Engineering Commons^™

Brief Review On Applying Reinforcement Learning To Job Shop Scheduling Problems, Xiaohan Wang, Zhang Lin, Ren Lei, Kunyu Xie, Kunyu Wang, Ye Fei, Chen Zhen

Journal of System Simulation

Abstract: Reinforcement Learning (RL) achieves lower time response and better model generalization in Job Shop Scheduling Problem (JSSP). To explain the current overall research status of JSSP based on RL, summarize the current scheduling framework based on RL, and lay the foundation for follow-up research, the backgrounds of JSSP and RL are introduced. Two simulation techniques commonly used in JSSP are analyzed and two commonly used frameworks for RL to solve JSSP are given. In addition, some existing challenges are pointed out, and related research progress is introduced from three aspects: direct scheduling, feature representation-based scheduling, and parameter search-based scheduling.

Survey Of Ship Detection In Video Surveillance Based On Shallow Machine Learning, Zhenbo Bi, Shiyou Zhang, Yang Hua, Yuanhong Wu

Journal of System Simulation

Abstract: At present, detection of ship targets in video surveillance based on shallow machine learning methods is still attracting attention in the fields of underwater cultural heritage protection, marine aquaculture, maritime traffic, and port management. This paper provides a review and discussion for this kind of ship detection methods. The ship target detection based on video surveillance is divided into five parts according to the key technologies involved: preprocessing, region of interest extraction, target segmentation, ship feature extraction and ship type recognition. According to different functional modules, the core problems involved in them are pointed out, and the core ideas, …

Real-Time Simulation Technology Of Fluid-Thermo-Solid Coupling Of Hypersonic Vehicle, Yunqin Liu, Li Ni, Luming Zhao, Jinpeng Bai, Tingjun Li, Chenguang Wang

Journal of System Simulation

Abstract: The solution of the coupling characteristics of fluid-thermo-solid physics in the modeling of hypersonic vehicle is an unavoidable difficulty, and the real-time simulation of fluid-thermo-solid coupling is particularly challenging. Aiming at the conflicting problem of solution accuracy and solution efficiency in fluid-thermo-solid coupling real-time simulation, a CFD (Computational Fluid Dynamics)/ CSD (Computational Structural Dynamics)-based fluid-thermo-solid coupling characteristic solution method is established, which realizes the high-precision solution of the fluid, temperature, and structural deformation field coupling. According to the multi-condition offline solution set modeling method, by accumulating a large number of offline solutions as effective support for online …

A Data-Driven Modeling Method For Game Adversity Agent, Zeng Bi, Fang Xiao, Deshuai Kong, Xiangxiang Song, Zhengxuan Jia, Tingyu Lin

Journal of System Simulation

Abstract: Aiming at the problems of collaborative modeling of formation behavior and intelligent generation of decision-making in complex confrontation scenarios, based on the serious game to simulate the confrontation scenarios of complex maritime equipment against the air, this paper proposes a data-driven modeling method for game agent and uses a distributed modeling technology of parallel adversarial scenarios and opportunistic decision making technology of smart targets to achieve agent modeling. It provides support for the further exploration of multi-objective collaborative modeling in complex confrontation scenarios. The simulation results show that deep reinforcement learning algorithms can provide a basis for the modeling …

Research On Usv Navigation Simulation Key Technologies, Jianhai Jin, Zexing Zhou, Zhang Bo, Yihong Chen, Xizhong Wei

Journal of System Simulation

Abstract: In order to solve the problems of long test time, high cost and high risk, a general framework of simulation system for autonomous navigation test and verification of USV(Unmanned Surface Vessel) has been developed, and some key simulation technologies such as complex scenario simulation, intelligent perception, navigation simulation and environmental effect modeling are researched. the dynamic equation, kinematics equation, wind load modeling, wave surface modeling, wave drift force modeling and ocean current modeling are designed and realized. The simulation system is proved to have high accuracy and fidelity by the real ship test on the lake, which can greatly …

Kinematics Analysis And Simulation Of Automatically Tracking Dental Surgery Lamp, Zerui Jiang, Lijun Yang, Li Jun, Xiaolong Jiao, Zheng Hang

