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2017-10-18 ...
  • October 18-19, 2017 (8:30 a.m. - 4:30 p.m.) - Troy, Michigan
Training / Education Classroom Seminars
Organizations are becoming increasingly aware of the importance of developing secure software. This seminar introduces students to the concepts of software assurance which have direct application in all software industries, including automotive and aerospace sectors. The intent of this seminar is to give students an appreciation of the technical challenges associated with software assurance while developing the technical skills necessary to engineer secure software. Performing input validation is imperative when developing secure software systems as this seminar will demonstrate.
2017-06-28 ...
  • June 28-30, 2017 (8:30 a.m. - 4:30 p.m.) - Warrendale, Pennsylvania
  • September 27-29, 2017 (8:30 a.m. - 4:30 p.m.) - Warrendale, Pennsylvania
Training / Education Classroom Seminars
Internal audits (a requirement of the AS9100 Rev D Standard) are intended to verify the compliance and effectiveness of the organization's quality management system. Internal auditors must be knowledgeable of these requirements and the expectations as identified in the standard. In addition, the audit requirements outlined in the AS9101 Standard have significantly changed the way auditors are expected to conduct audits in the aviation, space and defense industries.
2017-04-24 ...
  • April 24-25, 2017 (8:30 a.m. - 4:30 p.m.) - Troy, Michigan
  • October 16-17, 2017 (8:30 a.m. - 4:30 p.m.) - Troy, Michigan
Training / Education Classroom Seminars
Embedded hardware is everywhere you look today from your vehicle’s infotainment system to refrigerator to medical devices and everything else in-between. With so much exposure one would think that such devices are secure against attack; however, sadly for a large number of devices this is not the case. For proof, just look no further than your local news reports. They are full of reports on devices being hacked into. So, as engineers, how do we go about first identifying and mitigating (or capitalizing) the potential security vulnerabilities within these devices?
CURRENT
2017-04-18
Standard
AS6416
This SAE Aerospace Standard provides definitions for terms and requirements used in SAE AS procurement specifications for fasteners (bolts, screws, studs, nuts, and other threaded parts).
2017-04-06
Event
The Mobility History Committee has as its mission to link the lessons of the past to the present and, with such an understanding, to support the platform for future developments.
2017-04-05
Event
Internet of Things joins everything: the customer, the OEMs, the Suppliers, hardware, software, safety, security, networks, storage, cloud and anything else you can think of connected to the internet. There are changes in paradigms, products, business models, sheer volume of data and the speed in which everything works. Learn about the technologies, strategies, integration, standards, products, needs, predictions and societal changes that IoT is driving. Meet the people that make it happen.
2017-04-05
Event
Business Modeling/Operation Research/Big Data Analytics are key enablers for the next wave of innovation and growth across most industries and will address complex issues and systems that involve multiple objectives, alternatives, trade-offs, and large amounts of data and situations involving uncertainty or risk. This session will address new technical advances in these areas and provide valuable insights through the applications of real-world case studies.
2017-04-05
Event
Business Modeling/Operation Research/Big Data Analytics are key enablers for the next wave of innovation and growth across most industries and will address complex issues and systems that involve multiple objectives, alternatives, trade-offs, and large amounts of data and situations involving uncertainty or risk. This session will address new technical advances in these areas and provide valuable insights through the applications of real-world case studies.
2017-04-04
Event
Business Modeling/Operation Research/Big Data Analytics are key enablers for the next wave of innovation and growth across most industries and will address complex issues and systems that involve multiple objectives, alternatives, trade-offs, and large amounts of data and situations involving uncertainty or risk. This session will address new technical advances in these areas and provide valuable insights through the applications of real-world case studies.
2017-04-04
Event
Business Modeling/Operation Research/Big Data Analytics are key enablers for the next wave of innovation and growth across most industries and will address complex issues and systems that involve multiple objectives, alternatives, trade-offs, and large amounts of data and situations involving uncertainty or risk. This session will address new technical advances in these areas and provide valuable insights through the applications of real-world case studies.
CURRENT
2017-03-30
Standard
J2403DA_201703
This document is intended to supplement SAE J2403 by providing the content of Table 1, Table 2, and Table 3 from SAE J2403 in a form that can be sorted and searched for easier use. It is NOT intended as a substitute for the actual document, and any discrepancies between this Digital Annex and the published SAE J2403 document must be resolved in favor of the published document. This document provides the content of Table 1 and Table 2 published in SAE J2403 into the single table in the 'Term' tab, while the 'Recommended Term Definitions' tab provides the content of Table 3 in SAE J2403 and the 'Glossary' tab provides the content of Table 4 in SAE J2403.
2017-03-30
Magazine
Thought leadership at WCX17 Proliferating electrification and performance. Clarity of purpose Honda's 2017 Clarity Fuel Cell has impressive performance, zero emissions and zero range anxiety. Clarity is ready for the mainstream, but is hydrogen fuel? Lightweighting hinges on the details Multi-material design approaches require careful integration of all adjacent constituents. Haptic feedback for gesture-control HMI Mid-air gesture controls rely on sophisticated sensing to aid the human-machine interface and help keep drivers' eyes on the road. Road-efficient mud machine Jeep's new Compass benefits from a trick AWD system co-developed with GKN. Past as prelude to the future SAE's Mobility History Committee brings a trove of knowledge- and cool technology. The new Fellow from Ricardo Prof. Neville Jackson will be recognized as an SAE Fellow at WCX17.
