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- All Subjects: Civil Engineering
Description
Semiconductor manufacturing facilities are very complex and capital intensive in nature. During the lifecycle of these facilities various disciplines come together, generate and use a tremendous amount of building and process information to support various decisions that enable them to successfully design, build and sustain these advanced facilities. However, a majority of the information generated and processes taking place are neither integrated nor interoperable and result in a high degree of redundancy. The objective of this thesis is to build an interoperable Building Information Model (BIM) for the Base-Build and Tool Installation in a semiconductor manufacturing facility. It examines existing processes and data exchange standards available to facilitate the implementation of BIM and provides a framework for the development of processes and standards that can help in building an intelligent information model for a semiconductor manufacturing facility. To understand the nature of the flow of information between the various stakeholders the flow of information between the facility designer, process tool manufacturer and tool layout designer is examined. An information model for the base build and process tool is built and the industry standards SEMI E6 and SEMI E51 are used as a basis to model the information. It is found that applications used to create information models support interoperable industry standard formats such as the Industry Foundation Classes (IFC) and ISO 15926 in a limited manner. A gap analysis has revealed that interoperability standards applicable to the semiconductor manufacturing industry such as the IFC and ISO15926 need to be expanded to support information transfers unique to the industry. Information modeling for a semiconductor manufacturing facility is unique in that it is a process model (Process Tool Information Model) within a building model (Building Information Model), each of them supported more robustly by different interoperability standards. Applications support interoperability data standards specific to the domain or industry they serve but information transfers need to occur between the various domains. To facilitate flow of information between the different domains it is recommended that a mapping of the industry standards be undertaken and translators between them be developed for business use.
ContributorsPindukuri, Shruthi (Author) / Chasey, Allan D (Thesis advisor) / Wiezel, Avi (Committee member) / Mamlouk, Michael (Committee member) / Arizona State University (Publisher)
Created2011
Description
The wood-framing trade has not sufficiently been investigated to understand the work task sequencing and coordination among crew members. A new mental framework for a performing crew was developed and tested through four case studies. This framework ensured similar team performance as the one provided by task micro-scheduling in planning software. It also allowed evaluation of the effect of individual coordination within the crew on the crew's productivity. Using design information, a list of micro-activities/tasks and their predecessors was automatically generated for each piece of lumber in the four wood frames. The task precedence was generated by applying elementary geometrical and technological reasoning to each frame. Then, the duration of each task was determined based on observations from videotaped activities. Primavera's (P6) resource leveling rules were used to calculate the sequencing of tasks and the minimum duration of the whole activity for various crew sizes. The results showed quick convergence towards the minimum production time and allowed to use information from Building Information Models (BIM) to automatically establish the optimal crew sizes for frames. Late Start (LS) leveling priority rule gave the shortest duration in every case. However, the logic of LS tasks rule is too complex to be conveyed to the framing crew. Therefore, the new mental framework of a well performing framer was developed and tested to ensure high coordination. This mental framework, based on five simple rules, can be easily taught to the crew and ensures a crew productivity congruent with the one provided by the LS logic. The case studies indicate that once the worst framer in the crew surpasses the limit of 11% deviation from applying the said five rules, every additional percent of deviation reduces the productivity of the whole crew by about 4%.
ContributorsMaghiar, Marcel M (Author) / Wiezel, Avi (Thesis advisor) / Mitropoulos, Panagiotis (Committee member) / Cooke, Nancy J. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Front end planning (FEP) is an essential and valuable process that helps identify risks early in the capital project planning phases. With effective FEP, risks can potentially be mitigated through development of detailed scope definition and subsequent efficient project resource use. The thesis describes the FEP process that has been developed over the past twenty years by the Construction Industry Institute (CII). Specifically, it details the FEP tools developed for early project planning and the data gathered to analyze the tools used within the CII community. Data from a March 2011 survey are given showing the tools commonly used, how those tools are used and the common barriers faced that prohibit successful FEP implementation. The findings from in-depth interviews are also shared in the thesis. The interviews were used to gather detail responses from organizations on the implementation of their FEP processes. In total, out of the 116 CII organizations, 59 completed the survey and over 75 percent of the respondents used at least one CII tool in their front end planning processes. Of the 59 survey respondents, 12 organizations participated in the in-depth interviews. The thesis concludes that CII organizations continue to find value in CII FEP tools due to the increase tool usage. Also the thesis concludes that organizations must have strong management commitment, smart succession planning and a standardized planning process to increase the likelihood of successful FEP strategies.