Journal of System Simulation

Abstract: In order to solve the problem that the oral surgical lamp cannot automatically adjust the irradiation posture of the surgical lamp according to the face direction and oral cavity position, a six-degree-of-freedom automatic tracking visual manipulator solution is proposed. Coordinate conversion is achieved through binocular vision to obtain three-dimensional information of oral cavity position and face normal vector. The geometric method is introduced into the kinematics calculation, and the closed solution of the inverse kinematics is obtained. The correctness is verified by the Maltab programming and the introduction of numerical values. Five-degree polynomial motion planning is performed …

Research On Digital Twin-Based Modeling And Monitoring Of Five-Axis Grinder, Xiao Tong, Haifan Jiang, Guofu Ding, Jiang Lei, Shuwen Ma

Journal of System Simulation

Abstract: Aiming at the poor virtual-real interaction ability, single data presentation mode, and hysteretic abnormality handling in CNC machine tool status monitoring, a visual monitoring method for machine tool process based on digital twin is proposed, Which realizes the mapping of three subsystems of machine tool, machinery, control and electrical to the information space from three dimensions of geometry, logic and data. The verification of instructions and CNC programs, real-time status monitoring and abnormality handling during operation are carried out. A digital twin-based machine tool modeling and monitoring system is designed and developed. Taking a five-axis CNC …

Hyperspectral Rx Anomaly Detection Method Based On The Fusion Of Spatial And Spectral Feature, Liu Xuan, Xiangyang Li, He Fang, Jianwei Zhao, Fenggan Zhang

Journal of System Simulation

Abstract: To address the problem that the hyperspectral anomaly detection algorithm does not make full use of the spatial information of the hyperspectral image and the detection accuracy is limited, a FSSRX (Fusing Spatial and Spectral Reed-Xiaol) anomaly detection algorithm that fuses spatial and spectrum information is proposed to improve the accuracy of hyperspectral anomaly detection. In FSSRX algorithm, the spatial feature of hyperspectral images is firstly extracted by the EMAP(Extended Multi-attribute Profile) method and the abnormal score of each pixel in spatial features is then calculated with RX detector. Meanwhile, RX anomaly detection is carried out directly on the …

Research On Model Reuse Technology Based On Semantic Matching And Composition, Xingyu Tian, Guangxun Zeng, Yunbo Gao, Lili Ye, Guanghong Gong, Li Ni

Journal of System Simulation

Abstract: In order to solve the data barriers between the conceptual model and the simulation scenario of the combat system, the intelligent mapping and model reuse technology of the simulation scenario is researched. The conceptual model is analyzed using DOM technology. Based on the ontology theory, the knowledge base of the combat domain is constructed and the web crawler is customized to build the domain thesaurus. Through the SWRL rule library, the reasoning engine is called to realize the relational reasoning at the semantic level. An intelligent matching algorithm is designed to map the semantic relationship to the combination relationship …

Research On Cloud Tool Integration And Management Methods, Tianying Zhang, Ji Hang, Junhua Zhou, Tao Luan

Journal of System Simulation

Abstract: In response to the application needs of using professional tools to develop complex products in the fields of aerospace, aviation, weapons, ships, etc., it is urgent to implement centralized management of cloud tools and cross-professional sharing of tools through tool service-oriented methods, so as to solve issues such as inconsistent tool versions, cross-professional resource barriers, and high thresholds for tool mastery during the traditional model development process. By studying the integration and calling methods of cross-professional and different versions of self-developed tools, as well as methods of tool server operation control, authority management, etc., and taking the local …

Predictive Control Method Of Peak Hour Passenger Flow At Urban Rail Station, Xiaohe Li, Jianping Wu, Depin Peng

Journal of System Simulation

Abstract: With the rapid development of subway in China, the urban rail station, especially the transfer station, is prone to generate passenger congestion in the peak period. After analyzing the types of passenger flow in and out of the platform, a predictive control model of passenger flow is established based on the discrete linear quadratic optimal control theory. Taking Fuxingmen Station as an example, the simulation environment of the station is built by using the simulation software of Anylogic. The historical passenger flow data in peak period and the optimal passenger flow control sequence obtained by solving the passenger flow …

Study And Effect Evaluation On The Setting Of Contraflow Left-Turn At Intersections, Zhao Dan, Xuejun Niu, Shuhao Zhang, Jiaxu Wei

