Operations Research, Systems Engineering and Industrial Engineering Commons^™

Modeling And Integration Method Of Sysml Model For Complex Business Scenarios, Bing Yu, Baoran An, Shicao Zhao

Journal of System Simulation

Abstract: The development process of complex equipment involves multi-stage business processes, multi-level product architecture, and multi-disciplinary physical processes. The relationship between its system model and various disciplinary models is extremely complicated. In the modeling and integration process, extensive customized development is needed to realize model integration and interoperability in different business scenarios. Meanwhile, the differences in modeling and interaction between different modeling tools make it difficult to support the consistent representation of models in complex scenarios. To improve the efficiency of system modeling and integration in complex business scenarios, a system modeling and integration method was proposed. This method took …

Algorithm And Semi-Physical System Simulation For Command Intent Recognition Of Uav In Low-Resource Environment, Hongfu Liu, Yajing Fu, Wanpeng Zhang, Hu Zhang

Journal of System Simulation

Abstract: When a communication network is partially disabled or disrupted, an UAV is plunged into a "low-resource environment" and must rely on local hardware resources. This situation imposes constraints on computing power, storage capacity, and energy availability. To address the need for command intent recognition in such environments, a semi-physical simulation system for UAV in emergency rescue operations has been designed and implemented. Based on the low resource airborne hardware in the loop, the system simulates UAV command intention recognition and mission planning through GIS+BIM 3D environment modeling task scenarios. A new lightweight algorithm for intent recognition has been proposed, …

Uav Swarm Obstacle Avoidance Based On Visual Filed And Adaptive Radius, Gaohang Ai, Chuntao Li

Journal of System Simulation

Abstract: Aiming at the obstacle avoidance problem of large-scale UAV swarm tracking flight route, a swarm obstacle avoidance algorithm based on distributed model predictive control combined with visual field and adaptive obstacle avoidance radius is proposed. In the process of swarm flight, the UAV obtains the reference route information of the current moment according to its own position, and obtains the predicted trajectory of its neighbors through local information interaction. When encountering obstacles, the adaptive obstacle avoidance radius and field of view topology method are combined to effectively solve the problem that the internal safety distance cannot be maintained and …

A Novel Research Pattern For The Simulation Of Complex Systems Sigd, Bin Chen, Runkang Guo, Zhengqiu Zhu, Yong Zhao, Yatai Ji, Aiguo Chen, Guangquan Cheng

Journal of System Simulation

Abstract: The complexity of the system is mainly reflected in the numerous components and extremely complex interactions. Combined with the current trend of artificial intelligence development, this paper analyzes and considers the changes in thinking mode brought by simulation discipline research, and forms an understanding of the connotation and research scope of simulation intelligence. A new pattern for complex system simulation research is proposed: "simulation intelligence based generating decisions (SIGD)". In the SIGD pattern, the similar principles, modeling methods, and decision-guiding modes in simulation disciplines are different from those in traditional simulation. Under the guidance of this concept, a connection-oriented …

Harmonic Impedance Modeling And Oscillation Analysis Of Modular Multilevel Converter, Yuhong Wang, Wensheng Chen, Shilin Gao, Jianquan Liao, Yangfan Cheng

Journal of System Simulation

Abstract: To facilitate rapid analysis of the oscillation stability mechanism in modular multilevel converter-based high voltage direct current (MMC-HVDC) systems and streamline the simulation process for determining MMC impedance characteristics, a simplified mathematical simulation model for MMC closed-loop impedance is developed using the harmonic state space method. This model considers various control strategies and includes both AC-side and DC-side impedance models. By applying a Nyquist criterion-based impedance analysis method, the stability mechanisms on the AC and DC sides of the MMC are examined. In addition, a data-driven oscillation stability analysis method is also proposed, leveraging a global sensitivity algorithm based …

Optimal Operation Scheduling Of Integrated Energy System Considering Energy Priority, Dongli Jia, Keyan Liu, Zhaoying Ren, Zezhou Wang, Dongsheng Tang

Journal of System Simulation

Abstract: Integrated with the actual situation of power grid and the growth of new energy, a multiobjective model for optimal scheduling of the integrated energy system(IES) is established based on the analysis of the energy-flow relationship of the IES and taking into account the priority of energy utilization and the load demand response in terms of the mismatch between the distributed energy sources and the loads, the net benefit of the unit cost of the IES, and the load response degree. Combined with the equipment and the environmental benefits system, a priority constraint for energy utilization has been established for …

Research On Scheduling Strategies Simulation For Building Air-Conditioning Systems Based On Transfer Imitation Learning, Qiaochu Wang, Yan Ding, Chuanzhi Liang, Haozheng Zhang, Chen Huang