ContributorsBosfield, Roberta Patrice (Author) / Gibson, G.Edward (Thesis advisor) / Wiezel, Avi (Committee member) / Ernzen, James (Committee member) / Arizona State University (Publisher)
Created2012
Description
Design is widely accepted as a factor that affects construction work. Although knowledge about this effect will contribute to the improvement of construction practice, this is very limited. No study has been focused on establishing how the effect of design on construction work can be evaluated. The primary objective of this research was to formulate an approach enabling the assessment of the effect of building design on construction work. To achieve this, a quantitative index based on field data, termed the 'index of difficulty,' was established. Given a construction activity, this index relates the effective work effort per unit of output expended in completing a construction part under two distinct designs: one under evaluation and the other designated as the base design for common comparison. The greater the index of difficulty associated with a design, the higher the required work effort, consequently resulting in a greater affect of the design on construction work.
Multiple ways of utilizing the index of difficulty to assess the effect of building design on construction activities are suggested. Additionally, application cases are exhibited to illustrate the implementation of the proposed approach and the required computations.
ContributorsChang, Luis Gerardo (Author) / Wiezel, Avi (Thesis advisor) / Sullivan, Kenneth (Committee member) / Ayer, Steven (Committee member) / Arizona State University (Publisher)
Created2023
Description
The success or failure of projects is not determined only by procedures, tasks, and technologies, but also by the project team and its effectiveness. In order to lead project teams towards successful outcomes, project managers must maintain high quality relationships in the workplace. When looking at employees’ relationships in the workplace, Social Exchange Theory introduces two types of exchanges: employee-organization and leader-member exchanges. While both types of exchanges focus exclusively on the employee’s longitudinal relationships, the interpersonal relationships among the team members are usually overlooked.
This research presents the results of a quantitative study of the interpersonal relationships of 327 project managers and assistant project managers in their workplace. Specifically, the study investigates if the quality of the relationship with particular stakeholders, such as one’s immediate supervisor (boss), peers, or subordinates, drives the individual’s quality of the relationship with other stakeholders.
Contrary to the expectations, in strictly hierarchical organizations (one direct supervisor), there is no significant correlation between the quality of relationships with the boss and the overall quality of the individual’s relationships. However, in the case of matrix organizations (two or three bosses), there are significant correlations between several variables such as the quality of the relationship, perceived importance and the time spent with each stakeholder, as well the inclination of the participant towards leadership actions. The driving relationship in matrix organizations is the one with “the most important peer”.
This research presents the results of a quantitative study of the interpersonal relationships of 327 project managers and assistant project managers in their workplace. Specifically, the study investigates if the quality of the relationship with particular stakeholders, such as one’s immediate supervisor (boss), peers, or subordinates, drives the individual’s quality of the relationship with other stakeholders.
Contrary to the expectations, in strictly hierarchical organizations (one direct supervisor), there is no significant correlation between the quality of relationships with the boss and the overall quality of the individual’s relationships. However, in the case of matrix organizations (two or three bosses), there are significant correlations between several variables such as the quality of the relationship, perceived importance and the time spent with each stakeholder, as well the inclination of the participant towards leadership actions. The driving relationship in matrix organizations is the one with “the most important peer”.
