Browse Topic: Production
As the adoption of Electric Vehicles (EV) and Plug-in Hybrid Electric Vehicles (PHEV) continues to rise, more individuals are encountering these quieter vehicles in their daily lives. While topics such as propulsion sound via Active Sound Design (ASD) and bystander safety through Acoustic Vehicle Alerting Systems (AVAS) have been extensively discussed, charging noise remains relatively unexplored. Most EV/PHEV owners charge their vehicles at home, typically overnight, leading to a lack of awareness about charging noise. However, those who have charged their cars overnight often report a variety of sounds emanating from the vehicle and the electric vehicle supply equipment (EVSE). This paper presents data from several production EVs measured during their normal charging cycles. Binaural recordings made inside and outside the vehicles are analyzed using psychoacoustic metrics to identify sounds that may concern EV/PHEV owners or their neighbors.
This paper discusses a systematic process that was developed to evaluate the acoustic performance of a production dash system. In this case it is for an electric vehicle application. The production dash panel was tested under different configurations to understand the importance of passthroughs in the acoustics of the system. Results show that often the performance of the passthroughs strongly affects the overall performance of the dash system and this may become the limiting factor to increase the system sound transmission loss. To understand the acoustic strength of different passthroughs and their effects on the overall system, the dash with passthroughs underwent extensive testing. Subsequently, a test procedure using flat panels was developed to quantify the performance of individual passthroughs on a part level. This data can be used by the OEM to develop STL targets that can be considered in the grommet design early in the vehicle development process.
The mass production of conventional silicon chips relies on a successful business model with large “semiconductor fabrication plants” or “foundries.” New research by KU Leuven and imec shows that this “foundry” model can also be applied to the field of flexible, thin-film electronics. Adopting this approach would give innovation in the field a huge boost.
Composite materials are created by combining two or more different materials, such as a filler or fibrous reinforcement dispersed in a polymer matrix. The primary goal of developing composites is to improve properties while reducing weight, making them ideal for the sustainable development of the automotive industry. Poly(lactic acid) (PLA) has emerged as a promising polymer matrix for composites due to its ecological and biodegradable nature, as well as its good mechanical properties (tensile strength and modulus of elasticity), though it remains limited when compared to engineering polymers such as acrylonitrile butadiene styrene (ABS) and acrylonitrile styrene acrylate (ASA). Cotton fibers have gained visibility in recent years as reinforcement in various matrices due to their low cost, renewable origin, and relative abundance. Incorporating cotton fibers into PLA can improve its mechanical properties, enhancing attributes such as tensile strength and stiffness, which makes the
High-efficiency manufacturing involves the transmission of copious amounts of data, exemplified both by trends in the automotive industry and advances in technology. In the automotive industry, products have been growing increasingly complex, owing to multiple SKUs, global supply chains and the involvement of many tier 2 / Just-In Time (JIT) suppliers. On top of that, recalls and incidents in recent years have made it important for OEMs to be able to track down affected vehicles based on their components. All of this has increased the need for OEMs to be able to collect and analyze component data. The advent of Industry 4.0 and IoT has provided manufacturing with the ability to efficiently collect and store large amounts of data, lining up with the needs of manufacturing-based industries. However, while the needs to collect data have been met, corporations now find themselves facing the need to make sense of the data to provide the insights they need, and the data is often unstructured
Opening a tailgate can cause rain that has settled on its surfaces to run off onto the customer or into the rear loadspace, causing annoyance. Relatively small adjustments to tailgate seals and encapsulation can effectively mitigate these effects. However, these failure modes tend to be discovered relatively late in the design process as they, to date, need a representative physical system to test – including ensuring that any materials used on the surface flow paths elicit the same liquid flow behaviours (i.e. contact angles and velocity) as would be seen on the production vehicle surfaces. In this work we describe the development and validation of an early-stage simulation approach using a Smoothed Particle Hydrodynamics code (PreonLab). This includes its calibration against fundamental experiments to provide models for the flow of water over automotive surfaces and their subsequent application to a tailgate system simulation which includes fully detailed surrounding vehicle geometry
In Automobile manufacturing, maintaining the Quality of parts supplied by vendor is crucial & challenging. This paper introduces a digital tool designed to monitor trends for critical parameters of these parts in real-time. Utilizing Statistical Process Control (SPC) graphs, the tool continuously tracks Quality trend for critical parts and process parameters, predicting potential issues for proactive improvements even before parts are supplied. The tool integrates data from all Supplier partners across value chain into a single ecosystem, providing a comprehensive view of their performance and the parts they supply. Suppliers input data into a digital application, which is then analyzed in the cloud using SPC techniques to generate potential alerts for improvement. These alerts are automatically sent to both Suppliers and relevant personnel at the OEM, enabling proactive measures to address any Quality deviations. 100% data is visualized in an integrated dashboard which acts as a
U.S. Army Combat Capabilities Development Command’s Armaments Center Independence, MO usarmy.pica.jpeo-aa.mbx.jpeo-aa-public-affairs@army.mil
A battery-electric Honda midsize SUV entering production in early 2026 will use Helm.ai's artificial intelligence to facilitate conditional automated driving. The start-up firm's AI technology could soon see its first off-highway application. “Different driving environments look pretty much the same from an engineering perspective, so the lessons we've learned from [passenger vehicle] autonomous driving can be brought to the mining space in a fairly seamless fashion,” Vladislav Voroninski, cofounder and CEO of Helm.ai, said in an interview with SAE Media.
