Development of methodology for highway agencies to follow in establishing optimum acceptance plans for pavements

The objective of this research is to develop an approach for establishing, optimum pavement and bridge construction acceptance plans that minimize the overall life cycle cost. To this end, an understanding of theoretical principles underlying statistical acceptance-sampling plans and current practices is essential. In this research, emphasis is placed on developing a methodology for the determination of the optimum sample size (i.e., number of samples) in acceptance sampling using a Bayesian statistic approach. A framework is established to integrate the many aspects that deal with each phase of the pavement life cycle in order to design, construct, and maintain the pavement at a minimum life cycle cost. Operating characteristics curves are used to evaluate the risk associated with optimum sample size derived from the mathematical-statistical cost model. As part of the comprehensive framework, significant attention is given to the development of guidelines for the evaluation of quality characteristics and tolerances using Genichi Taguchi methods. Finally, a pay adjustment method based on the quadratic loss function is developed to compensate for loss in quality resulting from the product's failure to meet the target design value. To illustrate this approach, estimated sampling cost and life cycle cost of pavement are used to determine the optimum sample size and the acceptance limits for the example. Boundary conditions are formulated and used to perform a sensitivity analysis; a discussion on the performance of the model as compared to statistically based models is also provided.