ContributorsK. Jamali, M. Hossein (Author) / Wiezel, Avi (Thesis advisor) / Sullivan, Kenneth T. (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2019
Description
Implementing Building Information Modeling (BIM) in construction projects has many potential benefits, but issues of projects can hinder its realization in practice. Although BIM involves using the technology, more than four-fifths of the recurring issues in current BIM-based construction projects are related to the people and processes (i.e., the non-technological elements of BIM). Therefore, in addition to the technological skills required for using BIM, educators should also prepare university graduates with the non-technological skills required for managing the people and processes of BIM. This research’s objective is to develop a learning module that teaches the non-technological skills for addressing common, people- and process-related, issues in BIM-based construction projects. To achieve this objective, this research outlines the steps taken to create the learning module and identify its impact on a BIM course. The contribution of this research is in the understanding of the pedagogical value of the developed problem-based learning module and documenting the learning module’s development process.
ContributorsAbdul Rahman, Abdul Rahimi Bin (Author) / Ayer, Steven K (Thesis advisor) / Tang, Pingbo (Committee member) / Wiezel, Avi (Committee member) / Arizona State University (Publisher)
Created2018
Description
Planning efforts conducted during the early stages of a construction project, known
as front end planning (FEP), have a large impact on project success and significant
influence on the configuration of the final project. As a key component of FEP, front end
engineering design (FEED) plays an essential role in the overall success of large industrial
projects. The primary objective of this dissertation focuses on FEED maturity and accuracy
and its impact on project performance. The author was a member of the Construction
Industry Institute (CII) Research Team (RT) 331, which was tasked to develop the FEED
Maturity and Accuracy Total Rating System (FEED MATRS), pronounced “feed matters.”
This dissertation provides the motivation, methodology, data analysis, research findings
(which include significant correlations between the maturity and accuracy of FEED and
project performance), applicability and contributions to academia and industry. A scientific
research methodology was employed in this dissertation that included a literature review,
focus groups, an industry survey, data collection workshops, in-progress projects testing,
and statistical analysis of project performance. The results presented in this dissertation are
based on input from 128 experts in 57 organizations and a data sample of 33 completed
and 11 on-going large industrial projects representing over $13.9 billion of total installed
cost. The contributions of this work include: (1) developing a tested FEED definition for
the large industrial projects sector, (2) determining the industry’s state of practice for
measuring FEED deliverables, (3) developing an objective and scalable two-dimensional
method to measure FEED maturity and accuracy, and (4) quantifying that projects with
high FEED maturity and accuracy outperformed projects with low FEED maturity and
accuracy by 24 percent in terms of cost growth, in relation to the approved budget.
as front end planning (FEP), have a large impact on project success and significant
influence on the configuration of the final project. As a key component of FEP, front end
engineering design (FEED) plays an essential role in the overall success of large industrial
projects. The primary objective of this dissertation focuses on FEED maturity and accuracy
and its impact on project performance. The author was a member of the Construction
Industry Institute (CII) Research Team (RT) 331, which was tasked to develop the FEED
Maturity and Accuracy Total Rating System (FEED MATRS), pronounced “feed matters.”
This dissertation provides the motivation, methodology, data analysis, research findings
(which include significant correlations between the maturity and accuracy of FEED and
project performance), applicability and contributions to academia and industry. A scientific
research methodology was employed in this dissertation that included a literature review,
focus groups, an industry survey, data collection workshops, in-progress projects testing,
and statistical analysis of project performance. The results presented in this dissertation are
based on input from 128 experts in 57 organizations and a data sample of 33 completed
and 11 on-going large industrial projects representing over $13.9 billion of total installed
cost. The contributions of this work include: (1) developing a tested FEED definition for
the large industrial projects sector, (2) determining the industry’s state of practice for
measuring FEED deliverables, (3) developing an objective and scalable two-dimensional
method to measure FEED maturity and accuracy, and (4) quantifying that projects with
high FEED maturity and accuracy outperformed projects with low FEED maturity and
accuracy by 24 percent in terms of cost growth, in relation to the approved budget.