2017-03-28
Technical Paper
2017-01-1141
Bashar Alzuwayer, Robert Prucka, Imtiaz Haque, Paul Venhovens
Abstract Fuel economy regulations have forced the automotive industry to implement transmissions with an increased number of gears and reduced parasitic losses. The objective of this research is to develop a high fidelity and a computationally efficient model of an automatic transmission, this model should be suitable for controller development purposes. The transmission under investigation features a combination of positive clutches (interlocking dog clutches) and conventional wet clutches. Simulation models for the torque converter, lock-up clutch, transmission gear train, interlocking dog clutches, wet clutches, hydraulic control valves and circuits were developed and integrated with a 1-D vehicle road load model. The integrated powertrain system model was calibrated using measurements from real-world driving conditions. Unknown model parameters, such as clutch pack clearances, compliances, hydraulic orifice diameters and clutch preloads were estimated and calibrated.
2017-03-28
Technical Paper
2017-01-0235
Qiuming Gong, Jimmy Kapadia
Abstract Plug-in hybrid electric vehicles (PHEV) have an EV mode driving range which can cover a portion of customer daily driving. This EV mode range affects the refuel frequency substantially compared with conventional vehicle. For a conventional vehicle, daily driving pattern, tank size and fuel economy are the factors affecting the refuel frequency. While for a PHEV, EV range is another factor would affect the results substantially. Traditional method of label range can’t represent real world driving range between fill-ups for PHEV well. How to accurately predict the PHEV refuel distance taking into account real world customer driving patterns and PHEV parameters become critical for PHEV system design and optimization. This paper presents real world big customer data based PHEV refuel distance estimation modeling. The target is to estimate PHEV refuel distance given several specific parameters such as EV range, hybrid mode fuel economy, tank size etc.
2017-03-28
Technical Paper
2017-01-0238
Velappan Shalini, Sridharan Krishnamurthy, Srinivasan Narasimhan
Abstract This study compares the model efficacy of Neural Network and Vector Auto Regression. Further it also analyses the impact of predictors controlling for total industry volume. Understanding both the methodologies has their distinctive advantages and disadvantages. Our empirical findings indicate that based on the characteristics of data such as non-stationary, non-linearity and non-normality paves the way for use of machine learning algorithm relative to econometrics technique. Our results suggest that data type and its characteristics are more important in determining the methodology than the methodology itself. In industry, econometrics methodologies are widely used due to their usage simplicity and its ability to explain the relationships in simple terms.
2017-03-28
Technical Paper
2017-01-1484
Giampiero Mastinu, Mario Pennati, Massimiliano Gobbi, Giorgio Previati, Federico Ballo
Abstract The ride comfort of three Alfa Romeo cars, namely Giulietta (1955), Alfetta (1972) and 159 (2005) has been assessed both objectively and subjectively. The three cars belong to the same market segment. The aim is to let young engineers or graduate students understand how technology has evolved and eventually learn a lesson from the assessed trend. A number of cleats have been fixed at the ground and the three cars have traversed such uneven surface. The objective assessment of the ride comfort has been performed by means of accelerometers fixed at the seat rails, additionally a special dummy developed at Politecnico di Milano has been employed. The subjective assessment has been performed by a panel of passengers. The match between objective and subjective ratings is very good. Simple mathematical models have been employed to establish a (successful) comparison between experimental and computational results. The ride comfort differs substantially among the cars.
2017-03-28
Technical Paper
2017-01-0232
Nizar Khemri, Hao Ying, Joseph Supina, Fazal Syed
Abstract Realistic vehicle fuel economy studies require real-world vehicle driving behavior data along with various factors affecting the fuel consumption. Such studies require data with various vehicles usages for prolonged periods of time. A project dedicated to collecting such data is an enormous and costly undertaking. Alternatively, we propose to utilize two publicly available vehicle travel survey data sets. One is Puget Sound Travel Survey collected using GPS devices in 484 vehicles between 2004 and 2006. Over 750,000 trips were recorded with a 10-second time resolution. The data were obtained to study travel behavior changes in response to time-and-location-variable road tolling. The other is Atlanta Regional Commission Travel Survey conducted for a comprehensive study of the demographic and travel behavior characteristics of residents within the study area.
2017-03-28
Technical Paper
2017-01-0894
Nishant Singh
Abstract Improving fuel economy has been a key focus across the automotive industry for several years if not decades. For heavy duty commercial vehicles, the benefits from minor gains in fuel economy can lead to significant savings for fleets as well as owners and operators. Additionally, the regulations require vehicles to meet certain GHG standards which closely translate to vehicle fuel economy. For current state of the art fuel economy technologies, incremental gains are so miniscule that measurements on the vehicle are inadequate to quantify the benefits. Engineers are challenged with high level of variability to make informed decisions. In such cases, highly controlled tests on Engine and Powertrain dynamometers are used, however, there is an associated variability even with these tests due to factors such as part to part differences, deterioration, fuel blends and quality, dyno control capabilities and so on.
