Effect of variability on end product specifications

In the past 10 years a number of transportation agencies have adopted end product specifications (EPS) as part of their quality assurance programs. The basic premise behind EPS is that the contractor is remunerated based on how well their final product meets specifications set by the transportation agency. For example, an EPS for asphalt concrete pavement might state that the field density should be within 97% of the Marshall density. If the field density is below this value, the contractor would receive a penalty, whereas if the field density is above this value the contractor would receive a bonus. Because of uncertainty regarding the exact relationship between the reduced (or increased) performance of the product and the measure of effectiveness, the price adjustments were established based on engineering judgment and were indirectly related to anticipated performance. For example, the transportation agencies pavement engineers would look at past performance in developing guidelines for what reasonably could be expected for a given EPS. However, the fact that many agencies collect and save EPS data means that the variability in the EPS may now be analyzed and the effects studied. This paper demonstrates how the data collected from an EPS, and in particular the variability measures identified from these data, may be used to identify optimal testing strategies and to identify the risk, to both the producer and the agency, inherent in the bonus/penalty schedules. In addition, the trade-off between sample size and testing accuracy will be demonstrated. Last, the implications of incorporating variance within the EPS will be explored. Data obtained from Alberta Transportation and Utilities on Marshall density and field density EPS measurements will be used to illustrate the methodology and demonstrate the key components of the paper.