Browse Topic: Manufacturing systems
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
Time Sensitive Networking (TSN) Ethernet is a real-time networking capability that is being developed by a growing number of embedded computing companies for the earliest stages of adoption by aerospace and defense manufacturers and their suppliers. According to the Institute of Electrical and Electronics Engineers (IEEE) TSN working group, it is a set of standards that provides deterministic connectivity within IEEE 802-aligned networks. Nigel Forrester is the Director of Product Strategy for Concurrent Technologies, a UK-based provider of high performance embedded computing solutions for aerospace, defense and many other industries. Check out our interview with Forrester about the potential impact of TSN Ethernet on new and legacy aerospace and defense applications, and how it is being adopted by manufacturers and system integrators below.
It is a fool's errand to make timely comments - in print! - about our current political turmoil. Even so, it feels important to place a marker in the sand to note the ongoing political reign of tariff threats, the upheaval potential of a demolished regulatory state affecting road and vehicle safety, and the damage that cuts to electric vehicle support might do to American automakers attempting to keep technological pace with their global automaker peers. It's a lot. The mainstream press is reporting the broad strokes of the industry's reaction to the new president. Ford CEO Jim Farley said Trump's erratic threats and changes are adding “a lot of cost and a lot of chaos” to the automotive industry and that a 25% tariff would “blow a hole in the U.S. industry that we've never seen.” Volvo Cars CEO Jim Rowan said that profitability would suffer under any tariffs, whether those are the general 25% tariffs on Canada and Mexico (now seemingly canceled after Trump backed down), just-announced
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.
Fused Deposition Modeling (FDM) is a highly adaptable additive manufacturing method that is extensively employed for creating intricate structures using a range of materials. Thermoplastic Polyurethane (TPU) is a highly versatile material known for its flexibility and durability, making it well-suited for use in industries such as footwear, automotive, and consumer goods. Hoses, gaskets, seals, external trim, and interior components are just a few of the many uses for thermoplastic polyurethanes (TPU) in the automobile industry. The objective of this study is to enhance the performance of Fused Deposition Modeling (FDM) by optimizing the parameters specifically for Thermoplastic Polyurethane (TPU) material. This will be achieved by employing a Taguchi-based Grey Relational Analysis (GRA) method. The researchers conducted experimental trials to examine the impact of key FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical responses
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
This SAE Recommended Practice establishes a procedure for the issuance and assignment of a World Manufacturer Identifier (WMI) on a uniform basis to vehicle manufacturers that may desire to incorporate it in their Vehicle Identification Numbers (VIN). This recommended practice is intended to be used in conjunction with the recommendations for VIN systems described in SAE J853, SAE J187, SAE J272, and other SAE reports for VIN systems. These procedures were developed to assist in identifying the vehicle as to its point of origin. It was felt that review and coordination of the WMI by a single organization would avoid duplication of manufacturer identifiers and assist in the identification of vehicles by agencies such as those concerned with motor vehicle titling and registration, law enforcement, and theft recovery.
