International Conference on Statistics and Analytical Methods in Automotive Engineering

The IMechE is the United Kingdom's qualifying body for mechanical engineers and the home of mechanical engineers for over 150 years. Around 75,000 engineers world-wide are members.

• Part 1 Engines: Bayesian statistics in engine mapping, M.C. Ward et al Applications of advanced modelling methods in engine development, J. Seabrook et alApplication of adaptive online DoE techniques for engine ECU calibration, Y. Raynaud et alRadial basis functions for engine modelling, T.M. Morton and S. KnottAn engine mapping case study - a two-stage regression approach, D.W. Rose et alApplication of a pareto-based evolutionary algorithm to fuel injection optimization, O. Roudenko et alA parametric inlet port design tool for multi-valve diesel engines, M.C. Bates and M.R. HeikalPractical application of DoE methods in the development of production internal combustion engines, K. Roepke et alA model and methodology used to assess the robustness of vehicle emissions and fuel economy characteristics, P.J. Shayler et alThe application of multivariate correlated techniques to driveability analysis, S.G. Pickering et alPart 2 Vehicles, systems and components: experiencing customer vehicle comfort requirements using concept synthesis techniques, D.J. Fothergill and M. Allman-WardDesigning for six sigma reliability, D. Brunson et alDimensional variation analysis for automotive hybrid aluminium body structures, R. Koganti and M. ZaluzecReliability-based multidisciplinary design optimization of vehicle structures, R.J. Yang et alAn analysis methodology for the simulation of vehicle pedestrian accidents, N. Le Glatin et alSensitivity of transmission noise and vibration to manufacturing and assembly process drift and variability, S.M. Athervale et alThe improvement of vehicle performance using predictive diagnostic algorithms, L. Borgarello et alReliability modelling using warranty data, I.F. Campean and D. BrunsonApplication of proportional hazard model to tyre design analysis, V.V. Krivtsov et alBetter understanding of automotive manufacturing reliability data using a spreadsheet-based model fitting tool, M. Linsley et alAchieving robust designs through the use of "design for Six Sigma", D. Mortimer