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IISE Annual Conference and Expo 2024

作者： Garbie, Ibrahim Garbie, Muhammad Department of Mechanical Engineering Industrial Engineering Program College of Engineering Helwan University Cairo Egypt Department of Industrial Systems and Manufacturing Engineering Texas Tech University LubbockTX United States

ISBN: (纸本)9781713877851

Currently, researchers are concentrating their attention on design for manufacturing, design for assembly, design for cost and design for quality, design for complexity, design for reconfiguration, design for sustainability, and design for X…etc., but they do not mention design manufacturing enterprises system for Industry 4.0. The design manufacturing enterprises system for Industry 4.0 is a systemic approach that simultaneously identifies elements and components for designing manufacturing enterprises for Industry 4.0, taking into consideration the new urgency of adopting Industry 4.0 and the challenges and risk management for implementing Industry 4.0. In this paper, the designing analysis and level will be presented by identifying the relative importance of urgent adoption and the challenges of implementing Industry 4.0. © IISE Annual Conference and Expo *** rights reserved.

关键词： Smart manufacturing

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Multi-criteria decision model for selection of a material suitable to lightning strike protection in aerospace applications

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Materials Today: Proceedings 2022年 59卷 725-733页

作者： Himagireesh, Ch. Ramji, K. Durga Prasad, K.G. Hari Kiran, V. Department of Mechanical Engineering Engineering and Technology Program GayatriVidyaParishad College for Degree & P.G.Courses Andhra Pradesh Visakhapatnam India Department of Mechanical Engineering Andhra University Visakhapatnam India Department of Mechanical Engineering Avanthi Institute of Engineering and Technology Andhra Pradesh India

In order to protect the aerospace structures against electromagneticinterference (EMI) caused by lightning strikes, metallic meshes or foils are currently being used. But the additional weight of metallic meshes cause counterbalance of weight saving imparted by the composite materials. In this context, Al6061 hybrid metal matrix composite specimens with different proportions of SiC, Al2O3 and fly ash particulates as reinforcement materials have been prepared and tested their characteristics suitability to lightning strike protection (LSP). As there is a conflicting nature among these properties a multi-criteria decision model using AHP, Entropy and TOPSIS techniques with a view to select appropriate specimen to meet the objective. The results of the proposed decision model are compared with that of the other methods VIKOR and PROMETHEE so as to validate the results. The same weightages for the properties are used in all the three methods. The proposed decision model is the robust one for ranking of the materials. © 2021

关键词： Aluminum oxide

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Analysis of Sandwich Structures with 3D-Printed Kresling Origami Cores

Analysis of Sandwich Structures with 3D-Printed Kresling Ori...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Hossain, Md Shahjahan Csercsevits, Vincent Seshaiah, Kira Bateniparvar, Omid Ghosh, Ranajay Department of Mechanical and Aerospace Engineering University of Central Florida OrlandoFL United States Department of Mechanical Engineering Widener University ChesterPA United States Smith College Picker Engineering Program NorthamptonMA United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Lightweight structures with bioinspired metamaterials, with their uniquely engineered properties not found in naturally occurring materials, have garnered significant attention for their potential in various engineering applications. This study explores the mechanical behavior of sandwich plate structures utilizing the Kresling origami pattern, fabricated through a straightforward 3D printing process. By conducting 3-point bending and compression tests, as well as simulations with Abaqus software, the research investigates the distinctive mechanical properties and performance enhancements these origami-inspired structures offer under mechanical loading. This study is noteworthy for being the first to investigate the bending characteristics of sandwich structures utilizing the two cell Kresling pattern or double Kresling, an area that has not been previously explored. Utilizing the Kresling structure in sandwich panels poses a challenge due to its rotational behavior. To address this, we employ a double Kresling pattern, which confines the rotation to the middle layer. This approach ensures that the outer layers remain stable, maintaining the overall integrity of the sandwich panel structure during deformation under mechanical loading. The findings reveal that the 3D-printed Kresling origami core significantly reduces weight while maintaining structural integrity, making it especially beneficial for aerospace engineering, where lightweight yet strong materials are crucial. This research highlights the potential of Kresling-patterned sandwich plates to improve efficiency and performance in supersonic vehicles, providing valuable insights into their structural efficiency and applicability in advanced engineering fields. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Compression testing

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Sustainability of Manufacturing Enterprises: A Psychological Perspective of Linking Manufacturing Layers

Sustainability of Manufacturing Enterprises: A Psychological...