Journal of System Simulation

Abstract: To solve the problem of unstable performance and inefficient training process of low-quality data conditions at the initial stage of online deployment of air conditioner scheduling, we propose a migration-imitation learning-based air conditioning scheduling strategy simulation method. Reinforcement learning methods are used to generate building operation strategies. A standard building simulation model serves as the source domain, upon which migration learning is applied. An imitation learning loss function is incorporated into the intelligent loss function to enhance algorithm performance. The results indicate that, compared with the non-use of migration learning, the proposed method can improve the operational efficiency by …

Behavioral Modeling Of Manned-Unmanned Cooperative Air Combat Based On Improved Abc Algorithm, Peng Wang, Haoyu Liu, Ni Li, Zexi Yu, Shangjie Jia

Journal of System Simulation

Abstract: To solve the problem of difficulty in establishing collaborative behavior models and weak adversarial capabilities in typical MAV/UAV air combat scenarios, a mixed decision based MAV/UAV behavior modeling framework is proposed. Using collaborative rule sets, rule subsets, tactical action sets, and other tools, a hierarchical decision collaborative behavior model supporting five types of collaborative tactics, including grinding tactics and unilateral flanking tactics, is constructed in this framework. a behavior model parameter optimization method based on an improved artificial bee colony (ABC) algorithm is proposed. By using the Mason rotation method to initialize the population, a better initial honey source …

Path Planning Of Desert Robot Based On Deep Reinforcement Learning, Ming Li, Wangzhong Ye, Jiehua Yan

Journal of System Simulation

Abstract: Due to the complexity and variability of the desert environment, the key to the high-efficient of mobile robot is how to avoid obstacles and plan its path. To solve the problems of poor search efficiency and slow convergence of deep reinforcement learning algorithm in complex environment, an improved deep reinforcement learning path planning algorithm is proposed. The exploration factor is improved and dynamically adjusted according to the convergence degree of the algorithm, so that the exploration factor dynamically decreases with the increase of the understanding degree of the agent to the environment, thus speeding up the convergence speed of …

Application Of Systems Engineering Principles In A Reliability Assessment Of Air- Cooled Heat Exchangers, Dheerajkumar R Narang

Harrisburg University Experiential Learning Projects

A significant systems engineering challenge exists due to the lack of a comprehensive methodology that holistically addresses both the static and dynamic components of air-cooled heat exchangers. Traditional methodologies often overlook the dynamic components—such as fin blades, electrical motors, gearboxes and propellers (fans)—that are integral to the overall performance and reliability of the air-cooled heat exchangers. The absence of an integrated framework that considers the interdependencies and interactions between mechanical and dynamic components complicates the task of accurately assessing the remaining life and ensuring the reliability of the entire system.

This article proposes a holistic RLA and reliability engineering framework …

The Boris Experience: Evaluating Omnichannel Returns And Repurchase Intention, Jianliang Hao, Robert G. Richey Jr., Tyler R. Morgan, Ian M. Slazinik

Faculty Publications

Researchers have examined the influence of the factors on reducing return rates in retailing over the years. However, the returns experience is often an overlooked way to drive customer engagement and repeat sales in the now ubiquitous omnichannel setting. The focus on returns prevention in existing research overshadows management’s need to understand better the comprehensive mechanics linking the customer in-store return experience with their repurchase actions. Recognizing the need to bridge different stages of the returns management process, this research aims to explore the facilitators and barriers of in-store return activities.

Enhanced Intellectual Property Protection Mechanisms Towards Collaborative Data Sharing In Metal-Based Additive Manufacturing, Durant Hayes Fullington

Theses and Dissertations

This dissertation aims to develop effective methodologies towards enhanced intellectual property protections for data sharing frameworks in metal-based additive manufacturing (AM). Currently, many small-to-medium sized manufacturers face data availability challenges due to the prohibitive high cost to collect, process, and analyze large amounts of process-related data for AM. Because these manufactures rely heavily on small-scale data, it can be difficult for them to effectively train complex machine learning (ML) algorithms, which are commonly used for AM process monitoring. One popular solution is to develop collaborative data sharing frameworks, where multiple independent AM users can share their data to increase the …

On Topological Measures And Network Vulnerability Patterns: A Review And Comparative Analysis, Saviz Saei

Theses and Dissertations

Despite much hope for climate change to slow down or even reverse, younger generations face a future overshadowed by extreme events. The indisputable reality is that unless the United Nations establishes comprehensive and sustained climate justice policies, children today will experience five times more extreme events than those that took place a century ago. On Monday, July 3rd of 2023, an unprecedented peak in global temperatures was documented, marking the highest global temperature ever recorded, as the U.S. National Centers for Environmental Prediction reported. These increasing temperatures indicate the ongoing and intensifying phenomenon of climate change, which amplifies the frequency …

