Browse Topic: Quality management systems
The intention of this exploration is to evolve an optimization method for the Electrochemical Machining (ECM) process on Haste alloy material, taking into account various performance characteristics. The optimization relies on the amalgamation of the Taguchi method with an Adaptive Neuro-Fuzzy Inference System (ANFIS). Haste alloy is extensively utilized in the aerospace, nuclear, marine, and car sectors, specifically in situations that are prone to corrosion. The experimental trials are organized based on Taguchi's principles and involve three machining variables: feed rate, electrolyte flow rate, and electrolyte concentration. This examination examines performance indicators, including the pace at which material is removed and the roughness of the surface. It also includes geometric factors such as overcut, shape, and tolerance for orientation. The results suggest that the rate at which the feed is supplied is the most influential element affecting the necessary performance standards
The aim of this study is to create an Adaptive Neuro-Fuzzy Inference System (ANFIS) model for the Electrochemical Machining (ECM) process using Nimonic Alloy material, with a specific focus on several performance aspects. The optimization strategy utilizes the combination of the Taguchi method and ANFIS integration. Nimonic Alloy is widely employed in the aerospace, nuclear, marine, and car sectors, especially in situations that are susceptible to corrosion. The experimental trials are designed according to Taguchi's method and involve three machining variables: feed rate, electrolyte flow rate, and electrolyte concentration. This study investigates performance indicators, such as the rate at which material is removed, the roughness of the surface, and geometric characteristics, including overcut, shape, and tolerance for orientation. Based on the analysis, it has been determined that the feed rate is the main component that influences the intended performance criteria. In order to
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
The objective of this research is to develop an optimization strategy for the Electrochemical Drilling process on Nimonic alloy material, taking into account various performance factors. The optimization strategy relies on the integration of the Taguchi method with Grey Relational Analysis (GRA). Nimonic is extensively utilized in aerospace, nuclear, and marine industries, specifically in situations that are prone to corrosion. The experimental trials are structured based on Taguchi's principle and encompass three machining variables: feed rate, electrolyte flow rate, and electrolyte concentration. This inquiry examines performance indicators like the rate of material removal, surface roughness, as well as geometric parameters such as overcut, shape, and orientation tolerance. Based on the investigation, it is determined that the feed rate is the primary factor that directly affects the intended performance criteria. In order to enhance the accuracy of predictions, multiple regression
Additive Manufacturing (AM), specifically Fused Deposition Modeling (FDM), has become a highly promising method for creating intricate shapes using different materials. Polyethylene Terephthalate Glycol (PETG) is a highly utilized thermoplastic that is recognized for its exceptional strength, resistance to chemicals, and effortless processing. This study aims to optimize the process parameters of the FDM technique for PETG material using Taguchi Grey Relational Analysis (GRA). An empirical study was carried out to examine the impact of various FDM process parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on important outcome variables like dimensional accuracy, surface quality, and mechanical properties. The Taguchi method was used to systematically design a series of experiments, while GRA was used to optimize the process parameters and performance characteristics. The results unveiled the most effective parameter combinations for attaining
Spot welds are integral to automotive body construction, influencing vehicle performance and durability. Spot welding ensures structural integrity by creating strong bonds between metal sheets, crucial for maintaining vehicle safety and performance. It is highly compatible with automation, allowing for streamlined production processes and increased efficiency in automotive assembly lines. The number and distribution of spot welds directly impact the vehicle's ability to withstand various loads and stresses, including impacts, vibrations, and torsion. Manufacturers adhere to strict quality control standards to ensure the integrity of spot welds in automotive production. Monitoring spot weld count and weld quality during manufacturing processes through advanced inspection techniques such as Image processing by YOLOv8 helps identify the number of spots and quality that could compromise safety. Automating quality control processes is paramount, and machine vision offers a promising
Wire Electrical Discharge Machining (WEDM) is an important method engaged to make intricate shapes in conductive materials like Cupronickel, which is well-known for its ability to resist corrosion and conduct heat. The intention of this exploration is to enhance the effectiveness and accuracy of Wire Electrical Discharge Machining (WEDM) for Cupronickel material by utilizing a Taguchi-based Grey Relational Analysis (GRA). The study examines the impact of WEDM parameters, specifically pulse-on time, pulse-off time, and discharge current, on key machining outcomes such as surface roughness (Ra), material removal rate (MRR). A comprehensive dataset is generated for analysis through a systematic series of experiments designed using the Taguchi method. Grey relational grades are assessed to measure the connections between the input parameters and machining responses, making it easier to determine the best parameter settings. The Taguchi-based GRA approach provides a systematic approach for
In recent years, battery electric vehicles (BEVs) have experienced significant sales growth, marked by advancements in features and market delivery. This evolution intersects with innovative software-defined vehicles, which have transformed automotive supply chains, introducing new BEV brands from both emerging and mature markets. The critical role of software in software-defined battery electric vehicles (SD-BEVs) is pivotal for enhancing user experience and ensuring adherence to rigorous safety, performance, and quality standards. Effective governance and management are crucial, as failures can mar corporate reputations and jeopardize safety-critical systems like advanced driver assistance systems. Product Governance and Management for Software-defined Battery Electric Vehicles addresses the complexities of SD-BEV product governance and management to facilitate safer vehicle deployments. By exploring these challenges, it aims to enhance internal processes and foster cross
This specification covers metric aircraft quality spacers for use as positioners for tubes, flat washers for use as load spreaders, galling protection of adjacent surfaces and or material compatibility, and key or tab washers for use as locks for bolts, nuts, and screws.
