[article]
| Titre : |
How to handle hard-to-change factors or components in a design experiment |
| Type de document : |
texte imprimé |
| Auteurs : |
Mark J. Anderson, Auteur |
| Année de publication : |
2018 |
| Article en page(s) : |
p. 46-49 |
| Note générale : |
Bibliogr. |
| Langues : |
Américain (ame) |
| Catégories : |
Plan d'expérience
|
| Index. décimale : |
658.56 Contrôle de la production. Contrôle de la qualité, emballage |
| Résumé : |
The traditional approach to experimentation—often referred to as the "scientific rnethod"—requires chang¬ing only one factor at a time (OFAT). Unfortunately, the relatively simplistic OFAT approach falls flat when users are faced with factor or component interactions, for example, the combined impact of time and temperature on a process, or two reactants in a mixture. Because inter¬actions abound in the coatings industry, the multifactor and multicomponent test matrices provided by the design of experiments (DOE) approach appeal greatly to process engineers and formulators.' However, carrying out DOE correctly réquires that runs be randomized whenever possible to counteract the bias that may be introduced by time-related trends, such as aging of materials, increasing humidity, and the like.
But what if complete randomization proves to be sa inconvenient that it becomes impossible ta run a statisti¬cally designed experiment? In this case, a specialized form of design called "split plot" becomes attractive, because of its ability to effectively group hard-to-change (HTC) factors.' A split plot accommodates bath HTC factors, for instance, the conditions in an electrostatic powder-coating chamber. and those factors that are easy to change (ETC), such as the part precleaning and preparation. |
| Note de contenu : |
- Case in point : the use of a split plot in an industrial experiment
- Combines mixture-process experiments made far easier
- Caveats
- Closing thoughts
- FIGURES : 1. Comparing a completely randomized experiment (vs one that is divided into split plots - 2. In this effect graph, 3D bars show the impact of temperature vs coating on corrosion resistance - the higher the better - 3. Three component mixture combined with one process factor - 4. Split plot for grouping blends and then processing them
- TABLE : Using a split-plot design to increase the corrosion resistance of steel bars |
| En ligne : |
https://drive.google.com/file/d/1NGjRsxr81PHndVi-qPd624QryQwep2vG/view?usp=drive [...] |
| Format de la ressource électronique : |
Pdf |
| Permalink : |
https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=30053 |
in COATINGS TECH > Vol. 15, N° 2 (02/2018) . - p. 46-49
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