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IISE Annual Conference and Expo 2024

ISBN: (纸本)9781713877851

As sustainability/sustainable development (S/SD) is still considered the buzzword in manufacturing environments, particularly after showing up and joining Industry 4.0 (I4.0), S/SD is prescribed to be embraced as one of the major perspectives of actualizing I4.0. Manufacturing, in common, is separated into three primary streams or layers. These layers are represented by machine design (MD), manufacturing processes (MP), and manufacturing systems (MS). All these layers constitute manufacturing enterprises. Although these layers coincide or overlap at one point, there's a psychological link between them. The primary layer is called the core and is dependable for designing machine components. The second layer is called the chosen layer, and it is represented by the manufacturing process with which generation operations will be adopted. The final layer could be a given one and is utilized to demonstrate which manufacturing system can be chosen. This paper aims to discover the S/SD for these layers and the psychological interface between them. In this paper, components of these three layers will be distinguished and analyzed, and the S/SD index of linking these layers through a psychological perspective will be proposed and outlined independently and universally. © IISE Annual Conference and Expo *** rights reserved.

关键词： Smart manufacturing

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Wind energy as a source of green hydrogen production in the USA

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Clean Energy 2023年第1期7卷 8-22页

作者： Ashish Sedai Rabin Dhakal Shishir Gautam Bijaya Kumar Sedhain Biraj Singh Thapa Hanna Moussa Suhas Pol National Wind Institute Texas Tech UniversityLubbockTX 79401USA Department of Mechanical Engineering Texas Tech UniversityLubbockTX 79401USA Department of Mechanical Engineering Tribhuvan UniversityPurbanchal CampusDharanNepal Green Hydrogen Lab Department of Mechanical EngineeringKathmandu UniversityDhulikhelNepal Wind Energy Program Texas Tech UniversityLubbockTX 79401USA

The study incorporates an overview of the green hydrogen-production potential from wind energy in the USA,its application in power generation and the scope of substituting grey and blue hydrogen for industrial *** 10 million metric tons of grey and blue hydrogen is produced in the USA annually to fulfil the industrial demand,whereas,for 1 million metric tons of hydrogen generated,13 million metric tons of CO_(2) are released into the *** research aims to provide a state-of-the-art review of the green hydrogen technology value chain and a case study on the production of green hydrogen from an 8-MW wind turbine installed in the southern plain region of *** research estimates that the wind-farm capacity of 130 gigawatt-hours is required to substitute grey and blue hydrogen for fulfilling the current US annual industrial hydrogen demand of 10 million metric *** study investi-gates hydrogen-storage methods and the scope of green hydrogen-based storage facilities for energy produced from a wind *** research focuses on the USA’s potential to meet all its industrial and other hydrogen application requirements through green hydrogen.

关键词： green hydrogen wind energy electrolysis greenhouse gases

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Trust Relationship in Large Group Emergency Decision-Making

Trust Relationship in Large Group Emergency Decision-Making

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2024 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2024

作者： Orshella, D.D. Masruroh, N.A. Arini, H.M. Department of Mechanical and Industrial Engineering Universitas Gadjah Mada Yogyakarta Indonesia Industrial Engineering Program Galuh University Ciamis Indonesia

