Republic of Korea Army(ROKA) has been founding new attack helicopter troops since last year by adopting US main attack helicopter, AH-64E Apache, and peripheral system like pilots and mechanics training systems and their organization. The AH-64E Apache is a major attack helicopter of the US Army and all of its systems are verified in terms of the effectiveness in real operations for several decades. However, ROKA still needs their own version of systems including tactics, template, and maintenance which are suitable for Korean terrain, climate, personnel, and so on. At least ROKA needs to have a chance to verify that the adopted system is working well with different circumstances, especially with a different maintenance system. As basic characteristics, routine maintenance and management are essential for accident prevention for a helicopter, there are specially formalized maintenance systems for every kind of helicopter respectively. It was established by a manufacturer in maintenance manuals and can be modified and integrated by users and operators. Apache also has its own maintenance schedule and system including 25-hour, 50-hour, 125-hour, and 250-hour maintenance and inspections which are implemented according to the operation hours. Those schedules are done by a task force or temporary maintenance team which is led by one or two inspectors and supported by 3~4 mechanics. Maintenance troops restrict the number of aircraft to get in the process by managing the flight hours considering the limit of manpower and equipment so that the operation rate stays above at least 80%. It is important to stipulate their capacity in need and max capacity with given personnel and facility for newly founding military troops. Especially since ROKA aviation branch is applying a more strict maintenance process, it might cause insufficiency of resources if organized by same template and procedure with the US Army. The goal of this study is to verify if existing personnel organization is affordable for new maintenance system of AH-64 Apache helicopters. As a further step ahead, this research found the most critical personnel pool and their relationship by sensitivity analysis. This research specified actual maintenance procedure and restrictions on computer and simulated virtually. During the repetition of the test, existing organization was found inadequate to satisfy all restrictions and requirements. Test pilot and inspector pool are critical to secure the successful maintenance support and to prepare for contingency. Also, there were interesting relationships between the mechanics groups. They are in supplemental relationships with each other because of the condition of one pool affects the other.

Lean is a dynamic, knowledge-driven, and customer focused philosophy that continuously eradicates waste and generates value, with a goal to improve a company's productivity, efficiency, and quality. Successful implementation of lean does not only offer cost reduction and improved quality and productivity, but also provides efficient guidance for organizations to attain significant and continued growth. Although its adoption by companies has proven successful in developed countries, there is no sufficient evidence of its successful implementation in developing countries such as Saudi Arabia. A review of the literature indicates that there is a need to study lean transformation in developing countries as part of a comprehensive approach to their survival in the global economy. The purpose of this research is to develop a framework for a successful lean transformation in developing countries. The framework was developed by conducting a thorough literature review analysis and interviewing key personnel in ten local and eight multinational Saudi Arabian companies. The framework reacted to general data about lean transformation in developing countries, assessed a lean transformation level, and constructed the Interpretive Structure Molding (ISM) for barriers to achieve a successful lean transformation. Expert opinions were used for validation of the main components of this study, which are assessment, barriers, ISM and framework. Similar to the literature findings which indicated that the level of successful lean transformation in developing countries is low, the assessment revealed that the lean transformation level in local companies in Saudi Arabia is between 30% and 40%, and in multinational companies the level is between 50% and 60%. Both local and multinational companies in the case of Saudi Arabian industry considered lack of suppliers' involvement, lack of cooperation from suppliers, lack of good quality suppliers, and slow response to market due to demand fluctuations as the root barriers that need to be addressed at the primary stages of lean transformation. The resulting framework provides clear phases with an estimated timeline for each phase, from the foundation phase to the excellence level phase. In addition, it involves executive leaders and a cross-functional team to mentor and assess the transformation after each phase. The framework comprises several methods and tools that can be considered critical success factors for lean transformation, which will enable companies in developing countries to move toward achieving a successful lean transformation and sustainability, as well as reaching higher and persistent levels of growth.

Nuclear power plant disasters can have severe and far-reaching consequences, thus emergency managers and first responders from utility owners to the DoD must be prepared to respond to and mitigate effects protecting the public and environment from further damage. Rapidly emerging unmanned systems promise significant improvement in response and mitigation of nuclear disasters. Models and simulations (M&S) may play a significant role in improving readiness and reducing risks through its use in planning, analysis, preparation training, and mitigation rehearsal for a wide spectrum of derivate scenarios. Legacy nuclear reactor M&S lack interoperability between themselves and avatar or agent-based simulations of emergent unmanned systems. Bridging the gap between past and the evolving future, we propose a conceptual model (CM) using a System of System (SoS) approach, a simulation federation framework capable of supporting concurrent and interoperating live, virtual and constructive simulation (LVC), and demonstrate a prototypical implementation of an unmanned system intervention for nuclear power plant disaster using the constructive simulation component. The SoS CM, LVC simulation framework, and prototypical implementation are generalizable to other preparedness, response, and mitigation scenarios. The SoS CM broadens the current stovepipe reactor-based simulations to a system-of-system perspective. The framework enables distributed interoperating simulations with a network of legacy and emergent avatar and agent simulations. The unmanned system implementation demonstrates feasibility of the SoS CM and LVC framework through replication of selective Fukushima events. Further, the system-of-systems approach advances life cycle stages including concept exploration, system design, engineering, training, and mission rehearsal. Live, virtual, and constructive component subsystems of the CM are described along with an explanation of input/output requirements. Finally, applications to analysis and training, an evaluation of the SoS CM based on recently proposed criteria found in the literature, and suggestions for future research are discussed.

