Acceptance Sampling Plans for Pipeline Condition Assessment

Abstract

Pipeline condition data collection and assessment is the first step for strategic infrastructure asset management and planning. However, since condition data collection and assessment is a highly expensive and time-consuming process, comprehensive asset management often fails even before it starts. Many municipalities perform periodic closed-circuit television (CCTV) inspections as a preventive maintenance and management strategy. However, due to limited budgets, not all the pipelines are inspected periodically as initially planned and only some parts that are believed to have some problems are chosen to be inspected. Municipalities often hesitate to use sampling inspection because of possible risks of not assessing the pipe assets correctly that may end up as liability issues. This paper shows the calculations of the possible risks of sampling and the techniques to control those risks. Acceptance sampling with the rectifying inspection method was used, which is a method widely used in quality control in the manufacturing industry. First, pipelines were categorized based on age, material, and any other characteristics that were believed to be reliable criteria for categorizing pipe assets in similar conditions. Then randomly selected pipelines in each category were inspected. The amount of the selection was determined by the municipality’s budget situation. The acceptance sampling with rectifying inspection method showed the improvement of average outgoing quality (AOQ). By repairing the defects in a sample inspection, not only was the quality level statistically measured, but the overall quality level also improved. By differing the sample sizes and the acceptance rates, optimization between inspection cost and quality can be achieved. The sampling strategy proposed in this paper presents the optimal CCTV inspection sampling strategy for an accurate condition estimation and provides the basis for the asset management plan.