ISBN: (纸本)9798350386097

Emergency decision-making requires perspectives from multiple decision-makers with different knowledge and experience to evaluate alternatives jointly and agree on the final solution. Researchers are developing the Large Group Emergency Decision-Making (LGEDM) framework, an assessment and evaluation process by 20 or more experts of alternative solutions in emergency cases. Trust relationship among experts participating in LGEDM is an important factor in the stages of LGEDM to reach the ideal consensus level. This literature review examines the development of research adapting trust relationships in the LGEDM framework, specifically from two perspectives (similarity-based trust and familiarity-based trust) and evidence of the effectiveness of trust relationships from previous studies. The study also identifies several opportunities from previous studies and provides recommendations for future studies. © 2024 IEEE.

关键词： Decision-making emergency familiarity similarity trust

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Comparison of Bioinspired MLP Controllers for Mobile Robots Obstacle Following/Avoidance

Comparison of Bioinspired MLP Controllers for Mobile Robots ...

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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Luiz, Matheus De S. Pastrana, M.A. Da Silva, Lukas. A. Campagnucci, Pamela. R. A. N. Mendoza-Penaloza, Jose Benevides, Rafael R.L. Munoz, Daniel M. University of Brasilia Mechatronics Graduate Program Department of Mechanical Engineering Brasilia Brazil University of Brasilia Faculty of Gama Electronics Engineering Undergraduate Program Brasilia Brazil

ISBN: (纸本)9798350374575

Proportional, integral, and derivative (PID) controllers have been widely adopted for industrial applications. However, these controllers are not very efficient for non-linear systems. Artificial neural networks (ANN) based on the Multilayer Perceptron (MLP) have great potential to replace PID controllers due to their polynomial structure, allowing complex non-linear systems to be controlled. This article introduces the integration of four MLPs as alternatives to a traditional PID controller. These MLPs were trained through four bioinspired algorithms tailored for following tasks in mobile robots. The bioinspired algorithms employed for MLP network training include Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Month-Flame Optimization (MFO), and Artificial Hummingbird Algorithm (AHA). A comparative analysis was conducted between these MLPs and a classic PID controller, focusing on parameters such as overshoot (OS), settling time (ST), and steady-state error for different simulated scenarios. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Close-Range Human Following Control on a Cane-Type Robot with Multi-Camera Fusion

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IEEE Robotics and Automation Letters 2023年第10期8卷 6443-6450页

作者： Liu, Haowen Wu, Fengxian Zhong, Bin Zhao, Yijun Zhang, Jiatong Niu, Wenxin Zhang, Mingming Shenzhen Key Laboratory of Smart Healthcare Engineering Guangdong Provincial Key Laboratory of Advanced Biomaterials Department of Biomedical Engineering Southern University of Science and Technology Shenzhen518055 China School of Medicine Tongji University Shanghai201619 China Department of Biomedical Engineering Southern University of Science and Technology Shenzhen518055 China Department of Biomedical Engineering National University of Singapore Singapore117583 Singapore School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China

Cane-Type robots have been utilized to assist the mobility-impaired population. The essential technique for cane-Type robots is to follow the user's ambulation at a close range. This study developed a new cane-Type wheeled robot and proposed a novel human-following control frame with multi-camera fusion. This human following control adopts a cascade control strategy consisting of two parts: 1) a human following position controller that locates a user by detecting his/her legs' positions via multi-camera fusion and 2) a cane robot velocity controller to steer the cane robot to the target position. The proposed strategy's effectiveness has been validated in outdoor experiments with six healthy subjects. The experimental scenarios included different terrains (i.e., straight, turning, and inclined paths), road conditions (i.e., asphalt and brick roads) and walking speeds. The obtained results showed that the average tracking error in the X and Y directions was less than 4.1 and 4.4 cm, respectively, and the error in angle was less than 12.9 across all scenarios. Moreover, the cane robot can effectively adapt to a wide range of individual gait patterns and achieve stable human following at daily walking speeds (0.74 m/s-1.47 m/s). © 2016 IEEE.