Strategic Responses For Unplanned Events, Tidjan Simpson

Harrisburg University Dissertations and Theses

The paper addresses the question, “Can dynamic, effective response plans be made for stakeholders of a manufacturing line dealing with unplanned events at a manufacturing line, irrespective of an individual’s unique subject matter expertise? Prior research in manufacturing-related environments has indicated the existence of a high frequency of unplanned events. When not responded to efficiently, they can result in reduced financial efficiency and employee overwhelm. Through collection and analysis of interviews conducted with stakeholders in the manufacturing environment, a possible means of efficiently addressing unplanned events can be found or synthesized to help stakeholders navigate uncertainty in the manufacturing environment …

Processing Cost Analysis For Great South Metals, Evan Briggs, Madisen Laskos, Jared Perrin

Senior Design Project For Engineers

Great south Metals (GSM), a steel processing company based in Acworth, GA, has partnered with the Kennesaw State University (KSU) Industrial and System Engineering (ISYE) department to optimize its costing model. Currently, GSM uses a flat pricing structure for GSM-owned materials and estimates costs for toll processing. However, this approach has led to inaccuracies in pricing and challenges in tracking profitability. GSM seeks to transition to a more systematic and data-driven costing model that will improve both internal and external quoting while ensuring competitiveness in the market.

To address these challenges, the project focused on developing separate costing matrices for …

Deep Learning For Bitcoin Price Direction Prediction: Models And Trading Strategies Empirically Compared, Oluwadamilare Omole, David Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper applies deep learning models to predict Bitcoin price directions and the subsequent profitability of trading strategies based on these predictions. The study compares the performance of the convolutional neural network–long short-term memory (CNN–LSTM), long- and short-term time-series network, temporal convolutional network, and ARIMA (benchmark) models for predicting Bitcoin prices using on-chain data. Feature-selection methods—i.e., Boruta, genetic algorithm, and light gradient boosting machine—are applied to address the curse of dimensionality that could result from a large feature set. Results indicate that combining Boruta feature selection with the CNN–LSTM model consistently outperforms other combinations, achieving an accuracy of 82.44%. Three …

Security Of Mobile Radiological Sources: Overview Of Industry Applied Technologies, Ann M. Archer, Ashleigh Wickham

International Journal of Nuclear Security

Small radiological sources used in industrial settings recurrently require transit between job sites. Securing these sources, while stationary, can be addressed with standard security approaches and equipment. Transport of these sources increases the risk and complexity of managing and maintaining control of these sources. Implementing methodologies to securely monitor and locate sources improves response and resolution of anomalous events during transit. The Mobile Source Transit Security (MSTS) system was developed to improve security and provide situational awareness of these mobile sources throughout their job cycle. The MSTS development effort focused on creating a set of systems that could be successfully …

A Novel Interpretation Of Average Run Length For Assessing The Performance Of Control Charts, Gonçalo Sousa

Masters Theses

The Average Run Length (ARL) is a performance measure of Control Charts widely used within Statistical Process Control. In this study we propose a new approach for the computation of the ARL that is based on a novel interpretation of out-of-control signals produced by a Control Chart. Specifically, out-of-control signals used to calculate traditional ARLs may correspond to Type I errors and may not reflect a Control Chart’s true performance. To compensate for this issue, for Shewhart and EWMA charts, constraints are applied to the calculation of ARLs so that only out-of-control signals that occur when the corresponding statistic is …

A Talking Cart, Abdullah Bin Naeem

LSU New Orleans Theses and Dissertations

This research investigates the development of a robust AI-powered detection and tracking engine aimed at revolutionizing the retail checkout experience. The foundation of this work is a comprehensive exploration of state-of-the-art Computer Vision methodologies, particularly focusing on object detection, segmentation, and tracking. The study employs a modular pipeline that integrates advanced visual recognition algorithms with a robust data processing framework.

Key to this work is the construction of a synthetic dataset using Unity3D, enabling the generation of high-quality annotated data that mirrors real-world retail scenarios. This approach addresses the challenge of insufficient labeled datasets by simulating diverse and cluttered shopping …

Model Reference Adaptive Control For Mobile Manipulators And Beyond, Srivatsan Srinivasan

All Dissertations

In recent years, robotics has expanded into various sectors, including manufacturing, transportation, and household services, making the integration of autonomy a critical area of research. This shift aims to ensure safety and enhance the utility of autonomous systems. Traditionally, robotic applications focused separately on mobility, like automated guided vehicles, and manipulation, such as serial-chain arms in manufacturing. Today, however, we see a merging of these capabilities in the growing field of mobile manipulator robots that combine movement with purposeful interactive functionalities.

A typical mobile manipulator is a robotic arm mounted on a wheeled base. This thesis focuses on advancing control …