Internet of Things (IoT) is a new vision of an integrated network covering physical objects that are able to collect and exchange data. It enables previously unconnected devices and objects to become connected using equipping devices with communication technology such as sensors and radio frequency identification tags (RFID). As technology progresses towards new paradigm such as IoT, there is a need for an approach to identify the significance of these projects. Conventional simulation modeling and data analysis approaches are not able to capture the system complexity or suffer from a lack of data needed that can help to build a prediction. Agent-based Simulation (ABM) proposes an efficient simulation scheme to capture the structure of this dimension and offer a potential solution. Two case studies were proposed in this research. The first one introduces a conceptual case study addressing the use of agent-based simulations to verify the effectiveness of the business model of IoT. The objective of the study is to assess the feasibility of such application, of the market in the city of Orlando (Florida, United States). The second case study seeks to use ABM to simulate the operational behavior of refrigeration units (7,420) in one of largest retail organizations in Saudi Arabia and assess the economic feasibility of IoT implementation by estimating the return on investment (ROI).

With advancement in technology, building structures are becoming bigger and more complex. Incidences of horrifying fires that occur in such complex structures resulting in loss of property as well as lives are recorded worldwide. Emergency evacuation training can play a crucial role in mitigating damage not only in cases of fire, explosion or chemical spill but also in cases of natural calamities like floods and hurricanes. Conventional safety training provided in industries mostly comprises of unidirectional flow of information. Due to this passive learning style, response of employees in real life emergency situations is known to be ineffective. The proposed research focuses on the development of virtual emergency evacuation safety training for residents, workers and employees. This research developed a 3 dimensional (3D) virtual fire safety and emergency evacuation training for building occupants. A 3D model of a real engineering college building in the University of Central Florida (UCF) was developed in a virtual world and participants could interact with various objects and scenarios in this virtual building on a standard desktop computer using keyboard and mouse. Expert interviews and literature review were utilized to develop contents of fire safety and emergency evacuation training. Also, a slide based fire safety and emergency evacuation training was developed based on same contents and made available through a website. An effort was made to develop both trainings- virtual and slide based to be comparable in terms of contents. A case study with two sets of experiments comprising of 143 participants from UCF community was conducted to understand factors such as fidelity, simulation sickness, engagement and effectiveness of 3D virtual and slide based fire safety and emergency evacuation training. Results of fidelity and simulation sickness validated use of 3D virtual training for training building residents on fire safety and emergency evacuation. Data analysis of knowledge tests allowed to compare short terms and long term effectiveness of 3D virtual training and slide based training. To further understand engagement, physiological measure- electroencephalograph (EEG) of 40 healthy participants was recorded in second set of experiments. Ratio of Beta and Alpha frequency bands was studied to understand attention paid by trainees in 3D virtual and slide based training.

The human brain processes vital information regarding human feelings. Prior research has focused on the problems of underage bullying, workplace bullying, burnout, mobbing and, most recently, cyberbullying. Scholars have traditionally examined the adverse outcomes of cyberbullying using subjective measures of stress and emotion for decades. However, very few studies examined cyberbullying using objective measures like EEG. The main goal of this study was to explore the relationship between the brain's EEG, expressed by the power spectral density, and emotions and stress due to two types of cyberbullying, specifically: 1) social exclusion, and 2) verbal harassment. This research also examined how cyberbullying factors of social interaction and publicity affect the emotional and stress responses. EEG data were collected from twenty-nine undergraduate students, aged 18-22, using 10/5 EEG system with 64 channels. Each cyberbullying experimental condition was treated as an independent study. The first study investigated the effects of social exclusion on EEG activity and the related emotional and stress factors while playing a virtual ball-tossing game known as cyberball. EEG results showed significant differences in alpha and beta power in the right posterior brain regions due to social exclusion. There were also significant differences in beta and gamma power in the left anterior brain regions due to social exclusion. The results suggest that EEG activity in the left anterior brain region may be important to identify social exclusion. The second study utilized a hypothetical scenario presented as impolite or complimentary online comments. EEG results showed marginally significant differences in gamma power at right- and left- anterior and midline brain regions due to verbal harassment. The results suggest that changes in gamma power at anterior brain regions might play an essential role in the processing of verbal harassment information. Self-reported measures confirmed that verbal harassment was more distressing than social exclusion.