Affordable mass refers to the ability to rapidly produce large quantities of effective, cost-efficient munitions and systems. It’s not about cutting corners but about optimizing every facet of the production process, from design to deployment. The challenge goes beyond strategic methods of design and manufacturing — and must feature industrywide acceptance of affordability as a means of adding capacity, survivability, and efficacy to a new generation of munitions.
For my nearly 60-year lifetime, I have had the benefit of being part of a North American Automotive Industry that was, from a production perspective, completely rationalized and optimized. Given the unprecedented political events of the last couple of months, maybe we should all consider ourselves fortunate. Strong competition and a free market allowed for components, systems and vehicles to be produced in the optimal location with an optimized supply chain, all structured to serve markets in the U.S., Canada and Mexico with some exports mixed in. Consumers, dealers, suppliers and vehicle manufacturers all benefit from this optimized structure.
Additive Manufacturing (AM), particularly Fused Deposition Modeling (FDM), has emerged as a revolutionary method for fabricating complex geometries using a variety of materials. Polyethylene terephthalate glycol (PETG) is a thermoplastic material that is biodegradable and environmentally friendly, making it a preferred choice in additive manufacturing (AM) due to its affordability and ease of use. This study aims to optimize the FDM settings for PETG material and investigate the impact of key process parameters on printing performance. An experimental study was conducted to evaluate the influence of crucial factors in FDM, including layer thickness, infill density, printing speed, and nozzle temperature, on significant outcomes such as dimensional accuracy, surface quality, and mechanical properties. The use of the Grey Relational Analysis (GRA) approach enabled a systematic assessment of multi-performance characteristics, facilitating the optimization of the FDM process. The findings
Additive Manufacturing (AM), specifically Fused Deposition Modeling (FDM), has transformed the manufacturing industry by allowing the creation of intricate shapes using different materials. Polylactic Acid (PLA) is a biodegradable thermoplastic that is commonly used in additive manufacturing (AM) because of its environmentally friendly nature, affordability, and ease of processing. This study aims to optimize the parameters of Fused Deposition Modeling (FDM) for PLA material using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach. The researchers performed experimental trials to examine the impact of important FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical outcomes, including dimensional accuracy, surface finish, and mechanical properties. The methodology of design of experiments (DOE) enabled a systematic exploration of parameters. The TOPSIS approach, a technique for making decisions
Additive Manufacturing (AM), particularly Fused Deposition Modeling (FDM), has revolutionized the manufacturing sector by enabling the production of complex geometries using various materials. Polylactic Acid (PLA) is a biodegradable thermoplastic often used in additive manufacturing (AM) because to its eco-friendliness, cost-effectiveness, and processing simplicity. This research seeks to enhance the parameters of Fused Deposition Modeling (FDM) for PLA material with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methodology. The researchers conducted experimental trials to investigate the influence of key FDM parameters, including layer thickness, infill density, printing speed, and nozzle temperature, on essential outcomes such as dimensional accuracy, surface quality, and mechanical qualities. The design of experiments (DOE) technique facilitated a systematic investigation of parameters. The TOPSIS method, a decision-making tool based on several
Over the past two decades, microfluidic devices, which use technology to produce micrometer-sized droplets, have become crucial to various applications. These span chemical reactions, biomolecular analysis, soft-matter chemistry, and the production of fine materials. Furthermore, droplet microfluidics has enabled new applications that were not possible with traditional methods. It can shape the size of the particles and influence their morphology and anisotropy. However, the conventional way of generating droplets in a single microchannel structure is often slow, limiting production.
