The avionics hardware industry world-wide is now commonly required to follow DO-254 Design Assurance Guidance for Airborne Electronic Hardware for literally all phases of development: Safety, Requirements, Design, Logic Implementation, V&V, Quality Assurance, etc. The DO-254 standard is a companion to the software DO-178B standard; however, there are many differences between hardware and software which must be understood. This basic course introduces the intent of the DO-254 standard for commercial avionics hardware development.
Individuals responsible for quality management system, implementation, and auditing to the AS9100:2016 series of standards for Aviation, Space, and Defense will require an understanding of the requirements for the preparation and execution of the audit process as defined in these revised standards. Management and implementers of AS9100:2016 Rev. D within these organizations must also be aware of what these requirements mean for their company.
Every year, the U.S. on average, experiences more than 34,000 traffic deaths and over 5 million vehicle crashes. While the trend in traffic deaths has been generally downward for the past decade, most of this reduction has been the result of optimizing passive occupant crash protection systems such as seatbelts and airbags. Highly automated vehicle's (HAV's) offer the potential to significantly reduce vehicle crashes by perceiving a dangerous situation before the crash has occurred and supporting the human driver with proactive warnings and in some cases active interventions to avoid or mitigate the crash.
.Advanced Driver Assist System (ADAS) and autonomous vehicle technologies have disrupted the traditional automotive industry with potential to increase safety and optimize the cost of car ownership. Light detection and ranging (LIDAR) sensing, a sensing method that detects objects and maps their distances, is seeing rapid growth and adoption in the industry. However, the sensor requirements and system architecture options continue to evolve. This course will provide the foundation on which to build LIDAR technologies in automotive applications.
Advanced Driver Assist System (ADAS) and autonomous vehicle technologies have disrupted the traditional automotive industry with potential to increase safety and optimize the cost of car ownership. Among the challenges are those of sensing the environment in and around the vehicle. Infrared camera sensing is seeing a rapid growth and adoption in the industry. The applications and illumination architecture options continue to evolve. This course will provide the foundation on which to build near infrared camera technologies for automotive applications.
Part 21 is the FAA regulation that provides the regulatory framework to conduct certification of products and parts. This includes the engineering, airworthiness, production and quality systems. The aerospace industry is hinged around compliance with Part 21; however, comprehension of Part 21 and its role in civil certification is challenging. This course is designed to provide participants with an understanding of the processes that encompass aircraft certification, including compliance with FARs, certification procedures and post certification responsibilities.
This 3-day advanced-level course provides an in-depth explanation of how to use tolerance stacks to analyze product designs and how to use geometric tolerances in stacks. The course can be conducted in three eight-hour sessions or with flexible scheduling, including five mornings or five afternoons. You’ll learn the essential methods and concepts used for creating 1D part and assembly tolerance stacks. The course discusses how virtual condition affects part assembly, stack methods, and using the stack form and spreadsheet.
The Robotics for AV Systems Bootcamp was developed by SAE International and Clemson University, with industry guidance from Argo AI. This rigorous, twelve-week, virtual-only experience is conducted by leading experts in industry and academia. You’ll develop a deep, technical understanding of how to build autonomous systems by learning to program a mobile robot through hands-on approaches using ROS, Gazebo, and Python.