Wire Electrical Discharge Machining (WEDM) is an essential manufacturing process used to shape complex geometries in conductive materials such as cupronickel, which is valued for its corrosion resistance and electrical conductivity. The aim of this explorative study is to enhance the efficiency and precision of machining by creating a specialized predictive model using an Adaptive Neuro-Fuzzy Inference System (ANFIS) for cupronickel material. The study examines the intricate correlation between process variables of the WEDM (Wire Electrical Discharge Machining) technique, such as pulse-on time (Ton), pulse-off time (Toff), and discharge current, and crucial machining responses, including surface roughness, material removal rate. Data is collected through systematic experimentation in order to train and validate the ANFIS predictive model. The ANFIS model utilizes the collective learning capabilities of neural networks and fuzzy logic systems to precisely forecast machining responses by
Additive Manufacturing (AM), specifically Fusion Deposition Modeling (FDM), has transformed the manufacturing industry by allowing the creation of complex structures using a wide range of materials. The objective of this study is to enhance the FDM process for Thermoplastic Polyurethane (TPU) material by utilizing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) optimization method. The study examines the influence of FDM parameters, such as layer height, nozzle temperature, and infill density, on important characteristics of the printing process, such as tensile strength, flexibility, and surface finish. The collection of experimental data is achieved by conducting systematic FDM printing trials that cover a variety of parameter combinations. The TOPSIS optimization method is utilized to determine the optimal parameter settings by evaluating each parameter combination against the ideal and anti-ideal solutions. This method determines the optimal parameter
Wire Electrical Discharge Machining (WEDM) is a highly accurate machining approach that is well-known for its capability to create intricate forms in materials with high levels of hardness and intricate geometries. Invar 36, a nickel-iron alloy, is extensively utilized in industries that demand exceptional dimensional stability across a wide temperature range. The objective of this exploration is for optimizing the WEDM parameters of Invar 36 material. Additionally, a predictive model called Adaptive Neuro-Fuzzy Inference System (ANFIS) will be developed to forecast the machining performance. The study involved conducting experimental trials to analyze the influence of crucial factors in WEDM. These parameters included pulse-on time (Ton), pulse-off time (Toff), and current. The objective was to examine their influence on key performance indicators such as material removal rate (MRR), surface roughness (Ra). The methodology of Design of Experiments (DOE) enabled a systematic
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
As we move towards sustainable transportation, it is essential to look for alternative powertrain technologies that might reduce emissions and depend less on fossil fuels. This paper offers a thorough analysis and comparison of several viable solutions along with their benefits, cost and conclusion for hydrogen fuel cells, solar cells, electric hybrid systems, compressed natural gas (CNG) and CNG hybrid systems alongside the latest proposal of using nuclear batteries. Hydrogen cars have zero emissions from their exhaust and can be refueled quickly, however there are some drawbacks like hydrogen production, storage, and infrastructure. The efficiency, affordability, and scalability of various hydrogen production techniques, fuel cell stack designs and storage technologies (compressed gas, liquid, and metal hydrides) are evaluated in this paper. Solar FCEVs on the other hand, are designed to utilize solar energy like Solar EVs but are very different in their operation and fundamentals
Wire Electrical Discharge Machining (WEDM) is a widely used manufacturing method that is employed to shape complex geometries in conductive materials such as cupronickel, which is highly regarded for its resistance to corrosion and ability to conduct heat. The aspiration of this investigation is to improve the effectiveness and accuracy of Wire Electrical Discharge Machining (WEDM) for cupronickel material by utilizing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) optimization method. The study analyzes the impact of WEDM parameters, specifically pulse-on time, pulse-off time, and discharge current, on important machining outcomes such as surface roughness, material removal rate. Experimental trials are performed to collect data on these parameters and their corresponding machining characteristics. The TOPSIS optimization method is utilized to determine the most favourable parameter settings by evaluating each parameter combination against the ideal and
Design and material choices can have a long-term impact on an original equipment manufacturer’s (OEM) production costs and product quality. When an OEM works together with an experienced contract design manufacturer (CDM) from the start of a project, many negative impacts to cost and quality can be avoided.
Whether for vascular catheters or implantable devices, medical tubing must meet tough standards for flexibility, strength, and biocompatibility. That’s why more manufacturers are turning to thermoplastic polyurethanes (TPUs) that strike the ideal balance between these key properties, making them an excellent choice for high-performance medical tubing. Unlocking the best that TPUs have to offer means optimizing the extrusion process. This article looks at why TPUs are a top pick, the common obstacles in extrusion, and the ways manufacturers can fine-tune their process to get the most out of different grades.
Industrial automation has traditionally been characterized by proprietary technologies and vendor-specific solutions. However, recent trends are shifting toward greater openness in both hardware and software, reflecting the evolving needs of end users, systems integrators (SIs), and original equipment manufacturers (OEMs).
In September, after several months of evaluating the market, “Honda Xcelerator Ventures” — the automotive manufacturer’s startup investment subsidiary — made a major investment award to California-based silicon photonics startup SiLC Technologies, Inc., to develop next generation Frequency-Modulated Continuous Wave (FMCW) LiDAR for “all types of mobility.”
Aerospace engine components like discs, blisks and rings are engineered to perform in extreme operating environments. They need to withstand intense heat and stress and be as lightweight as possible to meet exacting specifications. These parts are also notoriously difficult to machine, and manufacturers who work with them must meet serious challenges of their own. Holding tight tolerances, maintaining predictable tool life and accounting for internal material stress relief from material removal can be especially difficult when profiling complicated features such as thin-walled flanges, undercut pockets and seal fins.