2017-03-28
Technical Paper
2017-01-1625
Rajeev Kalamdani, Chandra Jalluri, Stephen Hermiller, Robert Clifton
Abstract Use of sensors to monitor dynamic performance of machine tools at Ford’s powertrain machining plants has proven to be effective. The traditional approach to convert sensor data to actionable intelligence consists of identifying single features from cycle based signatures and setting thresholds above acceptable performance limits based on trials. The thresholds are used to discriminate between acceptable and unacceptable performance during each cycle and raise alarms if necessary. This approach requires a significant amount of resource & time intensive set up work up-front and considerable trial and error adjustments. The current state does not leverage patterns that might be discernible using multiple features simultaneously. This paper describes enhanced methods for processing the data using supervised and unsupervised machine learning methods. The objective of using these methods is to improve the prediction accuracy and reduce up-front set up.
2017-03-28
Technical Paper
2017-01-1651
Douglas Thornburg, John Schmotzer, MJ Throop
Abstract Onboard, embedded cellular modems are enabling a range of new connectivity features in vehicles and rich, real-time data set transmissions from a vehicle’s internal network up to a cloud database are of particular interest. However, there is far too much information in a vehicle’s electrical state for every vehicle to upload all of its data in real-time. We are thus concerned with which data is uploaded and how that data is processed, structured, stored, and reported. Existing onboard data processing algorithms (e.g. for DTC detection) are hardcoded into critical vehicle firmware, limited in scope and cannot be reconfigured on the fly. Since many use cases for vehicle data analytics are still unknown, we require a system which is capable of efficiently processing and reporting vehicle deep data in real-time, such that data reporting can be switched on/off during normal vehicle operation, and that processing/reporting can be reconfigured remotely.
2017-03-28
Journal Article
2017-01-0237
Jonas Biteus, Tony Lindgren
Abstract Maintenance planning of trucks at Scania have previously been done using static cyclic plans with fixed sets of maintenance tasks, determined by mileage, calendar time, and some data driven physical models. Flexible maintenance have improved the maintenance program with the addition of general data driven expert rules and the ability to move sub-sets of maintenance tasks between maintenance occasions. Meanwhile, successful modelling with machine learning on big data, automatic planning using constraint programming, and route optimization are hinting on the ability to achieve even higher fleet utilization by further improvements of the flexible maintenance. The maintenance program have therefore been partitioned into its smallest parts and formulated as individual constraint rules. The overall goal is to maximize the utilization of a fleet, i.e. maximize the ability to perform transport assignments, with respect to maintenance.
2017-03-28
Journal Article
2017-01-0236
Zhigang Wei, Kamran Nikbin
In the Big Data era, the capability in statistical and probabilistic data characterization, data pattern identification, data modeling and analysis is critical to understand the data, to find the trends in the data, and to make better use of the data. In this paper the fundamental probability concepts and several commonly used probabilistic distribution functions, such as the Weibull for spectrum events and the Pareto for extreme/rare events, are described first. An event quadrant is subsequently established based on the commonality/rarity and impact/effect of the probabilistic events. Level of measurement, which is the key for quantitative measurement of the data, is also discussed based on the framework of probability. The damage density function, which is a measure of the relative damage contribution of each constituent is proposed. The new measure demonstrates its capability in distinguishing between the extreme/rare events and the spectrum events.
2017-03-28
Journal Article
2017-01-0245
Kanna Akella, N. Venkatachalam, K. Gokul, Keunho Choi, Ramachandraprabhu Tyakal
Abstract Voice of customer is typically captured through multiple connect points like surveys, warranty claims, social media, and so on. Customer verbatim is collected through these connect points to encourage free expression of opinion by customers. Such verbatim data is generally of high value and is typically analyzed using Natural Language Processing (NLP) techniques for translating into influencing actions in manufacturing, customer service, marketing, and product development departments. One of the challenges in analyzing unstructured verbatim data is to map that data onto appropriate concern codes (CCCs), which are typically used in automotive firms for tracking quality and satisfaction metrics. These concern codes map to a hierarchy of function areas in the organization aimed at improving product, service and hence the customer’s overall experience.
2017-03-28
Journal Article
2017-01-0241
Thiago B. Murari, Paulo Ungaretti, Marcelo A. Moret
Abstract Geometric Dimensioning and Tolerancing is used to describe the allowed feature variations regarding the product design. Tolerance specification is important in many stages of all phases on product development. The product development engineering need to define the symbols to use on the Feature Control Frame of every component. Since the component function has an increment on its complexity year over year, it is not trivial to define those symbols anymore. The determination of dimensional tolerance shall be preceded by careful specification of the types of tolerance and symbols that will be applied in controlled features. Poor tolerance specifications can increase the production cost, require late product changes or lead to legal issues.
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