This paper examines mechanisms underlying the phenomenon that, under some conditions, adaptive one-factor-at-a-time experiments outperform fractional factorial experiments in improving the performance of mechanical engineering systems. Five case studies are presented, each based on data from previously published full factorial physical experiments at two levels. Computer simulations of adaptive one-factor-at-a-time and fractional factorial experiments were carried out with varying degrees of pseudo-random error. For each of the five case studies, the average outcomes are plotted for both approaches as a function of the strength of the pseudo-random error. The main effects and interactions of the experimental factors in each system are presented and analyzed to illustrate how the observed simulation results arise. The case studies show that, for certain arrangements of main effects and interactions, adaptive one-factor-at-a-time experiments exploit interactions with high probability despite the fact that these designs lack the resolution to estimate interactions. Generalizing from the case studies, four mechanisms are described and the conditions are stipulated under which these mechanisms act.
Skip Nav Destination
e-mail: danfrey@mit.edu
e-mail: jrajesh@mit.edu
Article navigation
September 2006
Research Papers
The Mechanisms by Which Adaptive One-factor-at-a-time Experimentation Leads to Improvement
Daniel D. Frey,
Daniel D. Frey
Department of Mechanical Engineering and Engineering Systems Division,
e-mail: danfrey@mit.edu
Massachusetts Institute of Technology
, Room 3-449D, Cambridge, MA 02139
Search for other works by this author on:
Rajesh Jugulum
Rajesh Jugulum
Department of Mechanical Engineering,
e-mail: jrajesh@mit.edu
Massachusetts Institute of Technology
, Room 3-449G, Cambridge, MA 02139
Search for other works by this author on:
Daniel D. Frey
Department of Mechanical Engineering and Engineering Systems Division,
Massachusetts Institute of Technology
, Room 3-449D, Cambridge, MA 02139e-mail: danfrey@mit.edu
Rajesh Jugulum
Department of Mechanical Engineering,
Massachusetts Institute of Technology
, Room 3-449G, Cambridge, MA 02139e-mail: jrajesh@mit.edu
J. Mech. Des. Sep 2006, 128(5): 1050-1060 (11 pages)
Published Online: August 31, 2005
Article history
Received:
April 25, 2005
Revised:
August 31, 2005
Citation
Frey, D. D., and Jugulum, R. (August 31, 2005). "The Mechanisms by Which Adaptive One-factor-at-a-time Experimentation Leads to Improvement." ASME. J. Mech. Des. September 2006; 128(5): 1050–1060. https://doi.org/10.1115/1.2216733
Download citation file:
Get Email Alerts
Large Language Models for Predicting Empathic Accuracy Between a Designer and a User
J. Mech. Des (April 2025)
Repurposing as a Decommissioning Strategy for Complex Systems: A Systematic Review
J. Mech. Des (May 2025)
A Dataset Generation Framework for Symmetry-Induced Mechanical Metamaterials
J. Mech. Des (April 2025)
Related Articles
Conducting Non-adaptive Experiments in a Live Setting: A Bayesian Approach to Determining Optimal Sample Size
J. Mech. Des (March,2020)
Optimal Experimental Design of Human Appraisals for Modeling Consumer Preferences in Engineering Design
J. Mech. Des (July,2009)
Evaluation of Idea Generation Methods for Conceptual Design: Effectiveness Metrics and Design of Experiments
J. Mech. Des (December,2000)
One Step at a Time
Mechanical Engineering (July,2004)
Related Proceedings Papers
Related Chapters
Standard Usage and Transformation of Taguchi-Class Orthogonal Arrays
Taguchi Methods: Benefits, Impacts, Mathematics, Statistics and Applications
Regression
Engineering Optimization: Applications, Methods, and Analysis
STRUCTURAL RELIABILITY ASSESSMENT OF PIPELINE GIRTH WELDS USING GAUSSIAN PROCESS REGRESSION
Pipeline Integrity Management Under Geohazard Conditions (PIMG)