A method for 3D printing called vapor-induced phase-separation 3D printing, or VIPS-3D, can create single-material as well as multi-material objects. The printing process allows manufacturers to create custom-made objects economically and sustainably.
High productivity, low manufacturing costs, and high workpiece quality: these are the key factors that deliver sustainability, profitability, and competitive edge for industrial manufacturers. Reliable machine monitoring yields valuable real-time insights into ongoing processes; it is the basis for dependable, productive, and reproducible manufacturing and it helps machine operators to reach well-founded decisions on both short- and long-term improvements. This technology can even capture anomalies in highly dynamic machining processes, so users can respond instantly to ensure high productivity, decrease scrap rates, and prolong tool lifetimes. Thanks to all these advantages, continuous machine and process monitoring based on suitable sensor technology is a critical success factor in today’s manufacturing industry.
Nowadays, Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs) are becoming popular globally due to increasing pollution levels in the environment and expensive conventional non-renewable fuels. Li-ion battery EV’s have gained attention because of their higher specific energy density, better power density and thermal stability as compared to other cell chemistries. Performance of the Li-ion battery is affected by temperatures of the cells. For Li-ion cells, optimum operating temperature range should be between 15-35 °C [1]. Initially, small battery packs which are cooled by air were used but nowadays, large battery packs with high power output capacities being used in EV’s for higher vehicle performance. Air based cooling system is not sufficient for such batteries, hence, liquid coolant based cooling systems are being introduced in EV’s. Computational Fluid Dynamics (CFD) simulation can be used to get better insight of cell temperature inside battery. But it is complex, time
The changing regulatory landscape and innovation of medical products is driving an interest in additional options for medical product sterilization. One nontraditional way manufacturers can sterilize medical products that is becoming increasingly popular is with sterilizers that use vaporized hydrogen peroxide (VH2O2). The publication of ISO 22441:2022 and its recognition by the United States Food and Drug Administration (US FDA), coupled with the FDA’s reclassification of VH2O2 sterilization as an Established Category A process in 2024, supports this modality of sterilization.
The automotive industry faces unprecedented regulatory and societal pressure to adopt sustainable manufacturing practices. A recent survey by Accenture shows that more than 34 percent of today’s largest manufacturers have committed to zero-emission goals, yet 93 percent of them will miss their targets unless they double their emission reduction rates by 2030.
Continental's Georg Fässler, executive chair of the 2024 SAE COMVEC, details efforts to future-proof forthcoming vehicles. Severe driver shortages, rising fuel and material costs, escalating demand for freight transport, higher sustainability requirements - there is no shortage of challenges facing the transport sector. Commercial vehicle manufacturers and industry suppliers are devoting significant resources to develop, test and bring to market the technological advances that will help alleviate these pressure points. “The digitalization of commercial vehicles and the whole logistics chain is a necessary response and one of the most important developments in the CV industry in my view,” said Continental Automotive's head of commercial and special vehicles, Georg Fässler, in a recent interview with SAE International.
Wysong USA has been manufacturing industrial press brakes, hydraulic shears, and mechanical shears for sheet metal and plastics for nearly 120 years. Like many companies, their motto was “if it ain’t broke, don’t fix it,” so their product had remained essentially the same. But during a customer visit that motto clashed with another company saying, “the customer is always right.” This customer had replaced the dry clutch brake for an oil shear clutch brake that was more accurate. “The customer is always right” won, so Wysong updated their product line and increased accuracy while reducing costs, making it a win all around.
Sustainability remains a dominant trend in packaging and processing, continuing to attract the attention of the life sciences industry and inspire its new initiatives. Although pharmaceutical and medical device manufacturers must prioritize patient safety and product protection, concerns about climate change, greenhouse gas (GHG) emissions, plastic waste, and pressure to move toward a circular economy are prompting a greater focus on improving the sustainability of their products and packaging.
Airplane manufacturers running noise tests on new aircraft now have a much cheaper option than traditional wired microphone arrays. And it’s sensitive enough to help farmers with pest problems. The wireless microphone array that one company recently created with help from NASA can locate crop-threatening insects by listening for sound they make in fields. And now, it’s making fast, affordable testing possible almost anywhere.