In order to give full play to the economic and environmental advantages of liquid organic hydrogen carrier(LOHC) technology in hydrogen storage and transportation as well as its technological advantages as a hydrogen source for hydrogen refueling station(HRS) supply, it promotes the change of hydrogen supply method in HRSs and facilitates its technological landing in the terminal of HRSs. In this paper, combining the current commercialization status of organic liquid technology and the current construction status of HRS in China, we establish a traditional long-tube trailer HRS model through Matlab Simulink, carry out modification on the existing process, maximize the use of the original equipment, and introduce the hydrogen production end of the station with organic liquid as an auxiliary hydrogen source. Research and design of the two hydrogen sources of gas extraction strategy and the station control strategy and the formation of Stateflow language model, to realize the verification
At $829 billion in revenues, 2023 was a banner year for the aerospace industry led by civil aviation companies. Despite its strength, operations were hampered by production constraints, the lingering effects of supply chain and workforce disruptions, and higher materials costs. Even as those issues abate, the commercial sector is chasing accelerated demand. A flood of new aircraft orders pushing backlogs at an accelerated pace is causing the industry to struggle as it seeks to ramp up production. If the dynamic persists, many airlines will be forced to revise or postpone existing plans for enlarging, refreshing, or greening their fleets.
Speed and flexibility are increasingly becoming the cornerstones of modern manufacturing, even as their continued adoption must align with existing values of cost and reliability all while keeping up with the demands for smarter, more complex products. This presents many challenges to machine builders since they must keep pace with the complexity of upcoming products while also being ready to meet the demands of the companies that will buy and operate these machines when it comes to efficiency, rapid production line ramp up, small batch sizes and high quality. Artificial intelligence will be a key tool going forward in achieving these results, offering the ability to more rapidly design, prototype, and implement changes and solutions through superior data analytics abilities and improved human-machine interactions.
The goal of this research is to better understand the methodologies for manufacturing biodiesel worldwide and the main raw materials used in its production. We aim to compare the solutions established by relevant countries with those used in Brazil, identifying their advantages and disadvantages. Our primary areas of interest include the United States, Indonesia, and Europe, where we will analyze the solutions and, whenever possible, understand the commercial and political interests involved. We will highlight aspects related to sustainability in the production, transportation, and use of biodiesel. The methodology is based on research from recent publications and news, organized into graphs to facilitate analysis and comparison. Next, we will also examine the consequences of the solutions adopted in Brazil, envisioning future scenarios and recommended paths. In the short term, biodiesel is expected to be replaced by renewable diesel (also known as green diesel in some regions
The automotive industry is facing unprecedented pressure to reduce costs without compromising on quality and performance, particularly in the design and manufacturing. This paper provides a technical review of the multifaceted challenges involved in achieving cost efficiency while maintaining financial viability, functional integrity, and market competitiveness. Financial viability stands as a primary obstacle in cost reduction projects. The demand for innovative products needs to be balanced with the need for affordable materials while maintaining structural integrity. Suppliers’ cost structures, raw material fluctuations, and production volumes must be considered on the way to obtain optimal costs. Functional aspects lead to another layer of complexity, once changes in design or materials should not compromise safety, durability, or performance. Rigorous testing and simulation tools are indispensable to validate changes in the manufacturing process. Marketing considerations are also
The goal of this work is to increase the accuracy and efficiency of hose cutting operations in small scale industries is by designing and building an automatic hose-cutting equipment. The device uses a computer-controlled system to autonomously cut pipes of various sizes and lengths. By means of a stepper motor-driven, rapidly spinning blade, the cutting process is accomplished. Additionally, the machine has sensors that measure the hose's length and modify the cutting position as necessary. Premium components and materials are used in the machine's construction; these are chosen for their performance and longevity. The device is able to boost cut precision and raise industry production all around from 100% to 190% efficient system thereby decreasing labor and time needed for hose cutting operations.
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