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ItemA knowledge-based BIM exchange model for constructability assessment of commercial building designs(Georgia Institute of Technology, 2016-10-24) Zolfagharian, SamanehAt the early design stage of construction projects, designers often rely on general rules of thumb to make critical decisions about the geometry, construction systems, and materials used in their designs without fully evaluating the applicable construction requirements and constraints. However, ease of construction, or constructability, is a critical factor that is best examined at the early stage of construction projects when designs are the most amenable to change. Currently, reviewing a design’s constructability requires that designers spend a significant amount of time manually extracting constructability data from building models. Data extraction for constructability presents a challenging task, especially in large and complex projects, in which designers may neglect important data pertinent to, or extract unnecessary data from, their designs. The absence of a quantitative constructability model in the United States and a schema for extracting the necessary data for an automated constructability assessment of building designs motivated this study to develop a building information modeling-based constructability assessment exchange model. Through a comprehensive review of the literature, seventy-nine constructability attributes were first identified, which were then categorized into six groups using factor analysis based on 298 responses received from a questionnaire-based survey of industry professionals. Then using pairwise comparisons between constructability factors and common building systems used in the United States, a constructability assessment model was developed with the knowledge obtained from construction experts. Next, this study created a constructability exchange model (EM) using the United States National Building Information Modeling Standard™ approach to automate the data extraction required for the constructability assessment. The proposed EM identifies a reusable and consistent data set (e.g., geometry, object structures, relations, and properties) required for constructability assessment of building designs. The constructability EM was validated through an experiment based approach to examine if the model would help designers explore the constructability of designs in less time, assess the constructability of designs more accurately, and formalize the method of constructability assessment. We also validated the constructability EM using the IfcDoc application, so software vendors can use the EM to examine if their importers and exporters comply with the terminology and rule sets it defines. Moreover, domain experts can use it to validate their models to ensure they have all the required information for assessing constructability. Using the proposed constructability assessment model, designers can identify the tradeoffs involved in the constructability of various design alternatives and make informed decisions about any proposed changes. The constructability EM provides formal classifications of construction information that, when implemented, automates the repeated and time-consuming task of constructability assessment of designs.
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ItemSuccessful delivery of flash track projects(Georgia Institute of Technology, 2016-04-14) Austin, Robert BrendonThis research explores a higher order of fast tracking, called Flash Tracking, in response to increasing calls for faster, more reliable project deliveries. Flash Tracking is defined as a time-driven project, which by necessity requires a heightened degree of concurrency between engineering, procurement, and construction. In contrast to fast tracking, which entails a level of concurrency between engineering, procurement, and construction that has become a staple of the construction industry, Flash Tracking extends the envelope by requiring a series of innovative practices across the project delivery spectrum. The specific research questions pursued include: 1) identifying which innovative improvements in project delivery methodology could be made to compress project durations, while maintaining safety, quality, and risk tolerance, and 2) addressing how project teams can best overcome barriers to delivering shorter project durations. A multi-method research project was undertaken to address these questions, which entailed an extensive review of the literature, structured case study interviews, and multiple group decision-making exercises. The literature review focused on the construction industry, as well as manufacturing, shipbuilding, and software development, to identify practices and techniques potentially relevant to Flash Tracking that could be extended to the construction industry. Group decision-making exercises included a modified Delphi method study, an Analytic Hierarchy Process, and a series of research charrettes or focus groups. These studies produced a prioritized, two-tiered listing of 47 essential Flash Track practices, providing practitioners with both a measure to assess their readiness for undertaking a Flash Track project and strategies for increasing their readiness. A subsequent study--a semantic network analysis--refined and buttressed the research team’s earlier findings. This two-year study, conducted in concert with industry experts, led to a re-engineered engineering, procurement, and construction (EPC) model which embraces relational contract strategies, improved communications, and the early engagement of key stakeholders.
