A modelling strategy for vehicle dynamics using Pro/ENGINEER

Vehicle dynamics modelling can provide vehicle designers with vehicle performance data that can assist with the efficient development of more refined cars. However, such models are notoriously complicated requiring the user to have a considerable understanding of vehicle dynamics.

Modelling and improving maintenance decisions:Having foresight with simulation and artificial intelligence

Machine breakdowns are one of the main sources of disruption and throughput fluctuation in highly automated production facilities. One element in reducing this disruption is ensuring that the maintenance team responds correctly to machine failures. It is, however, difficult to determine the current practice employed by the maintenance team, let alone suggest improvements to it. 'Knowledge based improvement' is a methodology that aims to address this issue, by (a) eliciting knowledge on current practice, (b) evaluating that practice and (c) looking for improvements. The methodology, based on visual interactive simulation and artificial intelligence methods, and its application to a Ford engine assembly facility are described. Copyright © 2002 Society of Automotive Engineers, Inc.

Identification of industrial sources of airborne heavy metal pollution in urban areas

The research examines the deposition of airborne particles which contain heavy metals and investigates the methods that can be used to identify their sources. The research focuses on lead and cadmium because these two metals are of growing public and scientific concern on environmental health grounds. The research consists of three distinct parts. The first is the development and evaluation of a new deposition measurement instrument - the deposit cannister - designed specifically for large-scale surveys in urban areas. The deposit cannister is specifically designed to be cheap, robust, and versatile and therefore to permit comprehensive high-density urban surveys. The siting policy reduces contamination from locally resuspended surface-dust. The second part of the research has involved detailed surveys of heavy metal deposition in Walsall, West Midlands, using the new high-density measurement method. The main survey, conducted over a six-week period in November - December 1982, provided 30-day samples of deposition at 250 different sites. The results have been used to examine the magnitude and spatial variability of deposition rates in the case-study area, and to evaluate the performance of the measurement method. The third part of the research has been to conduct a 'source-identification' exercise. The methods used have been Receptor Models - Factor Analysis and Cluster Analysis - and a predictive source-based deposition model. The results indicate that there are six main source processes contributing to deposition of metals in the Walsall area: coal combustion, vehicle emissions, ironfounding, copper refining and two general industrial/urban processes. |A source-based deposition model has been calibrated using facctorscores for one source factor as the dependent variable, rather than metal deposition rates, thus avoiding problems traditionally encountered in calibrating models in complex multi-source areas. Empirical evidence supports the hypothesised associatlon of this factor with emissions of metals from the ironfoundry industry.

Towards a theoretical framework for human performance modelling within manufacturing systems design

The performance of direct workers has a significant impact on the competitiveness of many manufacturing systems. Unfortunately, system designers are ill equipped to assess this impact during the design process. An opportunity exists to assist designers by expanding the capabilities of popular simulation modelling tools, and using them as a vehicle to better consider human factors during the process of system design manufacture. To support this requirement, this paper reports on an extensive review of literature that develops a theoretical framework, which summarizes the principal factors and relationships that such a modelling tool should incorporate.

A road safety performance indicator for vehicle fleet compatibility

This paper discusses the development and the application of a safety performance indicator which measures the intrinsic safety of a country's vehicle fleet related to fleet composition. The indicator takes into account both the ‘relative severity’ of individual collisions between different vehicle types, and the share of those vehicle types within a country's fleet. The relative severity is a measure for the personal damage that can be expected from a collision between two vehicles of any type, relative to that of a collision between passenger cars. It is shown how this number can be calculated using vehicle mass only. A sensitivity analysis is performed to study the dependence of the indicator on parameter values and basic assumptions made. The indicator is easy to apply and satisfies the requirements for appropriate safety performance indicators. It was developed in such a way that it specifically scores the intrinsic safety of a fleet due to its composition, without being influenced by other factors, like helmet wearing. For the sake of simplicity, and since the required data is available throughout Europe, the indicator was applied to the relative share of three of the main vehicle types: passenger cars, heavy goods vehicles and motorcycles. Using the vehicle fleet data from 13 EU Member States and Norway, the indicator was used to rank the countries’ safety performance. The UK was found to perform best in terms of its fleet composition (value is 1.07), while Greece has the worst performance with the highest indicator value (1.41).