effectiveness in improving decisions made in the form of policies or strategies. The research results highlig...

Disaster impact analysis based on inter‐relationship of critical infrastructure and associated industries

Purpose – Natural disasters, such as Hurricane Katrina (the most destructive natural calamity in US history), have destructive impact on residents, critical infrastructure, as well as, functions and services of associated industries in the affected areas. In addition, due to a lack of both understanding of natural disaster impacts and preparedness to the hurricane, it was revealed that the emergency‐related organizations were not prepared to maximize the use of the critical infrastructure to mitigate the impacts. The purpose of this paper is to help those organizations have more understanding of disaster impacts and facilitate their decision making in order to prepare better mitigation plans.Design/methodology/approach – A disaster impact mechanism and inter‐relationships based on the main functions of associated industries are derived through an extensive literature review and case analyses. Based on these inter‐relationships, a decision support system is developed and evaluated using a winter flood disa...

Social network analysis

Explores connections and patterns created by the aggregated interactions in Facebook pages during disaster responses.Analyzes social media data from the Facebook page of city of Baton Rouge during the 2016 Louisiana flood (Aug 12Dec 1, 2016).Analyzes social roles and key players using social network analysis.Study recommends actions to improve the effectiveness of information diffusion via social media. Social media, such as Twitter and Facebook, plays a critical role in disaster management by propagating emergency information to a disaster-affected community. It ranks as the fourth most popular source for accessing emergency information. Many studies have explored social media data to understand the networks and extract critical information to develop a pre- and post-disaster mitigation plan.The 2016 flood in Louisiana damaged more than 60,000 homes and was the worst U.S. disaster after Hurricane Sandy in 2012. Parishes in Louisiana actively used their social media to share information with the disaster-affected community e.g., flood inundation map, locations of emergency shelters, medical services, and debris removal operation. This study applies social network analysis to convert emergency social network data into knowledge. We explore patterns created by the aggregated interactions of online users on Facebook during disaster responses. It provides insights to understand the critical role of social media use for emergency information propagation. The study results show social networks consist of three entities: individuals, emergency agencies, and organizations. The core of a social network consists of numerous individuals. They are actively engaged to share information, communicate with the city of Baton Rouge, and update information. Emergency agencies and organizations are on the periphery of the social network, connecting a community with other communities. The results of this study will help emergency agencies develop their social media operation strategies for a disaster mitigation plan.

Vulnerability Assessment of Critical Infrastructure, Associated Industries, and Communities during Extreme Events

Critical infrastructure play an important role in functioning of industries and communities and also responding against natural disasters to reduce their impacts (i.e., routes and bridges for evacuation and public buildings for sheltering). Due to global warming, there is an increase in the frequency of extreme weather events which pose a high risk of functional and structural failure of critical infrastructure. Recent natural disasters (i.e., Hurricane Katrina, 2008 Midwest Flood, etc.) have exposed the vulnerability of critical infrastructure in the U.S. Therefore, it is important for the emergency-related agencies to identify and fortify the vulnerable critical infrastructure ahead of time to significantly reduce the potential damage due to floods. In this paper a decision support system (DSS) using Bayesian Network theory and System Dynamics Simulation method is presented for vulnerability assessment of critical infrastructure. This DSS has been developed to support emergency agencies and industries to prepare customized mitigation strategies and plans for preparedness, response, and recovery using the criticality and vulnerability analyses.

Integration of the Construction Knowledge and Expertise in Front-End Planning

AbstractTraditionally, construction input is integrated after the completion of the design stage of the projects. Inadequate construction input at the predesign stage and during the front-end planning (FEP) process results in fragility of plans in terms of constructability. This paper reports on a research to investigate construction input during the FEP process. The research is based on three questionnaire surveys as well as complementary case studies. Questionnaires1 and 2 were developed to assess the status of the FEP process and select areas that require construction input, respectively. Case studies were then selected from a pool of projects and collected data were analyzed to investigate barriers to construction input. Results of the surveys and case studies suggested that lack of well-established interorganizational frameworks within project organizations, as a loosely coupled network, hinders effective construction input. Based on the results, a user-friendly decision aid, a construction input ass...