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AS13002 defines the process for qualifying an Alternate Inspection Frequency Plan for suppliers within the aero-engine sector.  This two-day course will provide common requirements for developing and qualifying an alternate inspection plan, other than 100% inspection of all features.  This course is designed to cover the basic elements of the process to be applied to design characteristics (as defined in AS9102), and parts or inspection processes as defined by the purchaser.

In the Aerospace Industry there is a focus on Defect Prevention to ensure that quality goals are met. Failure Mode and Effects Analysis (PFMEA) and Control Plan activities are recognized as being one of the most effective, on the journey to Zero Defects. This two-day course is designed to explain the core tools of Design Failure Mode and Effects Analysis (DFMEA), Process Flow Diagrams, Process Failure Mode and Effects Analysis (PFMEA) and Control Plans as described in AS13100 and RM13004. It will show the links to other quality tools such as Characteristics Matrix and Measurement Systems Analysis (MSA).

The international standards D-326A (U.S.) and ED-202A (Europe) titled "Airworthiness Security Process Specification" are the cornerstones of the "DO-326/ED-202 Set" and they are the only Acceptable Means of Compliance (AMC) by FAA & EASA for aviation cyber-security airworthiness certification, as of 2019.

Vehicle Acoustic Prototyping in the mid to high frequency range is challenging with numerical models only. To overcome this challenge, over the past decade, experimental techniques were developed that allow the engineer to incorporate Test-Based models in the simulation as well. Using Virtual Point Technology these Test-Based models serve well to describe, for example, the complex dynamics of the vehicle body / NTF. Here the high modal density and damping characteristics are simply measured on a mule or prototype vehicle and coupled using Dynamic Substructuring to cover the mid and high frequency ranges as well. As such accurate predictions and / or risk assessments can be made much earlier in the vehicle development stage. While test-based models serve well to describe the coupled vehicle dynamics, loads to compute actual vehicle responses are needed as well. Here so-called Equivalent or Blocked Forces are ideal as they are found to be independent of the vehicle dynamics.

Active Safety, Advanced Driver Assistance Systems (ADAS) are now being introduced to the marketplace as they serve as key enablers for anticipated autonomous driving systems. Automatic Emergency Braking (AEB) is one ADAS application which is either in the marketplace presently or under development as nearly all automakers have pledged to offer this technology by the year 2022. This one-day course is designed to provide an overview of the typical ADAS AEB system from multiple perspectives.

To accelerate development and improve the quality of car navigation systems, we have built a system for automatic generation of evaluation courses. In general, the operation of car navigation systems is verified by driving tests using vehicles. The evaluation courses need to be designed so that inspection sites, such as underground parking lots, tunnels, etc., will be visited during the evaluation period. They should be circuits that include as many inspection sites as possible within a defined distance. However, as the number of the inspection sites increases, the number of courses that can be designed becomes enormous. This makes it difficult to create courses that meet all of the requirements. Hence engineers have spent a lot of time on evaluation course design. For this reason, automatic course generation has become essential for reducing man-hours.

Contemporary cutting-edge technologies, such as automated driving brought up vital questions about safety and relativized the safety assurance and acceptance criterion on different aspects. New risk assessment, evaluation, and acceptance justifications are required to assure that the assumptions and benchmarking are made on a reasonable basis. While there are some existing risk evaluation methods, most of them are qualitative in nature and are subjective. Moreover, information such as the safety performance indicators (SPIs) of the sensors, algorithms, and actuators are often not utilized well in these methods. To overcome these limitations, in this paper we propose a risk quantification methodology that uses Bayesian Networks to assess if the residual risk is reasonable under a given scenario.

X-Domain describes the merging of different domains (i.e., braking, steering, propulsion, suspension) into single functionalities. One example in this context is torque-vectoring. Different goals can be pursued by applying X-Domain features. On the one hand, savings in fuel consumption and an improved vehicle driving performance can be potentially accomplished. On the other hand, safety can be improved by taking over a failed or degraded functionality of one domain by other domains. The safety-aspect from the viewpoint of requirements is highlighted within this contribution. Every automotive system being developed and influencing the vehicle safety must fulfill certain safety objectives. These are top-level safety requirements (ISO 26262-1) specifying functionalities to avoid unreasonable risk. Every safety objective is associated with an Automotive Safety Integrity Level (ASIL) derived from a Hazard Analysis and Risk Assessment (HARA).

