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.
HMI design is an Interdisciplinary, which is based on human cognitive psychology and combines humanities, sociology, aesthetics, information science and other disciplines. While automotive technologies can be applied regardless of regions, HMI must be localized, as it is closely related to regional culture, people's living habits and characteristics. At the same time, HMI design has its own complete theoretical system, research and design methods and testing methods, instead of relying on experience. The purpose of this course is to equip people involved in the automotive industry with a basic sense of HMI design of vehicles.
Static perceptual quality is the term applied to the customer’s first impression of a car at the beginning of the buying process including how it looks, feels, and smells. This “first feeling” largely determines whether the customer continues through the purchase process. At present, OEMs have no systematic method for static perceptual quality in the whole vehicle design and development process, especially for the static perceptual quality review in the early stage of design and development before data freezing. Usually, it can only be evaluated after the vehicle is produced and assembled.
Due to the increasing computational power, significant progress has been made over the past decades when it comes to CAD, multibody and simulation software. The application of this software allows to develop products from scratch, or to investigate the static and dynamic behavior of multibody models with remarkable precision. In order to keep the development costs low for highly sophisticated products, more precisely motorcycle rider assistance systems, it is necessary to focus extensively on the virtual prototyping using different software tools. In general, the interconnection of different tools is rather difficult, especially when considering the coupling of a detailed multibody model with a simulation software like MATLAB Simulink. The aim of this paper is to demonstrate the performance of a motorcycle rider assistance algorithm using a cosimulation approach between the free multibody software called FreeDyn and Simulink based on a sophisticated multibody motorcycle model.