Browse Topic: Production
This specification covers a corrosion- and heat-resistant nickel alloy in the form of investment castings.
This specification covers a corrosion- and heat-resistant nickel alloy in the form of investment castings.
This specification covers a corrosion- and heat-resistant iron alloy in the form of investment castings.
This specification covers the engineering requirements for producing brazed joints in parts made of steels, iron alloys, nickel alloys, and cobalt alloys by use of silver alloy filler metals and the properties of such joints.
This specification covers a leaded bronze in the form of sand and centrifugal castings (see 8.6).
This specification covers an aluminum bronze alloy in the form of centrifugal and chill castings (see 8.5).
This specification covers a nickel-aluminum-bronze alloy in the form of sand, centrifugal, and continuous castings (see 8.5).
This specification covers the requirements for a hard anodic coating on magnesium alloys and the properties of the coating.
This specification covers bonded honeycomb core made of aluminum alloy and supplied in the form of blocks, slices, or other configurations as ordered (see 8.5).
The global medical device manufacturing industry is undergoing a rapid transformation driven by technological innovation, automation, and increasing demands for customized, high-quality care. For engineers at the heart of medtech manufacturing, understanding the latest technologies is crucial not only for maintaining competitiveness but also for ensuring regulatory compliance, improving time to market, and optimizing production workflows.
For the team at SmartCap, building top-notch gear for outdoor adventurers isn’t just a business — it’s a passion driven by their own love for the wild. But as demand for their rugged, modular truck caps soared after their move to North America in 2022, they hit a snag: How do you ramp up production without sacrificing the meticulous quality you are known for, all while navigating a tough labor market? Their answer? A bold step into the world of intelligent automation, teaming up with GrayMatter Robotics, and employing the company’s innovative Scan&Sand™ system.
Hatz Americas (Waukesha, Wisconsin) expanded its power generation product portfolio to include AC and DC mobile diesel generators for the recreational vehicle and industrial markets. The new offerings provide prepackaged, sound-attenuated solutions for power generation and hybrid battery charging. Manufacturing and testing of the 1B30VE engines used in the generators will continue to take place at the primary engine plant in Ruhstorf, Germany. Final assembly of the generator sets will occur at Hatz's new production facility in Italy. The first model released will be the GD3200-120 Silent Pack with RV package, which is available to order. This will be followed by the BD3000-56 Silent Pack for use in either 28V or 56V hybrid battery charging systems. https://www.hatzamericas.com
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.
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
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.
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
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
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
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.
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.
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
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