Assessing the road-damaging potential of heavy vehicles

The relative influence of various heavy vehicle design features on road-damaging potential is discussed. Testing procedures that could be used to measure the road-damaging potential of heavy vehicles are examined. A validated vehicle simulation is used to examine some of the characteristics of dynamic tyre forces generated by typical leaf sprung and air sprung articulated heavy vehicles for typical highway conditions. The proposed EC suspension test is simulated and the results compared with dynamic tyre forces generated under highway conditions. It is concluded that the road-damaging potential of a vehicle cannot be assessed by the simplistic parametric measurement of the proposed EC test. It is questionable whether a vehicle that passes the test will be any more 'road friendly' than one that fails.

Value of information in product recovery decisions: A Bayesian approach

There is a widespread recognition of the need for better information sharing and provision to improve the viability of end-of-life (EOL) product recovery operations. The emergence of automated data capture and sharing technologies such as RFID, sensors and networked databases has enhanced the ability to make product information; available to recoverers, which will help them make better decisions regarding the choice of recovery option for EOL products. However, these technologies come with a cost attached to it, and hence the question 'what is its value?' is critical. This paper presents a probabilistic approach to model product recovery decisions and extends the concept of Bayes' factor for quantifying the impact of product information on the effectiveness of these decisions. Further, we provide a quantitative examination of the factors that influence the value of product information, this value depends on three factors: (i) penalties for Type I and Type II errors of judgement regarding product quality; (ii) prevalent uncertainty regarding product quality and (iii) the strength of the information to support/contradict the belief. Furthermore, we show that information is not valuable under all circumstances and derive conditions for achieving a positive value of information. © 2010 Taylor & Francis.