关键词： Microcontrollers

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Optimizing Markov Chain Initial Conditions for Studying Blunt Body Reentry Dynamics Using Differential Evolution

Optimizing Markov Chain Initial Conditions for Studying Blun...

引用

AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Tiwari, Bipin Oz, Furkan Kassem, Ashraf Romeo, Shafi Al Salman Kara, Kursat San, Omer Department of Mechanical Aerospace & Biomedical Engineering University of Tennessee KnoxvilleTN37996 United States School of Mechanical & Aerospace Engineering Oklahoma State University StillwaterOK74078 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

The dynamics of blunt-body reentry vehicles are crucial, as they must withstand the intense aerodynamic forces and extreme heat generated during atmospheric reentry. Despite thermal protection benefits, the blunt body shape can cause dynamic instabilities, especially at transonic and low-supersonic speeds, which are crucial during parachute deployment and scientific measurements. Ensuring robust stability requires precise optimization of system parameters and initial conditions. Markov chain Monte Carlo (MCMC) framework, widely used for nonlinear parameter estimation for these systems, is highly sensitive to initial conditions. However, traditional gradient-based methods are prone to getting stuck in local minima, whereas neural network-based approaches often face challenges such as overfitting, hyperparameter sensitivity, and the curse of dimensionality in navigating complex loss landscapes. This study employs Differential Evolution (DE), an evolutionary algorithm, to optimize initial conditions for MCMC parameter estimation. We present a case study on 1-DoF planar motion blunt body vehicle dynamics, demonstrating that DE improves computational efficiency and solution quality. Using DE, the pitch-damping sum coefficients (a = 1.49, b =-0.78, c =-0.37, d =-0.31, and e =-1.01) were optimized to capture nonlinear aerodynamic behavior through a cubic spline model. The reconstructed angle-of-attack (a) trajectories closely matched high-fidelity CFD data, with a sum of squared errors of 700, validating the accuracy of approach. Additionally, DE reduced computational time significantly, achieving a 30.0% reduction when using 10 CPU cores and a 43.6% reduction with 15 CPU cores compared to 5 CPU cores computation. This research advances our understanding of blunt body dynamics and underscores the value of evolutionary algorithms in complex aerospace applications. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Markov chains

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Trajectory Reconstruction of Blunt Body Capsules from Ballistic Range Testing Data Using Multi-Fidelity Gaussian Processes

Trajectory Reconstruction of Blunt Body Capsules from Ballis...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Romeo, Shafi Al Salman Oz, Furkan Kassem, Ashraf Tiwari, Bipin San, Omer Kara, Kursat School of Mechanical and Aerospace Engineering Oklahoma State University StillwaterOK74078 United States Department of Mechanical Aerospace and Biomedical Engineering University of Tennessee KnoxvilleTN37996 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Trajectory reconstruction from the sparse observation points of ballistic range testing data is crucial for accurately evaluating the performance and behavior of typical blunt bodies like the Genesis entry capsule, which become dynamically unstable at mid to low supersonic speeds. This instability causes the angle of attack oscillations during descent;if not addressed during the design process, these oscillations may lead to mission failure. Traditional methods often struggle with uncertainties and noise in the measurement data. Gaussian process regression offers a robust, non-parametric approach to address these challenges. However, the Gaussian process based on classical Bayesian optimization strategies does not effectively accommodate the inclusion of known physical behaviors or prior knowledge. This paper explores a hybrid optimization technique incorporating free-flight computational fluid dynamic simulations as prior information in physical models into the Bayesian optimization framework. We investigate applying this Multi-Fidelity Gaussian process for trajectory reconstruction in synthetic ballistics testing data. We emphasize its advantages in handling noisy data and providing probabilistic predictions, which can be used as input to parameter identification tools. The results indicate that the framework improves the precision of ballistic trajectory predictions and offers robust uncertainty quantification, making it an invaluable tool for ballistic range data analysis and design optimization. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Angle of attack

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