Olive oil, an important commodity of the Mediterranean region and a main ingredient of their world-renowned diet (see sidebar), must meet stringent European guidelines to achieve the coveted status of "extra virgin." Oils made from single cultivars (a particular cultivated variety of the olive tree) will at times fall into the lower "virgin" category due to seasonal variation. Then it becomes advantageous to blend in one or more superior oils. This is a great case to become acquainted with the tools of mixture design for optimal formulation.
An agricultural equipment manufacturer asked Henkel to help optimize a tough coating application using DOE.
Via mixture design of experiments (DOE) Alberto-Culver developed a new line of scrubs that far exceeded the performance of what they thought was possible. The formulator said "We selected Design-Expert software from Stat-Ease because of its exceptional capabilities in the design and analysis of mixture experiments. The end result is that we can get products to market faster and at a lower cost than with conventional experiment designs."
A statistically based design of experiments (DOE) approach developed specifically for mixtures was used to formulate a blend of rayon fibers that produced maximal tampon absorbency.
An experimental investigation was carried out in the PT-1 in order to determine the best porosity distribution in order to maximize the reduction of the wall interference over the widest possible Mach number range. Over 360 test points were measured on different models and wall porosity configurations over the selected mach number range to find out the minimum interference configuration for the PT-1; however, as these results are not wind tunnel-specific, they are expected to be applicable to all similar facilities. The optimum porosity distribution has been achieved trough an experiment designed with a Modern Design Of Experiment (MDOE) approach.
Diasorin used DOE to evaluate the robustness of its process for manufacturing an alpha-1-antitrypsin (AAT) assay. The results provided a considerable degree of confidence that existing in-process quality control criteria sufficed for being assured of meeting finished product requirements. This case study provides an excellent example of how DOE can reduce the time required to perform a latitude study while delivering statistical analysis that increases the degree of confidence in the study.
A large printing company tasked a Lean Six Sigma project team with finding a way to reduce setup time and costs in a department consisting of 33 Kluge presses. The results of the DOE led to a reduction of 5% in printing costs by moving to a less expensive foil for that job, and other knowledge gained from the experiment led to a 40% reduction in setup time over the last two years.