An industry-first 3D laser-based, computer-vision system can monitor and control the application of adhesive beads as tiny in width as two human hairs. This unique inspection system for electronic assemblies operates at speeds of 400 to 1,000 times per second, considerably quicker and more effective than conventional 2D systems. “Difficulty in precisely dispensing adhesives or sealants, especially in extremely small or complex electronic assemblies, can lead to over-application, under-application, bubbles, or incorrect location of the adhesive bead,” Juergen Dennig, president of Ann Arbor, Michigan-headquartered Coherix, told SAE Media. Improper application of joining material on electronic control units (ECUs) and power control units (PCUs) can result in poor adhesion, material voids and short circuits.
Vehicle HVAC noise performance is an important vehicle design validation criterion since it significantly links the brand image of a vehicle. It affects the customer’s buying decision and the business of selling vehicles because it directly affects driving comfort. Customers expect continuous improvement in HVAC noise without compromising cooling performance. The process of cascading vehicle-level acoustic performance to subsystem and component levels becomes an important factor in the vehicle NVH development process. It was found that the component-level [HVAC unit without duct] performance of an HVAC system measured in an anechoic chamber was at par when compared to targets, whereas the subsystem-level performance [HVAC unit with duct and dashboard] was on the higher side of the targets. Advanced NVH tools were used to identify the source of noise at the subsystem level. It helped to locate the source and its transfer path. A design modification done at the transfer path location
This standard defines the minimum requirements for conducting Measurement Systems Analysis (MSA) for variable and attribute assessment on characteristics as defined on the drawing or specification. It does not define the detailed analytical methods for each type of study as these can be found in existing published texts (see Section 2 for guidance).
This document establishes age limit and guidance for acceptance of hose and hose assemblies containing elastomeric materials for use in aircraft, space vehicles, missiles and component assemblies thereof at time of delivery to the contractor, procuring activity, or contracting officer. This document does not establish limitations on storage times for military/civil activities nor operating life.
To provide a method by which to assess the cleanliness of new hydraulic fluids. The method is applicable to new mineral and synthetic hydraulic fluids - regardless of packaging. This SAE Standard is not intended as a procedure for operating equipment.
This SAE Aerospace Recommended Practice (ARP) covers the requirements for the types of glass to be utilized in the fabrication of cover glasses and lighting wedges used in aerospace instruments. It defines the maximum extent of physical defects and recommends standard methods of inspection and evaluation. Definitions of terminology used in this document are covered in 2.2.
Military performance requirements for adhesives have been traditionally derived to fulfill niche defense needs in harsh operational environments with little consideration for dual-use commercial potential. U.S. Army Research Laboratory, Aberdeen, MD The term “military-grade” can have a variety of meanings that are perspective dependent. In 2014, Ford Motor Company emphasized the term heavily in advertising campaigns to garner consumer acceptance for the transition from steel to aluminum in the body of their flagship F150 model. As cited by Ford, “Engineers selected these high-strength, military-grade aluminum alloys because of the metals' unique ability to withstand tough customer demands.” From this point-of-view, military-grade implies superior performance. However, the bureaucratic and logistical barriers required for certification to military-grade acceptance levels per DoD performance requirements can also be perceived as impediments to innovation and the transition of fundamental
A company says that its digital twin alignment system, incorporating a sophisticated AI algorithm and an off-the-shelf camera, has the potential to revolutionize the auto industry, potentially saving it up to a staggering $20 billion in the effort to detect defects on the manufacturing line. Generally, such inspections of spot welds, bolt holes and the like are handled one of three ways: Slow manual inspections that can have high error rates. Even slower inspection with coordinate-measuring machines (CMMs) that can take hours to inspect 150 spot welds. Tremendously expensive technology, such as lasers, that still aren't perfect.
Due to manifold benefits compared to proprietary software solutions, free and open source software (FOSS) in general, and Linux especially becomes more and more relevant for embedded solutions in the automotive domain, especially in High Performance Computing Platforms (HPC). However, taking over liability and warranty for a FOSS-based problem raises the problem of software quality assurance, and thus risk control. In order to control and minimize the residual risk of a product or service, the traditional and well-accepted measure in the automotive domain is to assess the engineering processes and resulting work products via a process assessment model given by the ASPICE maturity model, as well as requirements from functional safety standards for safety related functions. The underlying process reference model of ASPICE covers software development performed and controlled by an organization. However, this situation is not given by and even contrary to the nature of FOSS development
This specification covers a carbon steel in the form of wire supplied as coils, spools, or cut lengths (see 8.2).
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