Abstract
From the 1990s to now, transportation maintenance quality assurance (MQA) programs have been developed to ensure that maintenance quality is being achieved. MQA programs must be capable of detecting insufficient maintenance efforts, poor material performance, and incorrect procedures when evaluating end-product performance. At the Maintenance Quality Assurance Peer Exchange held at Madison, Wisconsin, in October 2004, participants expressed interest in exploring how statistical tools might be more effectively applied in MQA programs. The purpose of this paper is to provide maintenance practitioners with knowledge of how to understand and use statistics in MQA programs. Literature pertaining to recent efforts in this area was reviewed and synthesized. In addition, hazardous debris data from Wisconsin and level of service data from North Carolina were analyzed to demonstrate how an agency could apply traditional statistical methods such as analysis of variance, confidence limits, means comparison, data stratification, and sample size determination to an MQA program.
Get full access to this article
View all access options for this article.