Journal of System Simulation

Abstract: Contraflow left-turn is one of the traffic organization ways at intersections. By analyzing the setting parameters of the contraflow left-turn, the length and the range of the contraflow left-turn lane, the constrained conditions of the contraflow left-turn are determined, and the applicable conditions are determined from the road, traffic and signal control. VISSIM software is used to analyze a road intersection, simulate and evaluate the indicators related to the intersection entrance, optimize the timing plan of contraflow left-turn lane, and validate the feasibility and advantages of contraflow left-turn lane. The results show that the intersection delays are reduced by …

Variety Recognition Based On Deep Learning And Double-Sided Characteristics Of Maize Kernel, Feng Xiao, Zhang Hui, Zhou Rui, Qiao Lu, Wei Dong, Dandan Li, Yuyao Zhang, Guoqing Zheng

Journal of System Simulation

Abstract: In order to construct a maize kernel variety recognition model with high recognition accuracy and suitable for mobile phone application, a mobile phone is used to obtain maize kernel double-sided (embryonic and non-embryonic) images. Based on the lightweight convolutional neural network MobileNetV2 and transfer learning, a maize kernel image variety recognition model is constructed. In view of the existing research methods are mainly for single-sided recognition of maize kernel variety, the performance of single-sided and double-sided characteristics modeling and recognition is compared. The results show that the double-sided recognition accuracy of maize kernel double-sided characteristics modeling is 99.83%, which …

The Product Test Scheduling Problem, Megan Wydick Martin, Cliff Ragsdale, John Fico, Carlos G. Cajica-Sierra, Richard M. Fetcenko

International Journal of Applied Management and Technology

This research focused on product test scheduling in the presence of in-process and at-completion inspection constraints. Such testing arises in the context of the manufacture of products that must perform reliably in extreme environmental conditions. Often, these products must receive a certification from prescribed regulatory agencies at the successful completion of a predetermined series of tests. Operational efficiency is enhanced by determining the optimal order and start times of tests so as to minimize the makespan while ensuring that technicians are available when needed to complete in-process and at-completion inspections. We refer to this as the product test scheduling problem. …

Choosing Wearable Internet Of Things Devices For Managing Safety In Construction Using Fuzzy Analytic Hierarchy Process As A Decision Support System, Sharique Khalid

Theses, Dissertations and Capstones

Many safety and health risks are faced daily by workers in the field of construction. There is unpredictability and risk embedded in the job and work environment. When compared with other industries, the construction industry has one of the highest numbers of worker injuries, illnesses, fatalities, and near-misses. To eliminate these risky events and make worker performance more predictable, new safety technologies such as the Internet of Things (IoT) and Wearable Sensing Devices (WSD) have been highlighted as effective safety systems. Some of these Wearable Internet of Things (WIoT) and sensory devices are already being used in other industries to …

Clarity, Organization, Precision, Economy: A Technical Writing Guide For Engineers, David J. Adams, University Of New Haven

Civil Engineering Faculty Book Series

This fourth edition of COPE was sparked by my involvement with PITCH (Project to Integrate Technical Communication Habits) at the Tagliatela College of Engineering at the University of New Haven. This new edition contains additional material on data displays, as well as some additional material on writing about data—including how to avoid rhetorical shifts that undermine the precision of a technical report.

Launch Editorial, Jindong Qin, Xiaofang Chen, Lida Xu

Information Technology & Decision Sciences Faculty Publications

The digital economy is first and foremost a data economy, and data is the first element of the digital economy. Management System Engineering (MSE) is dedicated to the methodology of System Engineering (SE) and the practice of Management Decision Making. The digital economy is a network economy, and the Internet is the basic carrier of the digital economy. [Extracted from the article]

Data-Driven Semantic Modeling For Welding Assemblies, Fahim Ahmed

Wayne State University Dissertations

A significant information gap is prevalent between the design domain and the manufacturing domain. The designers lack manufacturing awareness as they have little knowledge regarding the manufacturability of their designs. The welding domain falls prey to this issue as designers lack manufacturing awareness and welding engineers lack weldability of the product assembly. Data-driven techniques have shown promising results in the analysis and understanding of complex welding processes. Data analytics play a significant role to turn data into valuable insights to assist in the weldability certification decision-making or weldability prediction for Resistance Spot Welding (RSW) as well. We have used machine …

