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Abstract The demand for contactless, rapid manufacturing has increased over the years, especially during the COVID-19 pandemic. Additive manufacturing (AM), a type of rapid manufacturing, is a computer-based system that precisely manufactures products. It proves to be a faster, cheaper, and more efficient production system when integrated with cloud-based manufacturing (CBM). Similarly, the need for semiconductors has grown exponentially over the last five years. Several companies could not keep up with the increasing demand for many reasons. One of the main reasons is the lack of a workforce due to the COVID-19 protocols. This article proposes a novel technique to manufacture semiconductor chips in a fast-paced manner. An algorithm is integrated with cloud, machine vision, sensors, and email access to monitor with live feedback and correct the manufacturing in case of an anomaly.

Abstract An accurate Unmanned Aerial System (UAS) Flight Dynamics Model (FDM) allows us to design its efficient controller in early development phases and to increase safety while reducing costs. Flight tests are normally conducted for a pre-established number of flight conditions, and then mathematical methods are used to obtain the FDM for the entire flight envelope. For our UAS-S4 Ehecatl, 216 local FDMs corresponding to different flight conditions were utilized to create its Local Linear Scheduled Flight Dynamics Model (LLS-FDM). The initial flight envelope data containing 216 local FDMs was further augmented using interpolation and extrapolation methodologies, thus increasing the number of trimmed local FDMs of up to 3,642. Relying on this augmented dataset, the Support Vector Machine (SVM) methodology was used as a benchmarking regression algorithm due to its excellent performance when training samples could not be separated linearly.

Abstract The advancement in vision sensors and embedded technology created the opportunity in autonomous vehicles to look ahead in the future to avoid potential obstacles and steep regions to reach the target location as soon as possible and yet maintain vehicle safety from rollover. The present work focuses on developing a nonlinear model predictive controller (NMPC) for a high-speed off-road autonomous vehicle, which avoids undesirable conditions including stationary obstacles, moving obstacles, and steep regions while maintaining the vehicle safety from rollover. The NMPC controller is developed using CasADi tools in the MATLAB environment. The CasADi tool provides a platform to formulate the NMPC problem using symbolic expressions, which is an easy and efficient way of solving the optimization problem. In the present work, the vehicle lateral dynamics are modeled using the Pacejka nonlinear tire model.

Abstract This article investigates the fuel savings potential of a series hybrid military truck using a simultaneous battery pack design and powertrain supervisory control optimization algorithm. The design optimization refers to the sizing of the lithium-ion battery pack in the hybrid configuration. The powertrain supervisory control optimization determines the most efficient way to split the power demand between the battery pack and the engine. Despite the available design and control optimization techniques, a generalized mathematical formulation and solution approach for combined design and control optimization is still missing in the literature. This article intends to fill that void by proposing a unified framework to simultaneously optimize both the battery pack size and power split control sequence. This is achieved through a combination of genetic algorithm (GA) and Pontryagin’s minimum principle (PMP) where the design parameters are integrated into the Hamiltonian function.

Abstract Presently, 270 V direct current (DC) systems replace older 28 V DC voltage systems in both the civil and military aviation industry due to the requirement for more electrical power needs on board. Therefore, the existing avionics require retrofitting. The conversion from 270 V to 28 V appears to be quite promising for both old and new systems. This study aims to design an interleaved synchronous modular buck converter topology as a candidate for these requirements. Calculations for the converter design are conducted considering aviation standards. Switching with pulse-width modulation (PWM) is used to control the power converter. A double-loop feedback control system based on voltage and current feedback is designed. Therefore, the buck converter circuit with 1145 W power output is proposed, which supplies a 28 V and 41 A DC output from a 270 V DC input. The concept is verified using simulations and hardware-in-the-loop (HIL) experimental results.

Abstract In this article, a formation flying technique designed for a multiple unmanned aerial vehicles (multi-UAV) system to provide low-cost and efficient solution for civilian and military applications is presented. First, a modular leader-follower formation algorithm was developed to accomplish the formation flying with off-the-shelf low-cost components and sensors. Second, a proportional-integral-derivative (PID) controller was utilized for velocity control of the UAVs to maintain the tight formation. Third, a particle swarm optimization-optimized reciprocal velocity obstacles (PSO-RVO) algorithm was utilized for obstacles avoidance and collision avoidance between the UAVs while navigating, with the aid of sonar ranging sensors onboard. The formation flying algorithm developed was tested through both simulation and experiment using two quadcopters with global positioning system (GPS) signals.

Abstract The use of converging-diverging (C-D) variable area nozzle (VAN) in military aeroengines is now common, as it can give optimal expansion and control over engine back pressure, for a wide range of engine operations. At higher main combustion temperatures (desired for supercruise), an increase in the nozzle expansion ratio is needed for optimum performance. But changes in the nozzle throat and exit areas affect the visibility of engine hot parts as the diverging section of the nozzle is visible for a full range of view angle from the rear aspect. The solid angle subtended by engine hot parts varies with change in visibility, which affects the aircraft infrared (IR) signature from the rear aspect. This study compares the performances of fixed and variable area nozzles (FAN and VAN) in terms of engine thrust and IR signature of the engine exhaust system in the boresight for the same increase in combustion temperature.

Abstract Letter from the Guest Editors

Abstract This article describes the research work taken to compare the effect of air blast and surface-buried mine blast loading on an armored fighting vehicle (AFV) escape hatch, using the coupled Eulerian-Lagrangian (CEL) technique. Two types of escape hatch were considered for the study, namely, the flat plate version and double-side curved-plate version. To evaluate the research methodology used in this investigation, initially, a published experimental work on a circular plate subjected to air blast was chosen and a benchmark simulation was carried out using the CEL technique to establish the simulation procedure. Then the established procedure was utilized for further analysis. It was observed that the variation in the deformation between the published literature and the simulation work was well within the acceptable engineering limits.

Abstract This study underscores the benefits of refining the intralogistics process for small- to medium-sized manufacturing businesses (SMEs) in the engineer-to-order (ETO) sector, which relies heavily on manual tasks. Based on industrial visits and primary data from six SMEs, a new intralogistics concept and process was formulated. This approach enhances the value-added time of manufacturing workers while also facilitating complete digital integration as well as improving transparency and traceability. A practical application of this method in a company lead to cutting its lead time by roughly 11.3%. Additionally, improved oversight pinpointed excess inventory, resulting in advantages such as reduced capital needs and storage requirements. Anticipated future enhancements include better efficiency from more experienced warehouse staff and streamlined picking methods. Further, digital advancements hold promise for cost reductions in administrative and supportive roles.

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