Squeak and rattle (SAR) noise audible inside a passenger car causes the product quality perceived by the customer to deteriorate. The consequences are high warranty costs and a loss in brand reputation for the vehicle manufacturer in the long run. Therefore, SAR noise must be prevented. This research shows the application and experimental validation of a novel method to predict SAR noise on an actual vehicle interior component. The method is based on non-linear theories in the frequency domain. It uses the Harmonic Balance Method (HBM) in combination with the Alternating Frequency/Time Domain Method (AFT) to solve the governing dynamic equations. The simulation approach is part of a process for SAR noise prediction in vehicle interior development presented herein. In the first step, a state-of-the-art linear frequency-domain simulation estimates an empirical risk index for SAR noise emission. Critical spots prone to SAR noise generation are located and ranked. In the second step, the
For years, expertise in terrestrial applications has served as a launchpad for innovation. Companies honed their skills by building the networks that connected us on earth, but now, eyes are turning skyward. By adapting their capabilit ies to the unique demands of non-terrestrial applications, these same players are unlocking new possibilities and rewriting the rules of communication beyond the atmosphere. Here, Dan Rhodes, Director of Business Development at designer and manufacturer of RF-to-mmWave components and subsystems, Filtronic, explores the bridge between terrestrial expertise and non-terrestrial ambitions, highlighting how terrestrial success is becoming the fuel for stellar solutions. Bridging the terrestrial and non-terrestrial worlds is not merely a matter of applying existing technologies to a new canvas. While both environments share fundamental principles of communication and rely on robust components such as transmitters, receivers, filters and amplifiers, the shift
An SAE white paper on the different engineering approaches taken by traditional automakers and recent arrivals indicates that each category is remarkably aware of the others' strengths and weaknesses. Sven Beiker, a management lecturer at Stanford University, authored the report “Two Approaches to Mobility Engineering.” He gathered commentary from every corner of the vehicle ecosystem, from suppliers to software companies to manufacturers, and summarized the findings in a presentation at WCX 2024 in Detroit. Rather than “old companies,” Beiker likes to refer to traditional automakers as “incumbents.” Here are a few common observations from the report, which will be published this summer: Newer players are better at simplifying complexity, such as Tesla's ability to build vehicles with fewer parts. Older automakers are better at managing complexity, such as integrating disparate systems. Newer companies are constrained by financial resources and a shortage of available talent
The global medical device market offers opportunities for innovation-driven growth. Demand for smart, new lifesaving and life-enhancing technologies is perhaps stronger than ever. Manufacturers around the world looking to capitalize on this eager global market face a long list of challenges — some big, some small. Supply-chain disruptions, labor shortages, rising materials costs, and other headwinds are leading to delays in both engineering and manufacturing processes. Despite these challenges, the world demands medical device manufacturers’ best. A surging geriatric population, implications of a global pandemic, and the mortality rates for heart disease, cancer, obesity, and other conditions are all contributing to strong and sustained market demand. One study predicts a compound annual growth (CAGR) of 5.4 percent will push global sales of medical devices to nearly $658 billion (USD) by 2028. Of course, the road to success will be littered with familiar roadblocks — and some that are
For a couple of decades, virtually every global original equipment manufacturer spent significant capital and attention raising their sales/production profile in China. It became the world's largest light vehicle market by 2010 and has not looked back. Forming new joint ventures to expand their portfolios through the extension of global offerings, several OEMs even took the opportunity to design China-specific variants. Western OEMs followed these JVs, and scores of European, North American, Japanese and Korean Tier 1 and 2 suppliers followed their OEMs, creating a local supply of global components as China became an integral cog in the machine. A presence in China is core to success for many industry players. China produced about 28 million light vehicles in 2023, based on S&P Global Mobility's estimates. China is not only key for Western OEM profitability, from a volume perspective it is the largest single market (about 31% of the world in 2023) with the highest growth profile. It
The pace of innovation in automotive and heavy-duty transportation is rapidly accelerating. Manufacturers are harnessing advancements in electrification and electronification, ushering in new levels of safety, comfort, infotainment, connectivity, performance, and sustainability.
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