Quality Control

In a broad sense, every organization has a quality control program; in some manner, they assess production and construction and control their end product quality based on those assessments. Often, this method is not formalized but it exists to some extent in every organization. So then, what is quality control and what is an ideal quality control program?

In the narrowest sense, quality control seeks to control the level of quality being produced in the end product. This level of quality consists of two key components:

1. Target value. This is the goal set for a certain material characteristic. As a minimum it should conform to standards and be achievable. For example, on a specific contract the specified in-place HMA density might be 92-percent of theoretical maximum density. Therefore, a contractor may set an in-place density target value at 93-percent of TMD. This meets (in fact, it exceeds) the standard.
2. Variability. This describes how much a process varies from item-to-item (or location-to-location). A process that meets the target value on average but is highly variable will result in pavement locations where the material characteristic is unacceptable.

Thus, a quality control program consists of (1) the actions and considerations necessary to assess production and construction processes and (2) setting the end product target value and controlling variability. In order for a quality control program to be effective it should (1) base actions and decisions on measurable results and (2) be statistically valid.

Quality control actions and considerations should be based on objective evidence and not subjective opinion. Consider the difference between changing a roller pattern based on (1) an inspector’s opinion that compaction is inadequate or (2) consistently low-density test results. While the first option is subjective, the second option results in unequivocal evidence from which confident actions can be taken. This does not mean that experience and expertise are not valuable but rather that they should be used to determine what measurements to take and how to improve the process. A training manual for Komatsu Ltd. in Japan says it this way (Walton, 1986¹):

“The first step in quality control is to judge and act on the basis of facts. Facts are data such as length, time, fraction defective and sales amount. Views not backed by data are more likely to include personal opinions, exaggeration and mistaken impressions. Data volume has nothing to do with accuracy of judgment. Data without context or incorrect data are not only invalid but sometimes harmful as well. It is necessary to know the nature of that data and that proper data be picked as well.”

Since variability can only be accurately described and evaluated through statistical methods, quality control involves statistics. Fortunately, these statistics are relatively straightforward. For instance, control charts are frequently used to analyze production results (e.g., production, density, strength).

Setting Targets and Reducing Variability

For HMA, the job mix formula (JMF) sets the production targets: it records the mix design and the expected properties of the resulting mixture of aggregate and asphalt binder. Testing during production and placement shows whether those targets are being met.

Field samples should be taken at random locations, because samples always taken from the center of the lane or at a fixed spacing do not represent the whole job. Purely random sampling can leave some lots unsampled and others sampled several times, so samples are usually taken at random locations within predetermined, regular intervals.

Several practices help reduce variability:

• Pre-project planning. Reviewing past projects and the project requirements, and matching plant production to paving speed, gives steadier production and a more predictable schedule.
• Test strips. A test strip at the start of a project verifies the mix design and laydown procedures before "for pay" mix is placed. It can be built on a shoulder or another non-critical part of the job, and it helps settle start-up problems, calibrate production rate and paver and roller speeds, and set a roller pattern that reaches the required density in the fewest passes. A test strip may be repeated after significant changes during the project and may be unnecessary for a mix the contractor knows well.
• Timely testing and reporting. Testing at regular intervals, with results reported promptly, lets trends be noticed before they become specification failures. Control charts are a common way to present these results.

@misc{pavint-quality-control,
  author = {{Pavement Interactive}},
  title = {Quality Control},
  year = {2026},
  publisher = {HeadLight},
  howpublished = {\url{https://pavementinteractive.org/reference-desk/qc-qa/quality-assurance/quality-control/}},
  note = {Accessed [date]}
}