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ItemEvaluating supplier diversity development programs (SDDP) from the diverse supplier enterprise (DSE) perspective in the facility management industry(Georgia Institute of Technology, 2016-04-04) Hatcher, Michael B.Supplier diversity refers to the practice of creating opportunities for historically underutilized populations in the workforce and business arena. Supplier diversity encompasses initiatives specifically designed to increase the number of enterprises owned by people from ethnic minority groups who supply public, private, and/or voluntary sector organizations with goods and services (Ram & Smallbone, 2003). Supplier diversity initiatives were once driven solely by governmental policies focused on ethnic minorities. Also, minority vendor purchasing programs were designed to increase the volume of goods and services purchased by corporations from minority-owned businesses (Giunipero, 1981). Guided by the existing literature related to supplier diversity, this qualitative phenomenological study investigated the current state of Supplier Diversity Development Programs (SDDP) from the diverse supplier perspective. Primarily this research illuminated the (1) lived experiences of DSE Supplier Diversity Development Program participants (2) investigated the extent to which SDDPs eliminate or mitigate barriers/impediments to diverse suppliers previously identified in academic literature, and (3) evaluated the impact of SDDP participation on DSE business capacity development. This study explored and evaluated Supplier Diversity Development Programs to serve as a guide for (a) public and private POs in the facility management industry that currently utilize some supplier diversity development programs and (b) organizations seeking to implement SDDPs in the future. This research identified and posited a series of recommendations for the improvement of existing programs and the creation of new Supplier Diversity Development Programs. This research found that a Supplier Diversity Development Program that aligns program expectation with program delivery will result in greater levels of positive program participation outcomes. In addition this research study found SDDP mitigates DSE barriers/impediments and impacts DSE business capacity development, by way of building relationships, administering education, raising awareness, and creating platforms for access and engagement.
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ItemGeneralizable surrogate models for the improved early-stage exploration of structural design alternatives in building construction(Georgia Institute of Technology, 2016-01-15) Nourbakhsh, MehdiThe optimization of complex structures is extremely time consuming. To obtain their optimization results, researchers often wait for several hours and even days. Then, if they have to make a slight change in their input parameters, they must run their optimization problem again. This iterative process of defining a problem and finding a set of optimized solutions may take several days and sometimes several weeks. Therefore, to reduce optimization time, researchers have developed various approximation-based models that predict the results of time-consuming analysis. These simple analytical models, known as “meta- or surrogate models,” are based on data available from limited analysis runs. These “models of the model” seek to approximate computation-intensive functions within a considerably shorter time than expensive simulation codes that require significant computing power. One of the limitations of metamodels (or interchangeably surrogate models) developed for the structural approximation of trusses and space frames is lack of generalizability. Since such metamodels are exclusively designed for a specific structure, they can predict the performance of only the structures for which they are designed. For instance, if a metamodel is designed for a ten-bar truss, it cannot predict the analysis results of another ten-bar truss with different boundary conditions. In addition, they cannot be re-used if the topology of a structure changes (e.g., from a ten-bar truss to a 12-bar truss). If designers change the topology, they must generate new sample data and re-train their model. Therefore, the predictability of these exclusive models is limited. From a combination of the analysis of data from structures with various geometries, the objective of this study is to create, test, and validate generalizable metamodels that predict the results of finite element analysis. Developing these models requires two main steps: feature generation and model creation. In the first step, involving the use of 11 features for nodes and three for members, the physical representation of four types of domes, slabs, and walls were transformed into numerical values. Then, by randomly varying the cross-sectional area, the stress value of each member was recorded. In the second step, these feature vectors were used to create, test, and verify various metamodels in an examination of four hypotheses. The results of the hypotheses show that with generalizable metamodels, the analysis of data from various structures can be combined and used for predicting the performance of the members of structures or new structures within the same class of geometry. For instance, given the same radius for all domes, a metamodel generated from the analysis of data from a 700-, 980-, and 1,525-member dome can predict the structural performance of the members of these domes or a new dome with 250 members. In addition, the results show that generalizable metamodels are able to more closely predict the results of a finite element analysis than metamodels exclusively created for a specific structure. A case study was selected to examine the application of generalizable metamodels for the early-stage exploration of structural design alternatives in a construction project. The results illustrates that the optimization with generalizable metamodels reduces the time and cost of the project, fostering more efficient planning and more rapid decision-making by architects, contractors, and engineers at the early stage of construction projects.