Multi‐response robust screening in quality construction blue‐printing

Abstract

Purpose

The aim of this paper is to circumvent the multi‐distribution effects and small sample constraints that may arise in unreplicated‐saturated fractional factorial designs during construction blueprint screening.

Design/methodology/approach

A simple additive ranking scheme is devised based on converting the responses of interest to rank variables regardless of the nature of each response and the optimization direction that may be issued for each of them. Collapsing all ranked responses to a single rank response, appropriately referred to as “Super‐Ranking”, allows simultaneous optimization for all factor settings considered.

Research limitations/implications

The Super‐Rank response is treated by Wilcoxon's rank sum test or Mann‐Whitney's test, aiming to establish possible factor‐setting differences by exploring their statistical significance. An optimal value for each response is predicted.

Practical implications

It is stressed, by example, that the model may handle simultaneously any number of quality characteristics. A case study based on a real geotechnical engineering project is used to illustrate how this method may be applied for optimizing simultaneously three quality characteristics that belong to each of the three possible cases, i.e. “nominal‐is‐best”, “larger‐is‐better”, and “smaller‐is‐better” respectively. For this reason, a screening set of experiments is performed on a professional CAD/CAE software package making use of an L₈(2⁷) orthogonal array where all seven factor columns are saturated by group excavation controls.

Originality/value

The statistical nature of this method is discussed in comparison with results produced by the desirability method for the case of exhausted degrees of freedom for the error. The case study itself is a unique paradigm from the area of construction operations management.

Citation

Besseris, G.J. (2009), "Multi‐response robust screening in quality construction blue‐printing", International Journal of Quality & Reliability Management, Vol. 26 No. 6, pp. 583-613. https://doi.org/10.1108/02656710910966147