Optimization-Based Uav Fleet Routing And Safety Assurance – Models, Algorithms, And Prototyping, Zhenyu Zhou

Wayne State University Dissertations

Unmanned aerial vehicles (UAVs), especially multi-rotor drones, have been increasingly used in various scenarios in the last decade. With the reduced hardware costs, improved battery life, and enhanced processor performance, we can eventually allow all kinds of drones to automatically travel through the low-altitude airspace. The large-scale application of drones will extend the basic transportation facilities from the ground to the air and form 3D transportation networks for the future. Compared to current ground-vehicle and aircraft traffic systems, multi-UAV systems are far from well-developed. Most current multi-UAV systems are human-operated or pre-programmed to perform specific tasks. The current application of …

Automotive Product Assortment Planning With Consideration Of Distribution Channel Dynamics, Madagedara Maduka Rushanjalee Balasooriya

Wayne State University Dissertations

Automotive original equipment manufacturers (OEMs) are putting a lot of effort into maintaining an efficient order catalog to offer better products to their customers in maketo-stock (MTS) markets. While product “assortment planning" research grows to more effectively identify the best assortments for OEMs, the existing configurable assortment planning literature ignores a significant dimension: the impact of distribution channels, especially dealer franchise networks. Dealers face unique challenges in trying to best satisfy the choice preferences of their local consumers by balancing their limited product configuration inventory with profitability. In many predominantly MTS automotive markets such as the U.S., the reality is …

Improving Or Operations Using Machine Learning Techniques, Tannaz Khaleghi

Wayne State University Dissertations

Recently, health care related studies are being widely conducted by researchers using unique and efficient techniques to increase system profitability, quality of care, and patient satisfaction. Surgery department is considered as the hospital's engine, and cost of surgical services has a huge impact on the overall profitability of the hospital. This thesis proposes novel approaches to improve the efficiency of surgical services by using machine learning concepts.

In the first part, this research investigates the prediction of the surgery durations and Current Procedural Terminology (CPT) Codes. Accurate prediction of the surgery duration will improve the utilization of indispensable surgical resources …

Agile Research - Getting Beyond The Buzzword, Trupti Narayan Rane

Engineering Management & Systems Engineering Faculty Publications

"Oh yeah, we're an Agile shop, we gave up Waterfall years ago." - product owners, managers, or could be anyone else. You will seldom have a conversation with a product or software development team member without the agile buzzword thrown at you at the drop of a hat. It would not be an oversell to say that Agile software development has been adopted at a large scale across several big and small organizations. Clearly, Agile is an ideology that is working, which made me explore more on its applicability in research. As someone who has been in the Information Technology …

Blockchain-Based Digital Trust Mechanism: A Use Case Of Cloud Manufacturing Of Lds Syringes For Covid-19 Vaccination, Trupti Rane, Jingwei Huang

Engineering Management & Systems Engineering Faculty Publications

Trust is essential in the digital world. It is a critical task to build digital trust for the ongoing digital engineering transformation. Aiming at developing a blockchain-based digital trust mechanism for Cloud Manufacturing or Manufacturing-as-a-Service (MaaS), in this paper, we use the manufacturing of low dead space (LDS) medical syringes through Cloud Manufacturing as a motivating scenario to develop a basic framework. To meet the need of optimally saving COVID-19 vaccine doses to save more lives, the medical device manufacturing community needs to make a swift move to meet the surged need for LDS syringes. Cloud Manufacturing is a form …

Adapting The Human Factors Analysis And Classification System For Commercial Fishing Vessel Accidents, Peter Zohorsky, Holly Handley, Ronald Boring (Ed.)

Engineering Management & Systems Engineering Faculty Publications

The commercial fishing industry is frequently described as one of the most hazardous occupations in the United States. The objective, to maximize the catch, is routinely challenged by a variety of elements due to the environment, the vessel, the crew, and how they interact with each other. This study developed and evaluated a version of Wiegmann and Shappell’s (2003) Human Factors Analysis and Classification System (HFACS), specifically for commercial fishing industry vessels (HFACS-FV), using data from ten years of fatal fishing vessel accidents. For this study, the accident investigation information was converted into the HFACS-FV format by independent raters and …

A Primer On The Human Readiness Level Scale (Ansi/Hfes 400-2021), Kelly Steelman, Holly Handley, Katie Plant (Ed.), Gesa Praetorius (Ed.)

