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We show also other applications, where AI can be an excellent tool to evaluate vehicle acoustics. We emphasize the relation of AI to Speech Intelligibility and make considerations concerning other factors influencing Intelligibility. ...The paper presents the concepts and applications regarding Articulation Index (AI) that is widely used in the automotive industry as a powerful parameter to qualify/quantify the middle and high frequency spectra associated to the internal noise of vehicles. ...Finally we discuss the results presented and identify the position of AI in the general context/vision of the parameters that are available in vehicle acoustics.

Artificial intelligence (AI) is the branch of computer science committed to attaining and exceeding the intelligence of the human brain, primarily by innovative software technology. ...The objective of this paper is to provide an overview of AI applications, tools and techniques and to assist and encourage renewed initiative in research, development and applications of AI enhanced expert systems and robotics for the benefit of our industry. ...The objective of this paper is to provide an overview of AI applications, tools and techniques and to assist and encourage renewed initiative in research, development and applications of AI enhanced expert systems and robotics for the benefit of our industry.

With an initial focus on critical fight management systems, the committee will evaluate applications for AI usage in aviation and aerospace and will propose standards to support implementation and certification

The new Advanced Technology and Training Center (ATTC), which opened yesterday after a ribbon-cutting ceremony, will focus on breakthroughs in condition-based maintenance and the intersection of artificial intelligence (AI), robotics, and automation within that domain.

This document discusses guidelines for the development of Aircraft Systems leveraging AI capabilities, taking into account the overall aircraft operating environment and functions. This includes validation of requirements and verification of the design implementation for certification and product assurance and guidelines with the assessment of safety.

These areas include diagnostics, training, planning and scheduling, process monitoring, control and simulation. AI has been used extensively within Texas Instruments to improve manufacturing productivity and quality. ...Some examples of these internal applications, as well as external customer programs, are used to illustrate AI's potential for the factory of the future.

A “toolbox” approach to systematizing the application of AI tools is described. A recommended overall approach for successful application development is suggested.

However, this requires models based on the physics of the system to be built into the digital twin, links to data from sensors on the real live system, and sophisticated algorithms incorporating artificial intelligence (AI) and machine learning (ML). All of this can be used for integrated vehicle health management (IVHM) decisions, such as determining future failure, root cause analysis, and optimized energy performance. ...The Adoption of Digital Twins in Integrated Vehicle Health Management, however, still has a range of unsettled topics that cover technological reliability, data security and ownership, user presentation and interfaces, as well as certification of the digital twin’s system mechanics (i.e., AI, ML) for use in safety-critical applications. Click here to access the full SAE EDGETM Research Report portfolio.

This paper identifies the need for AI based tools to supplement CAD/FEA methods. The approach discussed focuses on the capture and feedback of part based case lessons or issues that form a knowledge base for future use.

A ‘Discriminating Cost Model’ was developed to capture the cost effectiveness of a given choice of process or equipment, and an AI (Artificial Intelligence) search algorithm implemented to quickly search through the large number of process and equipment selection options to arrive at the most cost effective choice.

The major difference between the STI and the widely used Articulation Index (AI) is that the calculation of STI takes into account both, the background noise at the talker's position and the alteration of the of the speech signal due to its transmission between the talker and the listener.

By integrating artificial intelligence (AI) technology into the vehicle’s embedded electronics, automakers and fleet owners can benefit from highly effective and adaptable vehicle health management capabilities that are not available today.

Vibration data and artificial intelligence (AI) algorithms were used to predict conditions. It was developed and installed so that maintenance engineers could predict failures in advance. ...Two different AI algorithm models were developed to recognize and predict changes in equipment state. First, 1D-CNN (Convolutional Neural Network) was used as a model for initially recognizing rapid changes in vibration trend.

The recent emergence of powerful artificial intelligence (AI) software development tools promises to reduce the time and effort associated with transforming an expert's knowledge into the operational software system required to implement automatic shutdown avoidance. ...To conduct an evaluation of the applicability of using AI techniques for life support processes, the National Aeronautics and Space Administration (NASA) developed a prototype expert system for automated fault detection, isolation, and correction of a regenerative carbon dioxide (CO2) removal subsystem.

Artificial intelligence becomes a reality Automakers could be among the leaders in deploying AI in free-standing, high-reliability environments. But developers must determine how to mitigate undesirable side-effects.

Artificial intelligence (AI), specifically machine learning technology, shows future promise in the VHM space, but it is not currently adequate by itself for high-accuracy analytics.

Innovations in Mobility: Aerospace Digital Summitaerospace mobility leaders convene leverage cutting-edge technology, design, develop safety measures, integrate current regulations, suggest future policies, expand markets, diversify revenue streams.

MIL-STD-1553, Aircraft Internal Time Division Command/Response Multiplex Data Bus, is a military standard which has become one of the basic standardization tools being used by the DOD for avionic interfaces. The standard describes the method of communication and the electrical interface requirements for devices using this standard. The 1 Mbps serial communication bus is the prime integration scheme for electronic devices in military avionics today. This paper addresses the application of the standard to military avionic integrations, describes the scope of the standard, the technical issues resolved in selecting the particular approach, and describes several military avionic examples using the standard.

The exploration of substantial money-saving areas of suitable usage for ECM (Electrochemical Metallizing) on aircraft components which are not in the purview of the original equipment manufacturer. The focus of the paper is upon the less spectacular maintenance opportunities rather than the much discussed repair of landing gear and engine components, all of which are strictly controlled by manufacturer's specifications because of safety considerations. Non-critical parts only require documented engineering specifications which are controlled by internal corporate engineering management. Our objective is to present areas of cost savings available to maintenance departments which have frequently been overlooked in the past. The perceived need is for some presentation of examples of applications which can be found in the normal day-to-day operations of aircraft maintenance activities so that similar opportunities may be identified and acted upon.

Document possible AI technologies, architecture, validation approach, and safety concerns for each use case.