ContributorsYussef, Abdulrahman (Author) / Gibson, Jr., G. Edward (Thesis advisor) / El Asmar, Mounir (Thesis advisor) / Bearup, Wylie (Committee member) / Wiezel, Avi (Committee member) / Arizona State University (Publisher)
Created2019
Description
Owner organizations in the architecture, engineering, and construction (AEC) industry are presented with a wide variety of project delivery approaches. Implementation of these approaches, while enticing due to their potential to save money, reduce schedule delays, or improve quality, is extremely difficult to accomplish and requires a concerted change management effort. Research in the field of organizational behavior cautions that perhaps more than half of all organizational change efforts fail to accomplish their intended objectives. This study utilizes an action research approach to analyze change message delivery within owner organizations, model owner project team readiness and adoption of change, and identify the most frequently encountered types of resistance from lead project members. The analysis methodology included Spearman's rank order correlation, variable selection testing via three methods of hierarchical linear regression, relative weight analysis, and one-way ANOVA. Key findings from this study include recommendations for communicating the change message within owner organizations, empirical validation of critical predictors for change readiness and change adoption among project teams, and identification of the most frequently encountered resistive behaviors within change implementation in the AEC industry. A key contribution of this research is the recommendation of change management strategies for use by change practitioners.
ContributorsLines, Brian (Author) / Sullivan, Kenneth (Thesis advisor) / Wiezel, Avi (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2014
Description
Resilient acquisition of timely, detailed job site information plays a pivotal role in maintaining the productivity and safety of construction projects that have busy schedules, dynamic workspaces, and unexpected events. In the field, construction information acquisition often involves three types of activities including sensor-based inspection, manual inspection, and communication. Human interventions play critical roles in these three types of field information acquisition activities. A resilient information acquisition system is needed for safer and more productive construction. The use of various automation technologies could help improve human performance by proactively providing the needed knowledge of using equipment, improve the situation awareness in multi-person collaborations, and reduce the mental workload of operators and inspectors.
Unfortunately, limited studies consider human factors in automation techniques for construction field information acquisition. Fully utilization of the automation techniques requires a systematical synthesis of the interactions between human, tasks, and construction workspace to reduce the complexity of information acquisition tasks so that human can finish these tasks with reliability. Overall, such a synthesis of human factors in field data collection and analysis is paving the path towards “Human-Centered Automation” (HCA) in construction management. HCA could form a computational framework that supports resilient field data collection considering human factors and unexpected events on dynamic job sites.
This dissertation presented an HCA framework for resilient construction field information acquisition and results of examining three HCA approaches that support three use cases of construction field data collection and analysis. The first HCA approach is an automated data collection planning method that can assist 3D laser scan planning of construction inspectors to achieve comprehensive and efficient data collection. The second HCA approach is a Bayesian model-based approach that automatically aggregates the common sense of people from the internet to identify job site risks from a large number of job site pictures. The third HCA approach is an automatic communication protocol optimization approach that maximizes the team situation awareness of construction workers and leads to the early detection of workflow delays and critical path changes. Data collection and simulation experiments extensively validate these three HCA approaches.
Unfortunately, limited studies consider human factors in automation techniques for construction field information acquisition. Fully utilization of the automation techniques requires a systematical synthesis of the interactions between human, tasks, and construction workspace to reduce the complexity of information acquisition tasks so that human can finish these tasks with reliability. Overall, such a synthesis of human factors in field data collection and analysis is paving the path towards “Human-Centered Automation” (HCA) in construction management. HCA could form a computational framework that supports resilient field data collection considering human factors and unexpected events on dynamic job sites.