Engineering Management & Systems Engineering Faculty Publications

"The Human Readiness Level (HRL) Scale is a simple 9-level scale for evaluating, tracking, and communicating the readiness of a technology for safe and effective human use. It is modeled after the well-established Technology Readiness Level (TRL) framework that is used throughout the government and industry to communicate the maturity of a technology and to support decision making about technology acquisition. Here we (1) introduce the ANSI/HFES 400-2021 Standard that defines the HRL scale and (2) provide concrete examples of evaluation activities to support the application of HRLs in the development of automated driving systems."

Machine Learning In Requirements Elicitation: A Literature Review, Cheligeer Cheligeer, Jingwei Huang, Guosong Wu, Nadia Bhuiyan, Yuan Xu, Yong Zeng

Engineering Management & Systems Engineering Faculty Publications

A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studies that incorporate ML and natural language processing (NLP) into demand elicitation. We answer the following research questions: (1) What requirement elicitation activities are supported by ML? (2) What data sources are used to build ML-based requirement solutions? (3) What technologies, algorithms, and tools are used to build ML-based requirement elicitation? (4) How to construct an ML-based requirements elicitation method? (5) What are the available tools to support ML-based requirements elicitation methodology? Keywords …

Theorizing The Initial Response Of Countries In Bringing Covid-19 Pandemic Under Control: The Effect Of Change Readiness Of Countries, M. Mahdi Moeini Gharagozloo, Farinaz Sabz Ali Pour, Chen Chen, Mozhgan Moeini Gharagozloo

Engineering Management & Systems Engineering Faculty Publications

Pandemic crises can bring the biggest and deepest shocks to countries around the world. In the first quarter of 2020, a global pandemic named “COVID-19” spread all over the world and not only took so many lives and created so much fear but also brought a tremendous financial pain as a result of shutting down economies to fight with this unknown contagious virus. This paper examines how countries’ change readiness enables them to bring the spread of an international crisis under control. We propose that higher levels of change readiness would help countries to cope with risks and uncertainties generated …

Acute Coronary Syndrome Prediction: A Data-Driven Machine Learning Modeling Approach In Emergency Care, Joshua Oluwatobiloba Emakhu

Wayne State University Dissertations

Healthcare facilities are faced with significant challenges all year round, with patients presenting to the emergency department (ED) with different health issues. Of these challenges, heart disease seems to be an outlier. With heart disease being the primary cause of mortality and morbidity in both developed and developing countries, clinical concerns for acute coronary syndrome (ACS) are one of emergency medicine’s most common patient encounters. Of the three sub-categories of ACS, non-ST-segment elevation myocardial infarction (NSTEMI) has a long-term impact on the well-being of patients if left untreated. Previous efforts in hospital management have applied machine learning algorithms in differentiating …

The Relationship Between First Case On-Time Starts, Turnover Times, And Operating Room Productivity, Rhafia Bucoy

Walden Dissertations and Doctoral Studies

Operating room (OR) managers struggle to manage day-to-day surgical operations while meeting and exceeding organizational productivity amid the COVID-19 pandemic. The deferral of surgeries contributes to millions of backlogs of surgical case volume and unintended negative consequences. Grounded in the proposition that first-case on-time starts (FCOTS) and turnover time (TOT) are correlates of OR productivity, the purpose of this quantitative correlational study was to examine the relationship between FCOTS, TOT, and OR productivity. Archival data from 136 electronic surgical records were collected from two free-standing ambulatory surgery centers and analyzed using multiple regression. The results of the one-service, eye-specialized, ambulatory …

Mixed-Integer Programming Methods For Modeling And Optimization Of Cascading Processes In Complex Networked Systems, Cheng-Lung Chen

Electronic Theses and Dissertations, 2020-2023

Dynamics and growth of many natural and man-made systems can be represented by large-scale complex networks. Entity interactions and community interconnections within complex networks increase the level of difficulty for the investigation on structural network properties such as robustness, vulnerability and resilience. In this dissertation, we develop methodologies based on mixed-integer programming techniques to solve challenging optimization problems that model cascading processes in complex networked systems. In particular, we seek to provide decision making recommendations for problems related to different types of cascading processes in networks commonly considered in a variety of applications: interdependent infrastructure networks and social networks. In …