Reliability-Based Optimal Inspection Interval

Infrastructure management in the past may not used the optimal planning for maintenance and rehabilitation. Many governments developed methods for the maintenance operation and rehabilitation planning. They concerned the three main processes. Those are, how to inspect the performance of the infrastructure, the appropriate frequency of inspection data, and the best way to find the maintenance and rehabilitation technique on the appropriate time.

Most development interest in the performance index such as condition index or roughness index, it is the method to optimize the maintenance and rehabilitation planning, and the optimal inspection time interval. The sample unit management in term of the number of sample unit and inspection interval does not have the optimal technique. This omission made many problems in every country about the inspection tradeoff between time, cost, and accuracy.

Mr. Dolyawich Nongpong made a study which main objective was to optimize the inspection interval for the pavement inspection. The secondary objectives of his study were to (1) develop the reliability functions that are derived from IRI data. This function can help deciding the inspection interval and pavement reliability, (2) show the percentage of inspection sample reduction based on the traffic volume of the pavement; (3) develop the modified model that is derived from the cost data. This function is developed based on the number of inspection sample; and (4) show the percentage difference of the inspection costs between the calculation cost and the actual cost.

Conclusions

The important conclusions for Mr. Nongpong’s research are:
1. The optimal inspection interval is related to the traffic volume and the pavement performance.
2. The current technique to collect IRI data every kilometer is not the optimal sample.
3. The most appropriate reliability function is the lognormal type.
4. The cost model is reliable to estimate the cost for inspection IRI data.
5. The reliability functions in this study are reliable and acceptable.
6. The optimal inspection intervals in this study are reliable and acceptable.
7. The cost model requires the development for more reasonable cost factor in the future work when the cost data is available.

His thesis abstract is copied and posted.

ABSTRACT

Highway agencies spend a large amount of budget in collecting the pavement condition data. Visual inspection is a time-consuming and expensive task. Most agencies sample the inspection areas and use the selected sample size to represent the condition of the entire area. Decreasing the number of sample size can reduce the total inspection cost and time, but it may jeopardize the overall data quality. Reliability can be defined as a probability of a non-failure over the specific time. The reliability of the pavement plays an important role in the life cycle cost analysis. It can be viewed as the subset of the pavement quality that satisfies the users’ requirement and can be used to determine the expected service life of the pavement as well.

This main objective of this research is to apply the reliability theory to determine the optimal pavement inspection intervals and the appropriate sample size for pavement inspection. The relationship between reliability values and the number of sample units is investigated. The analysis used in this study is based on the relationship between the number of sample units and their reliability values. Traffic volumes are grouped to investigate the sensitivity of different parameters on the reliability values. This paper presented the optimal pavement inspection intervals determined based on the developed reliability values and the appropriate inspection sample size for highway agencies to balance between data quality issue and inspection cost control.