Advanced quality systems : probabilistic optimization for profit (Prob.O.Prof) software
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Advanced quality systems : probabilistic optimization for profit (Prob.O.Prof) software

Filetype[PDF-1.34 MB]

  • English

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      Final report
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    • Abstract:
      Contractors constantly have to make decisions regarding how to maximize profit and minimize risk on paving projects. With more and more States adopting incentive/disincentive pay adjustment provisions for quality, as measured by various acceptance quality characteristics (AQCs), a contractor likely has to evaluate several options before selecting an optimum target quality that accomplishes this goal. The greater the number of AQCs, the more complex the assessment the contractor is required to perform, and the less intuition and experience can be relied upon. Highway agencies also need to evaluate their specifications to determine the appropriateness of the process and criteria, and to ensure that the specifications do not have any undesirable consequences. If, for example, an agency learns that there is an economic benefit for contractors to construct pavements at substandard quality levels because of inadequate disincentives, then the agency may need to adjust the specification pay schedule accordingly. Prob.O.Prof 2.0 is a newly developed software tool that can be used by contractors and agencies alike to make keen business decisions regarding the levels of pavement quality to target. This probabilistic, Microsoft Excel®-based program is an enhancement of the original Prob.O.Prof program, developed as part of a Ph.D. dissertation at the University of Florida (Vidalis et al., 2006). It entails a major expansion of the original program through the incorporation of three additional State department of transportation (DOT) portland cement concrete (PCC) pavement specifications and the introduction of four State DOT hot mix asphalt (HMA) pavement specifications. As a result of this expansion, other forms of quality measures besides percent within limits (PWL), such as average absolute deviation (AAD), averages, and average minus standard deviation, can be evaluated, along with other AQCs and pay factor schedules.
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