This dissertation presented an HCA framework for resilient construction field information acquisition and results of examining three HCA approaches that support three use cases of construction field data collection and analysis. The first HCA approach is an automated data collection planning method that can assist 3D laser scan planning of construction inspectors to achieve comprehensive and efficient data collection. The second HCA approach is a Bayesian model-based approach that automatically aggregates the common sense of people from the internet to identify job site risks from a large number of job site pictures. The third HCA approach is an automatic communication protocol optimization approach that maximizes the team situation awareness of construction workers and leads to the early detection of workflow delays and critical path changes. Data collection and simulation experiments extensively validate these three HCA approaches.
ContributorsZhang, Cheng (Author) / Tang, Pingbo (Thesis advisor) / Cooke, Nancy J. (Committee member) / Chong, Oswald (Committee member) / Arizona State University (Publisher)
Created2017
Description
Interpersonal communications during civil infrastructure systems operation and maintenance (CIS O&M) are processes for CIS O&M participants to exchange critical information. Poor communications that provide misleading information can jeopardize CIS O&M safety and efficiency. Previous studies suggest that communication contexts and features could be indicators of communication errors and relevant CIS O&M risks. However, challenges remain for reliable prediction of communication errors to ensure CIS O&M safety and efficiency. For example, existing studies lack a systematic summarization of risky contexts and features of communication processes for predicting communication errors. Limited studies examined quantitative methods for incorporating expert opinions as constraints for reliable communication error prediction. How to examine mitigation strategies (e.g., adjustments of communication protocols) for reducing communication-related CIS O&M risks is also challenging. The main reason is the lack of causal analysis about how various factors influence the occurrences and impacts of communication errors so that engineers lack the basis for intervention.
This dissertation presents a method that integrates Bayesian Network (BN) modeling and simulation for communication-related risk prediction and mitigation. The proposed method aims at tackling the three challenges mentioned above for ensuring CIS O&M safety and efficiency. The proposed method contains three parts: 1) Communication Data Collection and Error Detection – designing lab experiments for collecting communication data in CIS O&M workflows and using the collected data for identifying risky communication contexts and features; 2) Communication Error Classification and Prediction – encoding expert knowledge as constraints through BN model updating to improve the accuracy of communication error prediction based on given communication contexts and features, and 3) Communication Risk Mitigation – carrying out simulations to adjust communication protocols for reducing communication-related CIS O&M risks.
This dissertation uses two CIS O&M case studies (air traffic control and NPP outages) to validate the proposed method. The results indicate that the proposed method can 1) identify risky communication contexts and features, 2) predict communication errors and CIS O&M risks, and 3) reduce CIS O&M risks triggered by communication errors. The author envisions that the proposed method will shed light on achieving predictive control of interpersonal communications in dynamic and complex CIS O&M.
This dissertation presents a method that integrates Bayesian Network (BN) modeling and simulation for communication-related risk prediction and mitigation. The proposed method aims at tackling the three challenges mentioned above for ensuring CIS O&M safety and efficiency. The proposed method contains three parts: 1) Communication Data Collection and Error Detection – designing lab experiments for collecting communication data in CIS O&M workflows and using the collected data for identifying risky communication contexts and features; 2) Communication Error Classification and Prediction – encoding expert knowledge as constraints through BN model updating to improve the accuracy of communication error prediction based on given communication contexts and features, and 3) Communication Risk Mitigation – carrying out simulations to adjust communication protocols for reducing communication-related CIS O&M risks.
This dissertation uses two CIS O&M case studies (air traffic control and NPP outages) to validate the proposed method. The results indicate that the proposed method can 1) identify risky communication contexts and features, 2) predict communication errors and CIS O&M risks, and 3) reduce CIS O&M risks triggered by communication errors. The author envisions that the proposed method will shed light on achieving predictive control of interpersonal communications in dynamic and complex CIS O&M.
ContributorsSun, Zhe (Author) / Tang, Pingbo (Thesis advisor) / Ayer, Steven K (Committee member) / Cooke, Nancy J. (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2020