Maintaining and diagnosing vehicle systems often involves a technician connecting a service computer to the vehicle diagnostic port through a vehicle diagnostics adapter (VDA). This creates a connection from the service software to the vehicle network through a protocol adapter. Often, the protocols for the personal computer (PC) hosted diagnostic programs use USB, and the diagnostic port provides access to the controller area network (CAN). However, the PC can also communicate to the VDA via WiFi or Bluetooth. There may be scenarios where these wireless interfaces are not appropriate, such as maintaining military vehicles. As such, a method to defeature the wireless capabilities of a typical vehicle diagnostic adapter is demonstrated without access to the source code or modifying the hardware. The process of understanding the vehicle diagnostic adapter system, its hardware components, the firmware for the main processor and subsystems, and the update mechanism is explored.

Accurate sensing of road conditions is one of the necessary technologies for safe driving of intelligent vehicles. Compared with the structured road, the unstructured road has complex road conditions, and the response characteristics of vehicles under different road conditions are also different. Therefore, accurately identifying the road categories in front of the vehicle in advance can effectively help the intelligent vehicle timely adjust relevant control strategies for different road conditions and improve the driving comfort and safety of the vehicle. However, traditional road identification methods based on vehicle kinematics or dynamics are difficult to accurately identify the road conditions ahead of the vehicle in advance. Therefore, this paper proposes an unstructured road region detection and road classification algorithm based on machine vision to obtain the road conditions ahead.

Remote Monitory and Teleoperation (RMTO) of Autonomous Vehicle (AV) has been advancing in pace in the industry. Researchers and industrial partners have been exploring the role RMTO plays in helping AV navigate through complicated situations among many others. At the heart of this, lies the problem of potential pathways and attack vectors or threat surfaces by which a malicious attack can be carried out on a RMTO as well as on an AV itself. The separation of cybersecurity consideration in RMTO in comparison to AV has barely been touched upon, as most available research and consideration has mainly been focused on AV. The main focus of this paper is resolving the first problem by utilizing an adaptable security-by-design approach. Though security-by-design is still in the infant state within the automotive cybersecurity.

This SAE Standard defines methods and apparatus to evaluate electronic devices for immunity to potential interference from conducted transients along battery feed or switched ignition inputs. Test apparatus specifications outlined in this procedure were developed for components installed in vehicles with 12-V systems (passenger cars and light trucks, 12-V heavy-duty trucks, and vehicles with 24-V systems). Presently, it is not intended for use on other input/output (I/O) lines of the device under test (DUT).

This SAE Aerospace Recommended Practice (ARP) is not a certification document; it contains no certification requirements beyond those already contained in existing certification documents. The purpose of this ARP is to provide: a Guidelines for potential usage of life samples depending upon the mission environment and at user discretion to use them or not. b Guidelines of: 1 Who approves the parts to be used. 2 Notification requirements to manufacturers. 3 Traceability and segregation. 4 Packing and labeling of such parts. This ARP does not claim that the recommended practices and artifacts described herein are the only acceptable ones. They are, however, used widely today, and merit serious consideration of potential usage where applicable in the military and space hardware. This ARP does not supersede any contracts or legal agreements between contractual parties.

THIS STANDARD ESTABLISHES THE DIMENSIONAL AND VISUAL QUALITY REQUIREMENTS, LOT REQUIREMENTS AND PACKAGING AND LABELING REQUIREMENTS FOR O-RINGS MOLDED FROM AMS7361 (ETHYLENE-PROPYLENE) RUBBER WHICH IS ABLE TO PROVIDE THE REQUIRED SEALING PERFORMANCE IN STATIC APPLICATIONS AT TEMPERATURES DOWN TO -75 °F (-59 °C). IT SHALL BE USED FOR PROCUREMENT PURPOSES.

Traditional solutions developed for the aerospace industry must overcome challenges posed for automation systems like design, requalification, large manual content, restricted access, and tight tolerances. At the same time, automated systems should avoid the use of dedicated equipment so they can be shared between jigs; moved between floor levels and access either side of the workpiece. This article describes the development of a robotic system for drilling and inspection for small aerostructure manufacturing specifically designed to tackle these requirements. The system comprises three work packages: connection within the digital thread (from concept through to operational metrics including Statistical Process Control), innovative lightweight / low energy drill, and auto tool-change with in-process metrology. The validation tests demonstrating Technology Readiness Level 6 are presented and results are shown and discussed.

The advent of the Covid-19 pandemic that began at the end of 2019 accelerated technology to support remote work environments. While the technologies were not new, the capabilities of those technologies significantly increased. The number of users embracing the remote working technologies significantly increased within a very short timeframe. The expanded remote work capabilities have enabled new collaborating mechanisms that will carry-forth in the future, pandemic or not. SAE ARP 4761 [1] provides guidelines to perform a safety assessment. The Zonal Safety Assessment (ZSA) is one of the tools described in ARP 4761. An aspect of ZSA is an audit (or inspection) of the physical article. The remote work capabilities, along with cameras and software presenting a virtual environment, can allow individuals to participate in the physical audit without traveling to the site of the physical article.