Assessing Decision Making Strategies In Construction Management By Using A Schedule-Based Simulation Framework

During the project, managers encounter numerous contingencies and are faced with the challenging task of making decisions that will effectively keep the project on track. This task is very challenging because construction projects are non-prototypical and the processes are irreversible. Therefore, it is critical to apply a methodological approach to develop a few alternative management decision strategies during the planning phase, which can be deployed to manage alternative scenarios resulting from expected and unexpected disruptions in the as-planned schedule. Such a methodology should have the following features but are missing in the existing research: (1) looking at the effects of local decisions on the global project outcomes, (2) studying how a schedule responds to decisions and disruptive events because the risk in a schedule is a function of the decisions made, (3) establishing a method to assess and improve the management decision strategies, and (4) developing project specific decision strategies because each construction project is unique and the lessons from a particular project cannot be easily applied to projects that have different contexts. The objective of this dissertation is to develop a schedule-based simulation framework to design, assess, and improve sequences of decisions for the execution stage. The contribution of this research is the introduction of applying decision strategies to manage a project and the establishment of iterative methodology to continuously assess and improve decision strategies and schedules. The project managers or schedulers can implement the methodology to develop and identify schedules accompanied by suitable decision strategies to manage a project at the planning stage. The developed methodology also lays the foundation for an algorithm towards continuously automatically generating satisfactory schedule and strategies through the construction life of a project. Different from studying isolated daily decisions, the proposed framework introduces the notion of {em decision strategies} to manage construction process. A decision strategy is a sequence of interdependent decisions determined by resource allocation policies such as labor, material, equipment, and space policies. The schedule-based simulation framework consists of two parts, experiment design and result assessment. The core of the experiment design is the establishment of an iterative method to test and improve decision strategies and schedules, which is based on the introduction of decision strategies and the development of a schedule-based simulation testbed. The simulation testbed used is Interactive Construction Decision Making Aid (ICDMA). ICDMA has an emulator to duplicate the construction process that has been previously developed and a random event generator that allows the decision-maker to respond to disruptions in the emulation. It is used to study how the schedule responds to these disruptions and the corresponding decisions made over the duration of the project while accounting for cascading impacts and dependencies between activities. The dissertation is organized into two parts. The first part presents the existing research, identifies the departure points of this work, and develops a schedule-based simulation framework to design, assess, and improve decision strategies. In the second part, the proposed schedule-based simulation framework is applied to investigate specific research problems.

EVALUATING INFRASTRUCTURE PERFORMANCE TO ASSIST FACILITY MANAGEMENT TOWARD SUSTAINABLE SYSTEMS

Civil infrastructure provides essential services for the development of both society and economy. It is very important to manage systems efficiently to ensure sound performance. However, there are challenges in information extraction from available data, which also necessitates the establishment of methodologies and frameworks to assist stakeholders in the decision making process. This research proposes methodologies to evaluate systems performance by maximizing the use of available information, in an effort to build and maintain sustainable systems. Under the guidance of problem formulation from a holistic view proposed by Mukherjee and Muga, this research specifically investigates problem solving methods that measure and analyze metrics to support decision making. Failures are inevitable in system management. A methodology is developed to describe arrival pattern of failures in order to assist engineers in failure rescues and budget prioritization especially when funding is limited. It reveals that blockage arrivals are not totally random. Smaller meaningful subsets show good random behavior. Additional overtime failure rate is analyzed by applying existing reliability models and non-parametric approaches. A scheme is further proposed to depict rates over the lifetime of a given facility system. Further analysis of sub-data sets is also performed with the discussion of context reduction. Infrastructure condition is another important indicator of systems performance. The challenges in predicting facility condition are the transition probability estimates and model sensitivity analysis. Methods are proposed to estimate transition probabilities by investigating long term behavior of the model and the relationship between transition rates and probabilities. To integrate heterogeneities, model sensitivity is performed for the application of non-homogeneous Markov chains model. Scenarios are investigated by assuming transition probabilities follow a Weibull regressed function and fall within an interval estimate. For each scenario, multiple cases are simulated using a Monte Carlo simulation. Results show that variations on the outputs are sensitive to the probability regression. While for the interval estimate, outputs have similar variations to the inputs. Life cycle cost analysis and life cycle assessment of a sewer system are performed comparing three different pipe types, which are reinforced concrete pipe (RCP) and non-reinforced concrete pipe (NRCP), and vitrified clay pipe (VCP). Life cycle cost analysis is performed for material extraction, construction and rehabilitation phases. In the rehabilitation phase, Markov chains model is applied in the support of rehabilitation strategy. In the life cycle assessment, the Economic Input-Output Life Cycle Assessment (EIO-LCA) tools are used in estimating environmental emissions for all three phases. Emissions are then compared quantitatively among alternatives to support decision making.