Industry 4.0 is a complex concept that is not clearly understood by companies and most of the organizations' managers. While the uncertainty about the outcomes and the maturity and ability of the companies become challenges, there is a need for strategic guidance, detailed roadmaps, and implementation processes. The management is saddled with the training of people for efficient cyber-physical collaboration between people and the systems, with operations that require a creative process and sensors for monitoring and control. The Thesis presents a framework for industry 4.0 through which management can understand the challenges that stemmed from this technological change. The strategic problems and solutions that will promote the conversion of both small and medium scale industries from the existing platform into the new platform is presented and the findings in this thesis will help manufacturing and business organizations to reengineer their operational processes, industrial assets, energy requirements and use, and employees' skill acquisitions toward Industry 4.0. As the management devotes time and resources to manage this transition, this thesis outlines strategies and approaches that will enable them to achieve global competitiveness in the new technological and big-data environment. This thesis proposes a conceptual framework of Industry 4.0 with respect to design principles, technology roadmap to guide the managers of how to set the Digital strategies, select the key technologies and talents to match.

Despite the nearly universal imperative to continuously improve processes, Shewhart-stable time series are often ignored for improvement because of various generalized assumptions and "rules", many of which are actually very context dependent. The process control literature presents widely divergent views, including the extreme position that stable processes are completely random and therefore any further compensation ("tampering") can only increase process variability. The traditional reductionist approach to process improvement characterizes underlying factors using statistical variance measures, which has been very effective for unstable processes. However, this approach, especially when it involves Shewhart control charts, is generally much less effective for directing the improvement of stable time series, often resulting in a transition to passive monitoring to await a special cause of variation. A model-free strategy founded upon information theoretic quantifiers was researched to instead develop an emergence-based perspective for stable process improvement. Jensen-Shannon complexity was mapped temporally with permutation entropy to reveal structural patterns of order that could direct further improvement, challenging the notion of tampering. Stable processes disclosed informative nonrandom structure corresponding with relative degrees of randomness, also challenging the notion of a constant system of "chance causes." In the future, similar emergence-based methods could provide a useful supplement to reductionist methods during the improvement of virtually all types of processes.

Augmented Reality (AR) projects a virtual overlay onto real space so that the user can see a superimposed image over the real-world background. Although AR has advanced recently and a breadth of applications can be found in practice, they are focused on simple tasks with few examples of more complex work tasks. One area that could benefit from advancing AR technology is operations management, specifically operational performance measurement (OPM); however, a brief review of the literature reveals that this potential application area has not yet been explored. Therefore, the purpose of this work is to investigate the application of AR technology to OPM to improve real-time decision-making and management practice. A systematic literature review was conducted to evaluate the current application areas related to management practices. This review did not identify any studies related to using AR to support OPM, but did identify many applications relevant to management activities that empirically demonstrate the benefit of adoption. The review analyzed the current development in this research area and how it has matured including evaluating the applications discussed in the identified publications to demonstrate the existing gap in the research related to OPM applications. An expert study was then conducted to explore potential challenges and benefits of such a device as well as to operationally define effective decision-making for operations managers. The results of the expert study were leveraged to develop a Design of Experiments based laboratory study to empirically test the effects of an AR supported environment on decision-making effectiveness and operational performance. The results showed that the AR device supported improved operational performance, but did not show a significant effect on participants' perceived decision-making effectiveness. This study contributes to the academic literature on technology-enabled OPM and managerial decision-making as well as providing insights for industry professionals interested in adopting AR to support management functions.

With the rise of human-agent teaming (HAT), a new cycle of scientific discovery commenced. Through scientific discovery, a number of theories of constructs in HAT were developed, however, an overarching model is lacking that elucidates the relative importance of these constructs in relation to human performance. The main objective of this research was to develop a model of simulated military HAT and to validate it against selected empirical data. Experimental data borrowed from four simulated military HAT studies were used to test the proposed Core model. The Core model was assumed to be directly affecting task performance and consisted of constructs related to Task Composition, Task Perception, and the qualities that each team member (Human/Agent Qualities) brings to the team. The available experimental data were tested against the null model: everything, within and between these Core sections, are equal contributors to hit rate. Furthermore, in order to validate the Core model, a validation approach was developed based on relative importance, wherein the outcome was a proportional value and followed a beta distribution (Ferrari & Cribari-Neto, 2004). This new modeling approach consisted of (1) application of dominance analysis (DA; Azen & Budescu, 2003; Budescu, 1993) to determine the most important contributors to task performance, (2) establishing robustness and generalizability of the dominance outcome through bootstrap procedures (Azen & Budescu, 2003; Efron, 1981), and (3) combining the dominant predictors into a full beta regression model to evaluate the fit and significance of the model (Ferrari & Cribari-Neto, 2004). DA of all four experimental studies examined in this research led to rejecting the null hypotheses. Constructs in the proposed Core model were not equally important to performance in these simulated military HAT studies. Results showed consistently similar yet different dominance patterns in relation to human performance. Attempts were made to elucidate the most important predictors of task performance. Analyses unveiled the importance of taking task difficulty into consideration when assessing the relative importance within the proposed Core model.